Drug Therapy

From Neurology/Chronic Pain Management Services, Department of Veterans Affairs (VA) Maryland Health Care System, Baltimore VA Medical Center, Baltimore, MD (Dr. Uche), and School of Nursing, Washburn University, Topeka, KS (Drs. Jamison and Waugh).

Abstract

Objective: The purpose of this quality improvement project was to abstract and analyze previously collected data from veterans with high-impact chronic pain who attended the Empower Veterans Program (EVP) offered by a Veterans Administration facility in the northeastern United States.

Methods: This quality improvement project used data collected from veterans with chronic pain who completed the veterans health care facility’s EVP between August 2017 and August 2019. Pre- and post-intervention data on pain intensity, pain interference, quality of life, and pain catastrophizing were compared using paired t-tests.

Results: Although data were abstracted from 115 patients, the final sample included 67 patients who completed both pre-and postintervention questionnaires. Baseline measures of completers and noncompleters were similar. Comparison of pre and post mean scores on completers showed statistically significant findings (P = .004) based on the Bonferroni correction. The medium and large effect sizes (Cohen’s d) indicated clinically significant improvements for veterans who completed the program. Veterans reported high levels of satisfaction with the program.

Conclusion: Veterans with chronic high-impact noncancer pain who completed the EVP had reduced pain intensity, pain interference, pain catastrophizing as well as improved quality of life and satisfaction with their health.

Keywords: musculoskeletal pain, Veterans Affairs, complementary and integrative health, acceptance and commitment therapy, mind-body therapies, whole health, multidisciplinary pain management.

More than 100 million American adults suffer from chronic pain; costs associated with managing chronic pain are approximately $635 billion each year.¹ Chronic pain is prevalent among military veterans, affecting one-third of the 9 million veterans who receive care from Veterans Health Administration (VHA) facilities.² The biopsychosocial impact of chronic pain on the general population, and specifically on veterans, has been compounded by the opioid crisis. The effects of chronic pain and the opioid crisis have fueled interest in the use of complementary and integrative health (CIH) modalities in the management of chronic noncancer pain. Providers are increasingly developing treatment programs that incorporate CIH in their management of chronic noncancer pain.

One such program is the Empower Veterans Program (EVP). Originally developed at the Atlanta Veterans Affairs Health Care System, the EVP is a CIH modality based on the biopsychosocial model of pain developed by psychiatrist George Engel in 1977.³ The biopsychosocial model of pain recognizes that pain is a complex, multidimensional, biopsychosocial experience. Under this model, the mind and body work in unison as interconnected entities. Because the model acknowledges biological, psychological, and social components of pain and illness,⁴ treatment focuses on all aspects of a person’s health, life, and relationships.

The EVP fits into the VHA Pain Management Stepped Care Model and is an adjunctive complement for that model.^5-7 The EVP complements care at the first step, where patient/family provide self-care and where care is provided by patient-aligned primary care teams, at the second step, which includes secondary consultation with multidisciplinary pain medicine specialty teams and other specialists, and at the third step, with the addition of tertiary interdisciplinary pain centers.

The VA Maryland Health Care System (VAMHCS) implemented the EVP as part of a quality improvement project for the management of chronic pain. The objectives of the program were to reduce pain intensity, pain catastrophizing, and pain interference, as well as improve functionality and quality of life among veterans with chronic high-impact noncancer pain. More than 2 years after the program was implemented, collected data had not been analyzed. The purpose of this quality improvement project was to abstract and analyze the previously collected data from veterans with high-impact chronic pain who attended an EVP offered by the VAMHCS. The results of the data analysis were used to inform decisions regarding the future of the program.

Methods

This quality improvement project used the Plan-Do-Study-Act (PDSA) process.⁸ The first 2 phases of the PDSA cycle (Plan and Do) were completed by a team of VA employees from the VAMHCS, who donated their time to establish and implement the program at the project site. This team consisted of psychologists, a physical therapist, a social worker, and a chaplain, and included support from medical administrative staff. This team planned and implemented the EVP at the VA facility based on the model developed at the Atlanta VA Health Care System. During the “Do” phase, the team collected data on pain intensity, pain interference, quality of life, and pain negative cognition (catastrophizing) before the intervention and post intervention. They also collected data on program outcome (patient treatment satisfaction) post intervention. Because these employees did not have time to retrieve and analyze the data, they welcomed the opportunity to have the data analyzed by the investigators during the Study phase of the PDSA cycle. Based on the results of the analysis, recommendations for program changes were made during the Act phase of the cycle.

Intervention

The EVP was developed as a 10-week (30 hours) interdisciplinary CIH approach that coached veterans with chronic pain to live fuller lives based on their individual values and what matters to them. EVP is the “What Else” management modality for the 5% of veterans with high-impact chronic pain.⁹ The EVP provided functional restoration through its components of whole health, mindfulness training, coaching calls, acceptance and commitment therapy, and mindful movement. It used the Wheel of Health with the 4 key components of me, self-care, professional care, and community.^10,11

Veterans who had a diagnosis of chronic nonmalignant pain for 3 months or more and who agreed to participate in the EVP at this facility attended 3-hour classes every Tuesday with a cohort of 8 to 12 peers and engaged in one-on-one coaching with interdisciplinary team members. During the class sessions, veterans were coached to understand and accept their pain and commit to maintaining function despite their pain. Mindful movement by the physical therapist emphasized the pivotal place of exercise in pain management. The therapist used the mantra “Motion is Lotion.”⁹ The guiding principle of the EVP was that small incremental changes can have a big impact on the individual’s whole life. Emphasis was placed on increasing self-efficacy and mindful awareness for veterans with high-impact pain by giving them “Skills before Pills.”⁹

Outcome Measures

Outcome measures included the Numerical Pain Rating Scale (NPRS), the Multidimensional Pain Inventory (MPI), the World Health Organization Quality of Life assessment (WHOQOL-BREF), the Pain Catastrophizing Scale (PCS), and the Pain Treatment Satisfaction Scale (PTSS). Cronbach alpha coefficients were calculated to assess internal consistency reliability of these measures in the sample of veterans who completed the EVP.

NPRS. The NPRS is ubiquitous as a screening tool in many health care environments and its use is mandated by the VA health care system.¹² The choice of the NPRS as the tool for pain screening in the VA health care system was based on a large body of research that supports the reliability and validity of the NPRS as a single index of pain intensity or severity. Studies suggest that the NPRS is valid for use in the assessment of acute, cancer, or chronic nonmalignant pain and in varied clinical settings.¹³ The NPRS has 4 items, each on a scale of 0 to 10. For the purpose of this project, only 3 items were used. The 3 items assessed the worst pain, usual pain, and the current pain (right now). The higher the score, the higher the pain intensity. Cronbach alpha coefficients on the NPRS obtained from the current sample of veterans were 0.85 on both pre- and postintervention assessments.

MPI. The MPI is an easily accessible, reliable, and valid self-report questionnaire that measures the impact of pain on an individual’s life, quality of social support, and general activity.¹⁴ This instrument is a short version of the West Haven-Yale MPI.¹⁵ The MPI contains 9 items rated on a scale from 0 to 6. The higher the score, the greater pain interference a person is experiencing. The MPI produces reliable, valid information for diagnostic purposes and for therapy outcome studies.¹⁶ The MPI had a Cronbach alpha of 0.90 on pre-intervention and 0.92 on postintervention assessments in the current sample.

WHOQOL-BREF. The WHOQOL-BREF is a measure of quality of life and is an abbreviated version of the WHOQOL-100. Quality of life is defined by the World Health Organization¹⁷ “as an individuals’ perception of their position in life in the context of the culture and value systems in which they live and in relation to their goals, expectations, standards and concerns.” The WHOQOL-BREF contains 26 items. The first 2 items were examined separately; the first item asks individuals to rate their overall quality of life and the second asks individuals how satisfied they are with their health. The remaining 24 items were used to calculate the following 4 domain scores: physical health, psychological health, social relationship, and environment.¹⁸ Each item is measured on a scale of 1 to 5. Higher scores denote higher or better quality of life. Domain scores have demonstrated good reliability and validity.^19-21 Cronbach alpha coefficients for the domain subscales ranged from 0.63 to 0.84 in the current sample, with the lowest alphas for the 3-item Social Relationships Domain.

PCS. The PCS is a widely used measure of catastrophic thinking related to pain. Catastrophizing has been conceived by Sullivan and colleagues as “an exaggerated negative mental set brought to bear during actual or anticipated painful experience.”²² The PCS provides a total score and scores for the following subscales: rumination, magnification, and helplessness.²³ It has been used in a variety of chronic pain populations and has demonstrated good reliability and validity in clinical as well as nonclinical samples.^24-26 The PCS has 13 items rated on a scale of 0 to 4. Higher scores mean greater negative pain cognition (catastrophizing). In the current sample, the PCS total scale had a Cronbach alpha coefficient of 0.95 and 0.94 on the 2 assessments. The coefficients for the subscales ranged from 0.81 to 0.90.

PTSS. The PTSS is a 5-item tool that measures patient satisfaction with pain treatment. It includes items that address overall satisfaction, staff warmth, staff skill level, ease of scheduling appointments, and recommendation of the program to other veterans. It was derived from the post-treatment version of The Pain Outcome Questionnaire-VA and has demonstrated reliability and validity.²⁷ The questions are scaled from 0 to 10. High scores on the PTSS denote high patient satisfaction with the EVP. The Cronbach alpha coefficient on the PTSS obtained from the current sample was 0.80.

Data Gathering and Analysis

Prior to starting the Study phase, Washburn University’s Institutional Review Board (IRB) and the VA IRB approved the project. The VA IRB, through its affiliate, gave a Not Human Research Determination and granted a waiver of informed consent and the Health Insurance Portability and Accountability Act authorization. The VA facility’s Research and Development department also approved the quality improvement project.

Once these approvals were obtained, the Study phase began with the abstraction of retrospective data obtained from veterans who participated in the VA health care facility’s EVP between August 2017 and August 2019. Most of the measurement tools changed in August 2019, and for this reason data abstraction was limited to the time period August 2017 to August 2019. The first author (JUU) abstracted data for both program completers and noncompleters. The second (MJ) and third (SW) authors analyzed the data in SPSS 24 and calculated effect sizes.

Veterans who completed the program were compared to veterans who did not complete the program on age, gender, and baseline measures. The investigators used independent samples t-tests to compare completers and noncompleters on age, pain intensity, pain interference, quality of life, and pain catastrophizing. They used the chi-square test of independence to analyze the association between gender and program completion.

Data were included in the pre- and postintervention analysis if the veteran completed the NPRS, MPI, WHOQOL-BREF, and PCS pre and post intervention. This became an important eligibility requirement as some of the tools/measures were changed towards the end of the review period in 2019. Pre- and postintervention data on pain intensity, pain interference, quality of life, pain catastrophizing, and patient satisfaction were compared using paired samples t-test at .004 level of significance based on the Bonferroni correction.²⁸ Data on patient satisfaction with pain treatment were collected at program completion (week 8 or 10) and were analyzed using descriptive statistics.

Effect sizes (Cohen’s d) were calculated to determine the substantive significance or magnitude of the mean differences in scores. Effect sizes (expressed as absolute values of Cohen’s d) were calculated as the mean difference divided by the standard deviation. Values of 0.2 were considered a small effect size, 0.5 a medium effect size, and 0.8 a large effect size.²⁹

Data were abstracted for 115 veterans who started the EVP. Of these, 48 left the program, leaving 67 veterans (58%) who completed the program. Completers and noncompleters were similar in age, gender, and baseline measures (Table 1). Fifty-three (79%) completers and 35 (73%) noncompleters were male. A chi-square test of independence showed no significant association between gender and program completion (χ^2₁ [N = 115] = .595, P = .440).

Comparison of pre-and postintervention mean scale scores resulted in statistically significant differences for all comparisons (Table 2). These comparisons yielded improvements in the desired direction. For example, the scores on the NPRS, the MPI, and the PCS (along with its subscales) decreased, revealing reductions in pain severity, the impact of pain on the veterans’ lives, and pain catastrophizing. The 2 individual item scores on the WHOQOL-BREF increased, indicating improvements in perceived quality of life and satisfaction with health. The domain scores on the WHOQOL-BREF increased, revealing improvements in pain-related quality of life. The moderate to large effect sizes indicated clinically significant improvements for veterans with chronic high-impact pain who completed the EVP.

Analysis of data obtained using the PTSS yielded high mean scores for items that focused on patient satisfaction with treatment (Table 3). Scaled statistics yielded a mean (SD) of 46.95 (4.40). These results denoted overall patient satisfaction with the EVP.

Discussion

The purpose of this quality improvement project was to abstract and analyze previously collected data from veterans with high-impact chronic pain who attended the EVP. Comparison of pre-intervention and postintervention data obtained from 67 veterans who completed the program revealed improvements in pain intensity, pain interference, negative cognition (catastrophizing), and quality of life. The differences were statistically significant and clinically meaningful, with medium and large effect sizes. In addition, veterans reported high satisfaction with the EVP.

The EVP includes CIH approaches that have demonstrated effectiveness among veterans and other populations with chronic pain. A wealth of studies, for example, support the effectiveness of CIH approaches among veterans.^30-34 Other studies focus on specific CIH approaches that are components of the EVP. Evidence supports, for example, the efficacy of mindfulness-based stress reduction,^35-39 acceptance and commitment therapy,^40-43 brief peer support intervention,⁴⁴ and interdisciplinary biopsychosocial rehabilitation.^45,46

While empirical evidence supports components of the EVP, only one study focused on the outcomes of the Atlanta VA EVP among veterans with chronic pain. Results of a qualitative study conducted by Penney and Haro⁴⁷ described the experience of veterans with the EVP. Those veterans reported adopting new self-care or lifestyle practices for pain management and health, accepting pain, being better able to adjust and set boundaries, feeling more in control, participating in life, and changing their medication use.

The mean baseline scores from the current sample were similar to samples of patients with chronic pain in other studies (NPRS,⁴⁸ MPI,⁴⁸ and PCS^48-51). After converting scores on the WHOQOL-BREF from those that ranged from 4 to 20 to those that ranged from 0 to 100,¹⁸ the scores from the current sample were similar to those of other studies of patients with chronic pain.^48,52,53Several strengths of the project should be noted. Data were collected using well established measurement tools that had previously demonstrated reliability and validity. All the tools used in data collection demonstrated good internal consistency reliabilities in the current sample of veterans. Weaknesses of the project include the use of a convenience sample of veterans and small sample size. Data were not available on the number of veterans who were offered participation or on how many veterans declined enrollment. The sample of veterans who chose to participate in the EVP may or may not have been representative of the population of veterans with high-impact chronic pain. As a pre- and postintervention design with no comparison group, the results are subject to multiple threats to internal validity, including the Hawthorne effect, maturation in the form of healing, and attrition. Reasons for leaving the program had not been recorded, so the investigators had no way of knowing factors that may have contributed to attrition. Also, data on when veterans left the program were unavailable. Research is needed with a control group to reduce the effect of confounding variables on the outcome measures. This project used data collected at a single VA facility, which limits its generalizability.

While completers and noncompleters of the EVP were similar on age, gender, and baseline measures, there may have been unidentified characteristics that influenced program completion. The investigators noticed the presence of more missing data among noncompleters compared to completers on the pre-intervention PCS; thus, noncompleters may have scored lower than completers on this instrument simply because there were more individual items that were unanswered/missing among this group of noncompleters.

Data were analyzed using a limited number of outcome measures that had previously been collected. Other outcome measures might include whether EVP participants reduced their use of medications, clinical resources, and personnel. Future projects, for example, could determine whether the EVP is effective in reducing opioid analgesic medication use and decreasing primary care and emergency department visits. Cost-benefit analyses could be completed to determine whether EVP is associated with financial savings.

Because no follow-up assessments were made to determine whether improvements were maintained over time, the project focus was limited to an evaluation of the short-term changes in the outcome measures. Future projects could include a follow-up assessment of the veterans 1- or 2-years post completion of the EVP.

Data for the project were collected prior to the COVID-19 pandemic, when the EVP was implemented through face-to-face meetings with participants and their peers. It is not clear how changes to the delivery of the program (such as offering it through telehealth) might impact veterans’ satisfaction with the program, willingness to complete it, and other variables of interest.

The results of this project were made available to stakeholders with recommendations for program expansion both at the current location and at other VA facilities, including the recommendation to hire additional personnel that would implement the program. As the VA network of facilities expand the EVP program and adapt it for telehealth delivery, the investigators recommended a similar analysis of data be performed following telehealth delivery. If delivery through telehealth is shown to improve outcome measures, the EVP could provide pain management treatment options for patients challenged by transportation barriers, including rural veterans.

Conclusion

This quality improvement project provided evidence of improvement in measures of pain severity, pain interference, negative cognition (catastrophizing), quality of life, and patient treatment satisfaction among veterans with chronic high-impact pain. Findings have been well received by the northeastern VA as well as the Veterans Integrated Systems Network 5. The results of the analyses were used to inform decisions regarding the future of the program.

Disclaimer: This material is the result of work supported with resources and the use of facilities at the VA Maryland Health Care System, Baltimore, Maryland. The views expressed are those of the authors and do not necessarily represent the views of the Department of Veterans Affairs or the United States Government.

Acknowledgments: The authors thank Dr. Arianna Perra, the recent past coordinator of the Empower Veterans Program (EVP), who provided initial insights and support that motivated the decision to evaluate the program. We also thank the veterans and VA EVP clinicians who contributed data for the evaluation, and Dr. Michael Saenger (Director, TelePain-EVP: EVP) and Dr. Robert Lavin for their ongoing support, care, and concern for veteran patients. We also thank Dr. Beverly Bradley and the neurology service administrative team for their guidance in the process of obtaining necessary VA approvals for this project.

Corresponding author: Jessica U. Uche, DNP, CRNP-Family; [email protected]

doi:10.12788/jcom.0089

From Neurology/Chronic Pain Management Services, Department of Veterans Affairs (VA) Maryland Health Care System, Baltimore VA Medical Center, Baltimore, MD (Dr. Uche), and School of Nursing, Washburn University, Topeka, KS (Drs. Jamison and Waugh).

Abstract

Objective: The purpose of this quality improvement project was to abstract and analyze previously collected data from veterans with high-impact chronic pain who attended the Empower Veterans Program (EVP) offered by a Veterans Administration facility in the northeastern United States.

Methods: This quality improvement project used data collected from veterans with chronic pain who completed the veterans health care facility’s EVP between August 2017 and August 2019. Pre- and post-intervention data on pain intensity, pain interference, quality of life, and pain catastrophizing were compared using paired t-tests.

Results: Although data were abstracted from 115 patients, the final sample included 67 patients who completed both pre-and postintervention questionnaires. Baseline measures of completers and noncompleters were similar. Comparison of pre and post mean scores on completers showed statistically significant findings (P = .004) based on the Bonferroni correction. The medium and large effect sizes (Cohen’s d) indicated clinically significant improvements for veterans who completed the program. Veterans reported high levels of satisfaction with the program.

Conclusion: Veterans with chronic high-impact noncancer pain who completed the EVP had reduced pain intensity, pain interference, pain catastrophizing as well as improved quality of life and satisfaction with their health.

Keywords: musculoskeletal pain, Veterans Affairs, complementary and integrative health, acceptance and commitment therapy, mind-body therapies, whole health, multidisciplinary pain management.

More than 100 million American adults suffer from chronic pain; costs associated with managing chronic pain are approximately $635 billion each year.¹ Chronic pain is prevalent among military veterans, affecting one-third of the 9 million veterans who receive care from Veterans Health Administration (VHA) facilities.² The biopsychosocial impact of chronic pain on the general population, and specifically on veterans, has been compounded by the opioid crisis. The effects of chronic pain and the opioid crisis have fueled interest in the use of complementary and integrative health (CIH) modalities in the management of chronic noncancer pain. Providers are increasingly developing treatment programs that incorporate CIH in their management of chronic noncancer pain.

One such program is the Empower Veterans Program (EVP). Originally developed at the Atlanta Veterans Affairs Health Care System, the EVP is a CIH modality based on the biopsychosocial model of pain developed by psychiatrist George Engel in 1977.³ The biopsychosocial model of pain recognizes that pain is a complex, multidimensional, biopsychosocial experience. Under this model, the mind and body work in unison as interconnected entities. Because the model acknowledges biological, psychological, and social components of pain and illness,⁴ treatment focuses on all aspects of a person’s health, life, and relationships.

The EVP fits into the VHA Pain Management Stepped Care Model and is an adjunctive complement for that model.^5-7 The EVP complements care at the first step, where patient/family provide self-care and where care is provided by patient-aligned primary care teams, at the second step, which includes secondary consultation with multidisciplinary pain medicine specialty teams and other specialists, and at the third step, with the addition of tertiary interdisciplinary pain centers.

The VA Maryland Health Care System (VAMHCS) implemented the EVP as part of a quality improvement project for the management of chronic pain. The objectives of the program were to reduce pain intensity, pain catastrophizing, and pain interference, as well as improve functionality and quality of life among veterans with chronic high-impact noncancer pain. More than 2 years after the program was implemented, collected data had not been analyzed. The purpose of this quality improvement project was to abstract and analyze the previously collected data from veterans with high-impact chronic pain who attended an EVP offered by the VAMHCS. The results of the data analysis were used to inform decisions regarding the future of the program.

Methods

This quality improvement project used the Plan-Do-Study-Act (PDSA) process.⁸ The first 2 phases of the PDSA cycle (Plan and Do) were completed by a team of VA employees from the VAMHCS, who donated their time to establish and implement the program at the project site. This team consisted of psychologists, a physical therapist, a social worker, and a chaplain, and included support from medical administrative staff. This team planned and implemented the EVP at the VA facility based on the model developed at the Atlanta VA Health Care System. During the “Do” phase, the team collected data on pain intensity, pain interference, quality of life, and pain negative cognition (catastrophizing) before the intervention and post intervention. They also collected data on program outcome (patient treatment satisfaction) post intervention. Because these employees did not have time to retrieve and analyze the data, they welcomed the opportunity to have the data analyzed by the investigators during the Study phase of the PDSA cycle. Based on the results of the analysis, recommendations for program changes were made during the Act phase of the cycle.

Intervention

The EVP was developed as a 10-week (30 hours) interdisciplinary CIH approach that coached veterans with chronic pain to live fuller lives based on their individual values and what matters to them. EVP is the “What Else” management modality for the 5% of veterans with high-impact chronic pain.⁹ The EVP provided functional restoration through its components of whole health, mindfulness training, coaching calls, acceptance and commitment therapy, and mindful movement. It used the Wheel of Health with the 4 key components of me, self-care, professional care, and community.^10,11

Veterans who had a diagnosis of chronic nonmalignant pain for 3 months or more and who agreed to participate in the EVP at this facility attended 3-hour classes every Tuesday with a cohort of 8 to 12 peers and engaged in one-on-one coaching with interdisciplinary team members. During the class sessions, veterans were coached to understand and accept their pain and commit to maintaining function despite their pain. Mindful movement by the physical therapist emphasized the pivotal place of exercise in pain management. The therapist used the mantra “Motion is Lotion.”⁹ The guiding principle of the EVP was that small incremental changes can have a big impact on the individual’s whole life. Emphasis was placed on increasing self-efficacy and mindful awareness for veterans with high-impact pain by giving them “Skills before Pills.”⁹

Outcome Measures

Outcome measures included the Numerical Pain Rating Scale (NPRS), the Multidimensional Pain Inventory (MPI), the World Health Organization Quality of Life assessment (WHOQOL-BREF), the Pain Catastrophizing Scale (PCS), and the Pain Treatment Satisfaction Scale (PTSS). Cronbach alpha coefficients were calculated to assess internal consistency reliability of these measures in the sample of veterans who completed the EVP.

NPRS. The NPRS is ubiquitous as a screening tool in many health care environments and its use is mandated by the VA health care system.¹² The choice of the NPRS as the tool for pain screening in the VA health care system was based on a large body of research that supports the reliability and validity of the NPRS as a single index of pain intensity or severity. Studies suggest that the NPRS is valid for use in the assessment of acute, cancer, or chronic nonmalignant pain and in varied clinical settings.¹³ The NPRS has 4 items, each on a scale of 0 to 10. For the purpose of this project, only 3 items were used. The 3 items assessed the worst pain, usual pain, and the current pain (right now). The higher the score, the higher the pain intensity. Cronbach alpha coefficients on the NPRS obtained from the current sample of veterans were 0.85 on both pre- and postintervention assessments.

MPI. The MPI is an easily accessible, reliable, and valid self-report questionnaire that measures the impact of pain on an individual’s life, quality of social support, and general activity.¹⁴ This instrument is a short version of the West Haven-Yale MPI.¹⁵ The MPI contains 9 items rated on a scale from 0 to 6. The higher the score, the greater pain interference a person is experiencing. The MPI produces reliable, valid information for diagnostic purposes and for therapy outcome studies.¹⁶ The MPI had a Cronbach alpha of 0.90 on pre-intervention and 0.92 on postintervention assessments in the current sample.

WHOQOL-BREF. The WHOQOL-BREF is a measure of quality of life and is an abbreviated version of the WHOQOL-100. Quality of life is defined by the World Health Organization¹⁷ “as an individuals’ perception of their position in life in the context of the culture and value systems in which they live and in relation to their goals, expectations, standards and concerns.” The WHOQOL-BREF contains 26 items. The first 2 items were examined separately; the first item asks individuals to rate their overall quality of life and the second asks individuals how satisfied they are with their health. The remaining 24 items were used to calculate the following 4 domain scores: physical health, psychological health, social relationship, and environment.¹⁸ Each item is measured on a scale of 1 to 5. Higher scores denote higher or better quality of life. Domain scores have demonstrated good reliability and validity.^19-21 Cronbach alpha coefficients for the domain subscales ranged from 0.63 to 0.84 in the current sample, with the lowest alphas for the 3-item Social Relationships Domain.

PCS. The PCS is a widely used measure of catastrophic thinking related to pain. Catastrophizing has been conceived by Sullivan and colleagues as “an exaggerated negative mental set brought to bear during actual or anticipated painful experience.”²² The PCS provides a total score and scores for the following subscales: rumination, magnification, and helplessness.²³ It has been used in a variety of chronic pain populations and has demonstrated good reliability and validity in clinical as well as nonclinical samples.^24-26 The PCS has 13 items rated on a scale of 0 to 4. Higher scores mean greater negative pain cognition (catastrophizing). In the current sample, the PCS total scale had a Cronbach alpha coefficient of 0.95 and 0.94 on the 2 assessments. The coefficients for the subscales ranged from 0.81 to 0.90.

PTSS. The PTSS is a 5-item tool that measures patient satisfaction with pain treatment. It includes items that address overall satisfaction, staff warmth, staff skill level, ease of scheduling appointments, and recommendation of the program to other veterans. It was derived from the post-treatment version of The Pain Outcome Questionnaire-VA and has demonstrated reliability and validity.²⁷ The questions are scaled from 0 to 10. High scores on the PTSS denote high patient satisfaction with the EVP. The Cronbach alpha coefficient on the PTSS obtained from the current sample was 0.80.

Data Gathering and Analysis

Prior to starting the Study phase, Washburn University’s Institutional Review Board (IRB) and the VA IRB approved the project. The VA IRB, through its affiliate, gave a Not Human Research Determination and granted a waiver of informed consent and the Health Insurance Portability and Accountability Act authorization. The VA facility’s Research and Development department also approved the quality improvement project.

Once these approvals were obtained, the Study phase began with the abstraction of retrospective data obtained from veterans who participated in the VA health care facility’s EVP between August 2017 and August 2019. Most of the measurement tools changed in August 2019, and for this reason data abstraction was limited to the time period August 2017 to August 2019. The first author (JUU) abstracted data for both program completers and noncompleters. The second (MJ) and third (SW) authors analyzed the data in SPSS 24 and calculated effect sizes.

Veterans who completed the program were compared to veterans who did not complete the program on age, gender, and baseline measures. The investigators used independent samples t-tests to compare completers and noncompleters on age, pain intensity, pain interference, quality of life, and pain catastrophizing. They used the chi-square test of independence to analyze the association between gender and program completion.

Data were included in the pre- and postintervention analysis if the veteran completed the NPRS, MPI, WHOQOL-BREF, and PCS pre and post intervention. This became an important eligibility requirement as some of the tools/measures were changed towards the end of the review period in 2019. Pre- and postintervention data on pain intensity, pain interference, quality of life, pain catastrophizing, and patient satisfaction were compared using paired samples t-test at .004 level of significance based on the Bonferroni correction.²⁸ Data on patient satisfaction with pain treatment were collected at program completion (week 8 or 10) and were analyzed using descriptive statistics.

Effect sizes (Cohen’s d) were calculated to determine the substantive significance or magnitude of the mean differences in scores. Effect sizes (expressed as absolute values of Cohen’s d) were calculated as the mean difference divided by the standard deviation. Values of 0.2 were considered a small effect size, 0.5 a medium effect size, and 0.8 a large effect size.²⁹

Data were abstracted for 115 veterans who started the EVP. Of these, 48 left the program, leaving 67 veterans (58%) who completed the program. Completers and noncompleters were similar in age, gender, and baseline measures (Table 1). Fifty-three (79%) completers and 35 (73%) noncompleters were male. A chi-square test of independence showed no significant association between gender and program completion (χ^2₁ [N = 115] = .595, P = .440).

Comparison of pre-and postintervention mean scale scores resulted in statistically significant differences for all comparisons (Table 2). These comparisons yielded improvements in the desired direction. For example, the scores on the NPRS, the MPI, and the PCS (along with its subscales) decreased, revealing reductions in pain severity, the impact of pain on the veterans’ lives, and pain catastrophizing. The 2 individual item scores on the WHOQOL-BREF increased, indicating improvements in perceived quality of life and satisfaction with health. The domain scores on the WHOQOL-BREF increased, revealing improvements in pain-related quality of life. The moderate to large effect sizes indicated clinically significant improvements for veterans with chronic high-impact pain who completed the EVP.

Analysis of data obtained using the PTSS yielded high mean scores for items that focused on patient satisfaction with treatment (Table 3). Scaled statistics yielded a mean (SD) of 46.95 (4.40). These results denoted overall patient satisfaction with the EVP.

Discussion

The purpose of this quality improvement project was to abstract and analyze previously collected data from veterans with high-impact chronic pain who attended the EVP. Comparison of pre-intervention and postintervention data obtained from 67 veterans who completed the program revealed improvements in pain intensity, pain interference, negative cognition (catastrophizing), and quality of life. The differences were statistically significant and clinically meaningful, with medium and large effect sizes. In addition, veterans reported high satisfaction with the EVP.

The EVP includes CIH approaches that have demonstrated effectiveness among veterans and other populations with chronic pain. A wealth of studies, for example, support the effectiveness of CIH approaches among veterans.^30-34 Other studies focus on specific CIH approaches that are components of the EVP. Evidence supports, for example, the efficacy of mindfulness-based stress reduction,^35-39 acceptance and commitment therapy,^40-43 brief peer support intervention,⁴⁴ and interdisciplinary biopsychosocial rehabilitation.^45,46

While empirical evidence supports components of the EVP, only one study focused on the outcomes of the Atlanta VA EVP among veterans with chronic pain. Results of a qualitative study conducted by Penney and Haro⁴⁷ described the experience of veterans with the EVP. Those veterans reported adopting new self-care or lifestyle practices for pain management and health, accepting pain, being better able to adjust and set boundaries, feeling more in control, participating in life, and changing their medication use.

The mean baseline scores from the current sample were similar to samples of patients with chronic pain in other studies (NPRS,⁴⁸ MPI,⁴⁸ and PCS^48-51). After converting scores on the WHOQOL-BREF from those that ranged from 4 to 20 to those that ranged from 0 to 100,¹⁸ the scores from the current sample were similar to those of other studies of patients with chronic pain.^48,52,53Several strengths of the project should be noted. Data were collected using well established measurement tools that had previously demonstrated reliability and validity. All the tools used in data collection demonstrated good internal consistency reliabilities in the current sample of veterans. Weaknesses of the project include the use of a convenience sample of veterans and small sample size. Data were not available on the number of veterans who were offered participation or on how many veterans declined enrollment. The sample of veterans who chose to participate in the EVP may or may not have been representative of the population of veterans with high-impact chronic pain. As a pre- and postintervention design with no comparison group, the results are subject to multiple threats to internal validity, including the Hawthorne effect, maturation in the form of healing, and attrition. Reasons for leaving the program had not been recorded, so the investigators had no way of knowing factors that may have contributed to attrition. Also, data on when veterans left the program were unavailable. Research is needed with a control group to reduce the effect of confounding variables on the outcome measures. This project used data collected at a single VA facility, which limits its generalizability.

While completers and noncompleters of the EVP were similar on age, gender, and baseline measures, there may have been unidentified characteristics that influenced program completion. The investigators noticed the presence of more missing data among noncompleters compared to completers on the pre-intervention PCS; thus, noncompleters may have scored lower than completers on this instrument simply because there were more individual items that were unanswered/missing among this group of noncompleters.

Data were analyzed using a limited number of outcome measures that had previously been collected. Other outcome measures might include whether EVP participants reduced their use of medications, clinical resources, and personnel. Future projects, for example, could determine whether the EVP is effective in reducing opioid analgesic medication use and decreasing primary care and emergency department visits. Cost-benefit analyses could be completed to determine whether EVP is associated with financial savings.

Because no follow-up assessments were made to determine whether improvements were maintained over time, the project focus was limited to an evaluation of the short-term changes in the outcome measures. Future projects could include a follow-up assessment of the veterans 1- or 2-years post completion of the EVP.

Data for the project were collected prior to the COVID-19 pandemic, when the EVP was implemented through face-to-face meetings with participants and their peers. It is not clear how changes to the delivery of the program (such as offering it through telehealth) might impact veterans’ satisfaction with the program, willingness to complete it, and other variables of interest.

The results of this project were made available to stakeholders with recommendations for program expansion both at the current location and at other VA facilities, including the recommendation to hire additional personnel that would implement the program. As the VA network of facilities expand the EVP program and adapt it for telehealth delivery, the investigators recommended a similar analysis of data be performed following telehealth delivery. If delivery through telehealth is shown to improve outcome measures, the EVP could provide pain management treatment options for patients challenged by transportation barriers, including rural veterans.

Conclusion

This quality improvement project provided evidence of improvement in measures of pain severity, pain interference, negative cognition (catastrophizing), quality of life, and patient treatment satisfaction among veterans with chronic high-impact pain. Findings have been well received by the northeastern VA as well as the Veterans Integrated Systems Network 5. The results of the analyses were used to inform decisions regarding the future of the program.

Disclaimer: This material is the result of work supported with resources and the use of facilities at the VA Maryland Health Care System, Baltimore, Maryland. The views expressed are those of the authors and do not necessarily represent the views of the Department of Veterans Affairs or the United States Government.

Acknowledgments: The authors thank Dr. Arianna Perra, the recent past coordinator of the Empower Veterans Program (EVP), who provided initial insights and support that motivated the decision to evaluate the program. We also thank the veterans and VA EVP clinicians who contributed data for the evaluation, and Dr. Michael Saenger (Director, TelePain-EVP: EVP) and Dr. Robert Lavin for their ongoing support, care, and concern for veteran patients. We also thank Dr. Beverly Bradley and the neurology service administrative team for their guidance in the process of obtaining necessary VA approvals for this project.

Corresponding author: Jessica U. Uche, DNP, CRNP-Family; [email protected]

doi:10.12788/jcom.0089

From Neurology/Chronic Pain Management Services, Department of Veterans Affairs (VA) Maryland Health Care System, Baltimore VA Medical Center, Baltimore, MD (Dr. Uche), and School of Nursing, Washburn University, Topeka, KS (Drs. Jamison and Waugh).

Abstract

Objective: The purpose of this quality improvement project was to abstract and analyze previously collected data from veterans with high-impact chronic pain who attended the Empower Veterans Program (EVP) offered by a Veterans Administration facility in the northeastern United States.

Methods: This quality improvement project used data collected from veterans with chronic pain who completed the veterans health care facility’s EVP between August 2017 and August 2019. Pre- and post-intervention data on pain intensity, pain interference, quality of life, and pain catastrophizing were compared using paired t-tests.

Results: Although data were abstracted from 115 patients, the final sample included 67 patients who completed both pre-and postintervention questionnaires. Baseline measures of completers and noncompleters were similar. Comparison of pre and post mean scores on completers showed statistically significant findings (P = .004) based on the Bonferroni correction. The medium and large effect sizes (Cohen’s d) indicated clinically significant improvements for veterans who completed the program. Veterans reported high levels of satisfaction with the program.

Conclusion: Veterans with chronic high-impact noncancer pain who completed the EVP had reduced pain intensity, pain interference, pain catastrophizing as well as improved quality of life and satisfaction with their health.

Keywords: musculoskeletal pain, Veterans Affairs, complementary and integrative health, acceptance and commitment therapy, mind-body therapies, whole health, multidisciplinary pain management.

More than 100 million American adults suffer from chronic pain; costs associated with managing chronic pain are approximately $635 billion each year.¹ Chronic pain is prevalent among military veterans, affecting one-third of the 9 million veterans who receive care from Veterans Health Administration (VHA) facilities.² The biopsychosocial impact of chronic pain on the general population, and specifically on veterans, has been compounded by the opioid crisis. The effects of chronic pain and the opioid crisis have fueled interest in the use of complementary and integrative health (CIH) modalities in the management of chronic noncancer pain. Providers are increasingly developing treatment programs that incorporate CIH in their management of chronic noncancer pain.

One such program is the Empower Veterans Program (EVP). Originally developed at the Atlanta Veterans Affairs Health Care System, the EVP is a CIH modality based on the biopsychosocial model of pain developed by psychiatrist George Engel in 1977.³ The biopsychosocial model of pain recognizes that pain is a complex, multidimensional, biopsychosocial experience. Under this model, the mind and body work in unison as interconnected entities. Because the model acknowledges biological, psychological, and social components of pain and illness,⁴ treatment focuses on all aspects of a person’s health, life, and relationships.

The EVP fits into the VHA Pain Management Stepped Care Model and is an adjunctive complement for that model.^5-7 The EVP complements care at the first step, where patient/family provide self-care and where care is provided by patient-aligned primary care teams, at the second step, which includes secondary consultation with multidisciplinary pain medicine specialty teams and other specialists, and at the third step, with the addition of tertiary interdisciplinary pain centers.

The VA Maryland Health Care System (VAMHCS) implemented the EVP as part of a quality improvement project for the management of chronic pain. The objectives of the program were to reduce pain intensity, pain catastrophizing, and pain interference, as well as improve functionality and quality of life among veterans with chronic high-impact noncancer pain. More than 2 years after the program was implemented, collected data had not been analyzed. The purpose of this quality improvement project was to abstract and analyze the previously collected data from veterans with high-impact chronic pain who attended an EVP offered by the VAMHCS. The results of the data analysis were used to inform decisions regarding the future of the program.

Methods

This quality improvement project used the Plan-Do-Study-Act (PDSA) process.⁸ The first 2 phases of the PDSA cycle (Plan and Do) were completed by a team of VA employees from the VAMHCS, who donated their time to establish and implement the program at the project site. This team consisted of psychologists, a physical therapist, a social worker, and a chaplain, and included support from medical administrative staff. This team planned and implemented the EVP at the VA facility based on the model developed at the Atlanta VA Health Care System. During the “Do” phase, the team collected data on pain intensity, pain interference, quality of life, and pain negative cognition (catastrophizing) before the intervention and post intervention. They also collected data on program outcome (patient treatment satisfaction) post intervention. Because these employees did not have time to retrieve and analyze the data, they welcomed the opportunity to have the data analyzed by the investigators during the Study phase of the PDSA cycle. Based on the results of the analysis, recommendations for program changes were made during the Act phase of the cycle.

Intervention

The EVP was developed as a 10-week (30 hours) interdisciplinary CIH approach that coached veterans with chronic pain to live fuller lives based on their individual values and what matters to them. EVP is the “What Else” management modality for the 5% of veterans with high-impact chronic pain.⁹ The EVP provided functional restoration through its components of whole health, mindfulness training, coaching calls, acceptance and commitment therapy, and mindful movement. It used the Wheel of Health with the 4 key components of me, self-care, professional care, and community.^10,11

Veterans who had a diagnosis of chronic nonmalignant pain for 3 months or more and who agreed to participate in the EVP at this facility attended 3-hour classes every Tuesday with a cohort of 8 to 12 peers and engaged in one-on-one coaching with interdisciplinary team members. During the class sessions, veterans were coached to understand and accept their pain and commit to maintaining function despite their pain. Mindful movement by the physical therapist emphasized the pivotal place of exercise in pain management. The therapist used the mantra “Motion is Lotion.”⁹ The guiding principle of the EVP was that small incremental changes can have a big impact on the individual’s whole life. Emphasis was placed on increasing self-efficacy and mindful awareness for veterans with high-impact pain by giving them “Skills before Pills.”⁹

Outcome Measures

Outcome measures included the Numerical Pain Rating Scale (NPRS), the Multidimensional Pain Inventory (MPI), the World Health Organization Quality of Life assessment (WHOQOL-BREF), the Pain Catastrophizing Scale (PCS), and the Pain Treatment Satisfaction Scale (PTSS). Cronbach alpha coefficients were calculated to assess internal consistency reliability of these measures in the sample of veterans who completed the EVP.

NPRS. The NPRS is ubiquitous as a screening tool in many health care environments and its use is mandated by the VA health care system.¹² The choice of the NPRS as the tool for pain screening in the VA health care system was based on a large body of research that supports the reliability and validity of the NPRS as a single index of pain intensity or severity. Studies suggest that the NPRS is valid for use in the assessment of acute, cancer, or chronic nonmalignant pain and in varied clinical settings.¹³ The NPRS has 4 items, each on a scale of 0 to 10. For the purpose of this project, only 3 items were used. The 3 items assessed the worst pain, usual pain, and the current pain (right now). The higher the score, the higher the pain intensity. Cronbach alpha coefficients on the NPRS obtained from the current sample of veterans were 0.85 on both pre- and postintervention assessments.

MPI. The MPI is an easily accessible, reliable, and valid self-report questionnaire that measures the impact of pain on an individual’s life, quality of social support, and general activity.¹⁴ This instrument is a short version of the West Haven-Yale MPI.¹⁵ The MPI contains 9 items rated on a scale from 0 to 6. The higher the score, the greater pain interference a person is experiencing. The MPI produces reliable, valid information for diagnostic purposes and for therapy outcome studies.¹⁶ The MPI had a Cronbach alpha of 0.90 on pre-intervention and 0.92 on postintervention assessments in the current sample.

WHOQOL-BREF. The WHOQOL-BREF is a measure of quality of life and is an abbreviated version of the WHOQOL-100. Quality of life is defined by the World Health Organization¹⁷ “as an individuals’ perception of their position in life in the context of the culture and value systems in which they live and in relation to their goals, expectations, standards and concerns.” The WHOQOL-BREF contains 26 items. The first 2 items were examined separately; the first item asks individuals to rate their overall quality of life and the second asks individuals how satisfied they are with their health. The remaining 24 items were used to calculate the following 4 domain scores: physical health, psychological health, social relationship, and environment.¹⁸ Each item is measured on a scale of 1 to 5. Higher scores denote higher or better quality of life. Domain scores have demonstrated good reliability and validity.^19-21 Cronbach alpha coefficients for the domain subscales ranged from 0.63 to 0.84 in the current sample, with the lowest alphas for the 3-item Social Relationships Domain.

PCS. The PCS is a widely used measure of catastrophic thinking related to pain. Catastrophizing has been conceived by Sullivan and colleagues as “an exaggerated negative mental set brought to bear during actual or anticipated painful experience.”²² The PCS provides a total score and scores for the following subscales: rumination, magnification, and helplessness.²³ It has been used in a variety of chronic pain populations and has demonstrated good reliability and validity in clinical as well as nonclinical samples.^24-26 The PCS has 13 items rated on a scale of 0 to 4. Higher scores mean greater negative pain cognition (catastrophizing). In the current sample, the PCS total scale had a Cronbach alpha coefficient of 0.95 and 0.94 on the 2 assessments. The coefficients for the subscales ranged from 0.81 to 0.90.

PTSS. The PTSS is a 5-item tool that measures patient satisfaction with pain treatment. It includes items that address overall satisfaction, staff warmth, staff skill level, ease of scheduling appointments, and recommendation of the program to other veterans. It was derived from the post-treatment version of The Pain Outcome Questionnaire-VA and has demonstrated reliability and validity.²⁷ The questions are scaled from 0 to 10. High scores on the PTSS denote high patient satisfaction with the EVP. The Cronbach alpha coefficient on the PTSS obtained from the current sample was 0.80.

Data Gathering and Analysis

Prior to starting the Study phase, Washburn University’s Institutional Review Board (IRB) and the VA IRB approved the project. The VA IRB, through its affiliate, gave a Not Human Research Determination and granted a waiver of informed consent and the Health Insurance Portability and Accountability Act authorization. The VA facility’s Research and Development department also approved the quality improvement project.

Once these approvals were obtained, the Study phase began with the abstraction of retrospective data obtained from veterans who participated in the VA health care facility’s EVP between August 2017 and August 2019. Most of the measurement tools changed in August 2019, and for this reason data abstraction was limited to the time period August 2017 to August 2019. The first author (JUU) abstracted data for both program completers and noncompleters. The second (MJ) and third (SW) authors analyzed the data in SPSS 24 and calculated effect sizes.

Veterans who completed the program were compared to veterans who did not complete the program on age, gender, and baseline measures. The investigators used independent samples t-tests to compare completers and noncompleters on age, pain intensity, pain interference, quality of life, and pain catastrophizing. They used the chi-square test of independence to analyze the association between gender and program completion.

Data were included in the pre- and postintervention analysis if the veteran completed the NPRS, MPI, WHOQOL-BREF, and PCS pre and post intervention. This became an important eligibility requirement as some of the tools/measures were changed towards the end of the review period in 2019. Pre- and postintervention data on pain intensity, pain interference, quality of life, pain catastrophizing, and patient satisfaction were compared using paired samples t-test at .004 level of significance based on the Bonferroni correction.²⁸ Data on patient satisfaction with pain treatment were collected at program completion (week 8 or 10) and were analyzed using descriptive statistics.

Effect sizes (Cohen’s d) were calculated to determine the substantive significance or magnitude of the mean differences in scores. Effect sizes (expressed as absolute values of Cohen’s d) were calculated as the mean difference divided by the standard deviation. Values of 0.2 were considered a small effect size, 0.5 a medium effect size, and 0.8 a large effect size.²⁹

Data were abstracted for 115 veterans who started the EVP. Of these, 48 left the program, leaving 67 veterans (58%) who completed the program. Completers and noncompleters were similar in age, gender, and baseline measures (Table 1). Fifty-three (79%) completers and 35 (73%) noncompleters were male. A chi-square test of independence showed no significant association between gender and program completion (χ^2₁ [N = 115] = .595, P = .440).

Comparison of pre-and postintervention mean scale scores resulted in statistically significant differences for all comparisons (Table 2). These comparisons yielded improvements in the desired direction. For example, the scores on the NPRS, the MPI, and the PCS (along with its subscales) decreased, revealing reductions in pain severity, the impact of pain on the veterans’ lives, and pain catastrophizing. The 2 individual item scores on the WHOQOL-BREF increased, indicating improvements in perceived quality of life and satisfaction with health. The domain scores on the WHOQOL-BREF increased, revealing improvements in pain-related quality of life. The moderate to large effect sizes indicated clinically significant improvements for veterans with chronic high-impact pain who completed the EVP.

Analysis of data obtained using the PTSS yielded high mean scores for items that focused on patient satisfaction with treatment (Table 3). Scaled statistics yielded a mean (SD) of 46.95 (4.40). These results denoted overall patient satisfaction with the EVP.

Discussion

The purpose of this quality improvement project was to abstract and analyze previously collected data from veterans with high-impact chronic pain who attended the EVP. Comparison of pre-intervention and postintervention data obtained from 67 veterans who completed the program revealed improvements in pain intensity, pain interference, negative cognition (catastrophizing), and quality of life. The differences were statistically significant and clinically meaningful, with medium and large effect sizes. In addition, veterans reported high satisfaction with the EVP.

The EVP includes CIH approaches that have demonstrated effectiveness among veterans and other populations with chronic pain. A wealth of studies, for example, support the effectiveness of CIH approaches among veterans.^30-34 Other studies focus on specific CIH approaches that are components of the EVP. Evidence supports, for example, the efficacy of mindfulness-based stress reduction,^35-39 acceptance and commitment therapy,^40-43 brief peer support intervention,⁴⁴ and interdisciplinary biopsychosocial rehabilitation.^45,46

While empirical evidence supports components of the EVP, only one study focused on the outcomes of the Atlanta VA EVP among veterans with chronic pain. Results of a qualitative study conducted by Penney and Haro⁴⁷ described the experience of veterans with the EVP. Those veterans reported adopting new self-care or lifestyle practices for pain management and health, accepting pain, being better able to adjust and set boundaries, feeling more in control, participating in life, and changing their medication use.

The mean baseline scores from the current sample were similar to samples of patients with chronic pain in other studies (NPRS,⁴⁸ MPI,⁴⁸ and PCS^48-51). After converting scores on the WHOQOL-BREF from those that ranged from 4 to 20 to those that ranged from 0 to 100,¹⁸ the scores from the current sample were similar to those of other studies of patients with chronic pain.^48,52,53Several strengths of the project should be noted. Data were collected using well established measurement tools that had previously demonstrated reliability and validity. All the tools used in data collection demonstrated good internal consistency reliabilities in the current sample of veterans. Weaknesses of the project include the use of a convenience sample of veterans and small sample size. Data were not available on the number of veterans who were offered participation or on how many veterans declined enrollment. The sample of veterans who chose to participate in the EVP may or may not have been representative of the population of veterans with high-impact chronic pain. As a pre- and postintervention design with no comparison group, the results are subject to multiple threats to internal validity, including the Hawthorne effect, maturation in the form of healing, and attrition. Reasons for leaving the program had not been recorded, so the investigators had no way of knowing factors that may have contributed to attrition. Also, data on when veterans left the program were unavailable. Research is needed with a control group to reduce the effect of confounding variables on the outcome measures. This project used data collected at a single VA facility, which limits its generalizability.

While completers and noncompleters of the EVP were similar on age, gender, and baseline measures, there may have been unidentified characteristics that influenced program completion. The investigators noticed the presence of more missing data among noncompleters compared to completers on the pre-intervention PCS; thus, noncompleters may have scored lower than completers on this instrument simply because there were more individual items that were unanswered/missing among this group of noncompleters.

Data were analyzed using a limited number of outcome measures that had previously been collected. Other outcome measures might include whether EVP participants reduced their use of medications, clinical resources, and personnel. Future projects, for example, could determine whether the EVP is effective in reducing opioid analgesic medication use and decreasing primary care and emergency department visits. Cost-benefit analyses could be completed to determine whether EVP is associated with financial savings.

Because no follow-up assessments were made to determine whether improvements were maintained over time, the project focus was limited to an evaluation of the short-term changes in the outcome measures. Future projects could include a follow-up assessment of the veterans 1- or 2-years post completion of the EVP.

Data for the project were collected prior to the COVID-19 pandemic, when the EVP was implemented through face-to-face meetings with participants and their peers. It is not clear how changes to the delivery of the program (such as offering it through telehealth) might impact veterans’ satisfaction with the program, willingness to complete it, and other variables of interest.

The results of this project were made available to stakeholders with recommendations for program expansion both at the current location and at other VA facilities, including the recommendation to hire additional personnel that would implement the program. As the VA network of facilities expand the EVP program and adapt it for telehealth delivery, the investigators recommended a similar analysis of data be performed following telehealth delivery. If delivery through telehealth is shown to improve outcome measures, the EVP could provide pain management treatment options for patients challenged by transportation barriers, including rural veterans.

Conclusion

This quality improvement project provided evidence of improvement in measures of pain severity, pain interference, negative cognition (catastrophizing), quality of life, and patient treatment satisfaction among veterans with chronic high-impact pain. Findings have been well received by the northeastern VA as well as the Veterans Integrated Systems Network 5. The results of the analyses were used to inform decisions regarding the future of the program.

Disclaimer: This material is the result of work supported with resources and the use of facilities at the VA Maryland Health Care System, Baltimore, Maryland. The views expressed are those of the authors and do not necessarily represent the views of the Department of Veterans Affairs or the United States Government.

Acknowledgments: The authors thank Dr. Arianna Perra, the recent past coordinator of the Empower Veterans Program (EVP), who provided initial insights and support that motivated the decision to evaluate the program. We also thank the veterans and VA EVP clinicians who contributed data for the evaluation, and Dr. Michael Saenger (Director, TelePain-EVP: EVP) and Dr. Robert Lavin for their ongoing support, care, and concern for veteran patients. We also thank Dr. Beverly Bradley and the neurology service administrative team for their guidance in the process of obtaining necessary VA approvals for this project.

Corresponding author: Jessica U. Uche, DNP, CRNP-Family; [email protected]

doi:10.12788/jcom.0089

From the Veterans Affairs Ann Arbor Healthcare System Medicine Service (Dr. Cusick), University of Michigan College of Pharmacy, Clinical Pharmacy Service, Michigan Medicine (Dr. Hanigan), Department of Internal Medicine Clinical Experience and Quality, Michigan Medicine (Linda Bashaw), Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI (Dr. Heidemann), and the Operational Excellence Department, Sparrow Health System, Lansing, MI (Matthew Johnson).

Abstract

Background: Diagnosis of heparin-induced thrombocytopenia (HIT) requires completion of an enzyme-linked immunosorbent assay (ELISA)–based heparin-platelet factor 4 (PF4) antibody test. If this test is negative, HIT is excluded. If positive, a serotonin-release assay (SRA) test is indicated. The SRA is expensive and sometimes inappropriately ordered despite negative PF4 results, leading to unnecessary treatment with argatroban while awaiting SRA results.

Objectives: The primary objectives of this project were to reduce unnecessary SRA testing and argatroban utilization in patients with suspected HIT.

Methods: The authors implemented an intervention at a tertiary care academic hospital in November 2017 targeting patients hospitalized with suspected HIT. The intervention was controlled at the level of the laboratory and prevented ordering of SRA tests in the absence of a positive PF4 test. The number of SRA tests performed and argatroban bags administered were identified retrospectively via chart review before the intervention (January 2016 to November 2017) and post intervention (December 2017 to March 2020). Associated costs were calculated based on institutional SRA testing cost as well as the average wholesale price of argatroban.

Results: SRA testing decreased from an average of 3.7 SRA results per 1000 admissions before the intervention to an average of 0.6 results per 1000 admissions post intervention. The number of 50-mL argatroban bags used per 1000 admissions decreased from 18.8 prior to the intervention to 14.3 post intervention. Total estimated cost savings per 1000 admissions was $2361.20.

Conclusion: An evidence-based testing strategy for HIT can be effectively implemented at the level of the laboratory. This approach led to reductions in SRA testing and argatroban utilization with resultant cost savings.

Keywords: HIT, argatroban, anticoagulation, serotonin-release assay.

Thrombocytopenia is a common finding in hospitalized patients.^1,2 Heparin-induced thrombocytopenia (HIT) is one of the many potential causes of thrombocytopenia in hospitalized patients and occurs when antibodies to the heparin-platelet factor 4 (PF4) complex develop after heparin exposure. This triggers a cascade of events, leading to platelet activation, platelet consumption, and thrombosis. While HIT is relatively rare, occurring in 0.3% to 0.5% of critically ill patients, many patients will be tested to rule out this potentially life-threatening cause of thrombocytopenia.³

The diagnosis of HIT utilizes a combination of both clinical suspicion and laboratory testing.⁴ The 4T score (Table) was developed to evaluate the clinical probability of HIT and involves assessing the degree and timing of thrombocytopenia, the presence or absence of thrombosis, and other potential causes of the thrombocytopenia.⁵ The 4T score is designed to be utilized to identify patients who require laboratory testing for HIT; however, it has low inter-rater agreement in patients undergoing evaluation for HIT,⁶ and, in our experience, completion of this scoring is time-consuming.

The enzyme-linked immunosorbent assay (ELISA) is a commonly used laboratory test to diagnose HIT that detects antibodies to the heparin-PF4 complex utilizing optical density (OD) units. When using an OD cutoff of 0.400, ELISA PF4 (PF4) tests have a sensitivity of 99.6%, but poor specificity at 69.3%.⁷ When the PF4 antibody test is positive with an OD ≥0.400, then a functional test is used to determine whether the antibodies detected will activate platelets. The serotonin-release assay (SRA) is a functional test that measures 14C-labeled serotonin release from donor platelets when mixed with patient serum or plasma containing HIT antibodies. In the correct clinical context, a positive ELISA PF4 antibody test along with a positive SRA is diagnostic of HIT.⁸

The process of diagnosing HIT in a timely and cost-effective manner is dependent on the clinician’s experience in diagnosing HIT as well as access to the laboratory testing necessary to confirm the diagnosis. PF4 antibody tests are time-consuming and not always available daily and/or are not available onsite. The SRA requires access to donor platelets and specialized radioactivity counting equipment, making it available only at particular centers.

The treatment of HIT is more straightforward and involves stopping all heparin products and starting a nonheparin anticoagulant. The direct thrombin inhibitor argatroban is one of the standard nonheparin anticoagulants used in patients with suspected HIT.⁴ While it is expensive, its short half-life and lack of renal clearance make it ideal for treatment of hospitalized patients with suspected HIT, many of whom need frequent procedures and/or have renal disease.

At our academic tertiary care center, we performed a retrospective analysis that showed inappropriate ordering of diagnostic HIT testing as well as unnecessary use of argatroban even when there was low suspicion for HIT based on laboratory findings. The aim of our project was to reduce unnecessary HIT testing and argatroban utilization without overburdening providers or interfering with established workflows.

Methods

Setting

The University of Michigan (UM) hospital is a 1000-bed tertiary care center in Ann Arbor, Michigan. The UM guidelines reflect evidence-based guidelines for the diagnosis and treatment of HIT.⁴ In 2016 the UM guidelines for laboratory testing included sending the PF4 antibody test first when there was clinical suspicion of HIT. The SRA was to be sent separately only when the PF4 returned positive (OD ≥ 0.400). Standard guidelines at UM also included switching patients with suspected HIT from heparin to a nonheparin anticoagulant and stopping all heparin products while awaiting the SRA results. The direct thrombin inhibitor argatroban is utilized at UM and monitored with anti-IIa levels. University of Michigan Hospital utilizes the Immucor PF4 IgG ELISA for detecting heparin-associated antibodies.⁹ In 2016, this PF4 test was performed in the UM onsite laboratory Monday through Friday. At UM the SRA is performed off site, with a turnaround time of 3 to 5 business days.

Baseline Data

We retrospectively reviewed PF4 and SRA testing as well as argatroban usage from December 2016 to May 2017. Despite the institutional guidelines, providers were sending PF4 and SRA simultaneously as soon as HIT was suspected; 62% of PF4 tests were ordered simultaneously with the SRA, but only 8% of these PF4 tests were positive with an OD ≥0.400. Of those patients with negative PF4 testing, argatroban was continued until the SRA returned negative, leading to many days of unnecessary argatroban usage. An informal survey of the anticoagulation pharmacists revealed that many recommended discontinuing argatroban when the PF4 test was negative, but providers routinely did not feel comfortable with this approach. This suggested many providers misunderstood the performance characteristics of the PF4 test.

Intervention

Our team consisted of hematology and internal medicine faculty, pharmacists, coagulation laboratory personnel, and quality improvement specialists. We designed and implemented an intervention in November 2017 focused on controlling the ordering of the SRA test. We chose to focus on this step due to the excellent sensitivity of the PF4 test with a cutoff of OD <0.400 and the significant expense of the SRA test. Under direction of the Coagulation Laboratory Director, a standard operating procedure was developed where the coagulation laboratory personnel did not send out the SRA until a positive PF4 test (OD ≥ 0.400) was reported. If the PF4 was negative, the SRA was canceled and the ordering provider received notification of the cancelled test via the electronic medical record, accompanied by education about HIT testing (Figure 1). In addition, the lab increased the availability of PF4 testing from 5 days to 7 days a week so there were no delays in tests ordered on Fridays or weekends.

Outcomes

Our primary goals were to decrease both SRA testing and argatroban use. Secondarily, we examined the cost-effectiveness of this intervention. We hypothesized that controlling the SRA testing at the laboratory level would decrease both SRA testing and argatroban use.

Data Collection

Pre- and postintervention data were collected retrospectively. Pre-intervention data were from January 2016 through November 2017, and postintervention data were from December 2017 through March 2020. The number of SRA tests performed were identified retrospectively via review of electronic ordering records. All patients who had a hospital admission after January 1, 2016, were included. These patients were filtered to include only those who had a result for an SRA test. In order to calculate cost-savings, we identified both the number of SRA tests ordered retrospectively as well as patients who had both an SRA resulted and had been administered argatroban. Cost-savings were calculated based on our institutional cost of $357 per SRA test.

At our institution, argatroban is supplied in 50-mL bags; therefore, we utilized the number of bags to identify argatroban usage. Savings were calculated using the average wholesale price (AWP) of $292.50 per 50-mL bag. The amounts billed or collected for the SRA testing or argatroban treatment were not collected. Costs were estimated using only direct costs to the institution. Safety data were not collected. As the intent of our project was a quality improvement activity, this project did not require institutional review board regulation per our institutional guidance.

Results

During the pre-intervention period, the average number of admissions (adults and children) at UM was 5863 per month. Post intervention there was an average of 5842 admissions per month. A total of 1192 PF4 tests were ordered before the intervention and 1148 were ordered post intervention. Prior to the intervention, 481 SRA tests were completed, while post intervention 105 were completed. Serotonin-release testing decreased from an average of 3.7 SRA results per 1000 admissions during the pre-intervention period to an average of 0.6 per 1000 admissions post intervention (Figure 2). Cost-savings were $1045 per 1000 admissions.

During the pre-intervention period, 2539 bags of argatroban were used, while 2337 bags were used post intervention. The number of 50-mL argatroban bags used per 1000 admissions decreased from 18.8 before the intervention to 14.3 post intervention. Cost-savings were $1316.20 per 1000 admissions. Figure 3 illustrates the monthly argatroban utilization per 1000 admissions during each quarter from January 2016 through March 2020.

Discussion

We designed and implemented an evidence-based strategy for HIT at our academic institution which led to a decrease in unnecessary SRA testing and argatroban utilization, with associated cost savings. By focusing on a single point of intervention at the laboratory level where SRA tests were held and canceled if the PF4 test was negative, we helped offload the decision-making from the provider while simultaneously providing just-in-time education to the provider. This intervention was designed with input from multiple stakeholders, including physicians, quality improvement specialists, pharmacists, and coagulation laboratory personnel.

Serotonin-release testing dramatically decreased post intervention even though a similar number of PF4 tests were performed before and after the intervention. This suggests that the decrease in SRA testing was a direct consequence of our intervention. Post intervention the number of completed SRA tests was 9% of the number of PF4 tests sent. This is consistent with our baseline pre-intervention data showing that only 8% of all PF4 tests sent were positive.

While the absolute number of argatroban bags utilized did not dramatically decrease after the intervention, the quarterly rate did, particularly after 2018. Given that argatroban data were only drawn from patients with a concurrent SRA test, this decrease is clearly from decreased usage in patients with suspected HIT. We suspect the decrease occurred because argatroban was not being continued while awaiting an SRA test in patients with a negative PF4 test. Decreasing the utilization of argatroban not only saved money but also reduced days of exposure to argatroban. While we do not have data regarding adverse events related to argatroban prior to the intervention, it is logical to conclude that reducing unnecessary exposure to argatroban reduces the risk of adverse events related to bleeding. Future studies would ideally address specific safety outcome metrics such as adverse events, bleeding risk, or missed diagnoses of HIT.

Our institutional guidelines for the diagnosis of HIT are evidence-based and helpful but are rarely followed by busy inpatient providers. Controlling the utilization of the SRA at the laboratory level had several advantages. First, removing SRA decision-making from providers who are not experts in the diagnosis of HIT guaranteed adherence to evidence-based guidelines. Second, pharmacists could safely recommend discontinuing argatroban when the PF4 test was negative as there was no SRA pending. Third, with cancellation at the laboratory level there was no need to further burden providers with yet another alert in the electronic health record. Fourth, just-in-time education was provided to the providers with justification for why the SRA test was canceled. Last, ruling out HIT within 24 hours with the PF4 test alone allowed providers to evaluate patients for other causes of thrombocytopenia much earlier than the 3 to 5 business days before the SRA results returned.

A limitation of this study is that it was conducted at a single center. Our approach is also limited by the lack of universal applicability. At our institution we are fortunate to have PF4 testing available in our coagulation laboratory 7 days a week. In addition, the coagulation laboratory controls sending the SRA to the reference laboratory. The specific intervention of controlling the SRA testing is therefore applicable only to institutions similar to ours; however, the concept of removing control of specialized testing from the provider is not unique. Inpatient thrombophilia testing has been a successful target of this approach.^11-13 While electronic alerts and education of individual providers can also be effective initially, the effectiveness of these interventions has been repeatedly shown to wane over time.^14-16

Conclusion

At our institution we were able to implement practical, evidence-based testing for HIT by implementing control over SRA testing at the level of the laboratory. This approach led to decreased argatroban utilization and cost savings.

Corresponding author: Alice Cusick, MD; LTC Charles S Kettles VA Medical Center, 2215 Fuller Road, Ann Arbor, MI 48105; [email protected]

Disclosures: None reported.

doi: 10.12788/jcom.0087

From the Veterans Affairs Ann Arbor Healthcare System Medicine Service (Dr. Cusick), University of Michigan College of Pharmacy, Clinical Pharmacy Service, Michigan Medicine (Dr. Hanigan), Department of Internal Medicine Clinical Experience and Quality, Michigan Medicine (Linda Bashaw), Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI (Dr. Heidemann), and the Operational Excellence Department, Sparrow Health System, Lansing, MI (Matthew Johnson).

Abstract

Background: Diagnosis of heparin-induced thrombocytopenia (HIT) requires completion of an enzyme-linked immunosorbent assay (ELISA)–based heparin-platelet factor 4 (PF4) antibody test. If this test is negative, HIT is excluded. If positive, a serotonin-release assay (SRA) test is indicated. The SRA is expensive and sometimes inappropriately ordered despite negative PF4 results, leading to unnecessary treatment with argatroban while awaiting SRA results.

Objectives: The primary objectives of this project were to reduce unnecessary SRA testing and argatroban utilization in patients with suspected HIT.

Methods: The authors implemented an intervention at a tertiary care academic hospital in November 2017 targeting patients hospitalized with suspected HIT. The intervention was controlled at the level of the laboratory and prevented ordering of SRA tests in the absence of a positive PF4 test. The number of SRA tests performed and argatroban bags administered were identified retrospectively via chart review before the intervention (January 2016 to November 2017) and post intervention (December 2017 to March 2020). Associated costs were calculated based on institutional SRA testing cost as well as the average wholesale price of argatroban.

Results: SRA testing decreased from an average of 3.7 SRA results per 1000 admissions before the intervention to an average of 0.6 results per 1000 admissions post intervention. The number of 50-mL argatroban bags used per 1000 admissions decreased from 18.8 prior to the intervention to 14.3 post intervention. Total estimated cost savings per 1000 admissions was $2361.20.

Conclusion: An evidence-based testing strategy for HIT can be effectively implemented at the level of the laboratory. This approach led to reductions in SRA testing and argatroban utilization with resultant cost savings.

Keywords: HIT, argatroban, anticoagulation, serotonin-release assay.

Thrombocytopenia is a common finding in hospitalized patients.^1,2 Heparin-induced thrombocytopenia (HIT) is one of the many potential causes of thrombocytopenia in hospitalized patients and occurs when antibodies to the heparin-platelet factor 4 (PF4) complex develop after heparin exposure. This triggers a cascade of events, leading to platelet activation, platelet consumption, and thrombosis. While HIT is relatively rare, occurring in 0.3% to 0.5% of critically ill patients, many patients will be tested to rule out this potentially life-threatening cause of thrombocytopenia.³

The diagnosis of HIT utilizes a combination of both clinical suspicion and laboratory testing.⁴ The 4T score (Table) was developed to evaluate the clinical probability of HIT and involves assessing the degree and timing of thrombocytopenia, the presence or absence of thrombosis, and other potential causes of the thrombocytopenia.⁵ The 4T score is designed to be utilized to identify patients who require laboratory testing for HIT; however, it has low inter-rater agreement in patients undergoing evaluation for HIT,⁶ and, in our experience, completion of this scoring is time-consuming.

The enzyme-linked immunosorbent assay (ELISA) is a commonly used laboratory test to diagnose HIT that detects antibodies to the heparin-PF4 complex utilizing optical density (OD) units. When using an OD cutoff of 0.400, ELISA PF4 (PF4) tests have a sensitivity of 99.6%, but poor specificity at 69.3%.⁷ When the PF4 antibody test is positive with an OD ≥0.400, then a functional test is used to determine whether the antibodies detected will activate platelets. The serotonin-release assay (SRA) is a functional test that measures 14C-labeled serotonin release from donor platelets when mixed with patient serum or plasma containing HIT antibodies. In the correct clinical context, a positive ELISA PF4 antibody test along with a positive SRA is diagnostic of HIT.⁸

The process of diagnosing HIT in a timely and cost-effective manner is dependent on the clinician’s experience in diagnosing HIT as well as access to the laboratory testing necessary to confirm the diagnosis. PF4 antibody tests are time-consuming and not always available daily and/or are not available onsite. The SRA requires access to donor platelets and specialized radioactivity counting equipment, making it available only at particular centers.

The treatment of HIT is more straightforward and involves stopping all heparin products and starting a nonheparin anticoagulant. The direct thrombin inhibitor argatroban is one of the standard nonheparin anticoagulants used in patients with suspected HIT.⁴ While it is expensive, its short half-life and lack of renal clearance make it ideal for treatment of hospitalized patients with suspected HIT, many of whom need frequent procedures and/or have renal disease.

At our academic tertiary care center, we performed a retrospective analysis that showed inappropriate ordering of diagnostic HIT testing as well as unnecessary use of argatroban even when there was low suspicion for HIT based on laboratory findings. The aim of our project was to reduce unnecessary HIT testing and argatroban utilization without overburdening providers or interfering with established workflows.

Methods

Setting

The University of Michigan (UM) hospital is a 1000-bed tertiary care center in Ann Arbor, Michigan. The UM guidelines reflect evidence-based guidelines for the diagnosis and treatment of HIT.⁴ In 2016 the UM guidelines for laboratory testing included sending the PF4 antibody test first when there was clinical suspicion of HIT. The SRA was to be sent separately only when the PF4 returned positive (OD ≥ 0.400). Standard guidelines at UM also included switching patients with suspected HIT from heparin to a nonheparin anticoagulant and stopping all heparin products while awaiting the SRA results. The direct thrombin inhibitor argatroban is utilized at UM and monitored with anti-IIa levels. University of Michigan Hospital utilizes the Immucor PF4 IgG ELISA for detecting heparin-associated antibodies.⁹ In 2016, this PF4 test was performed in the UM onsite laboratory Monday through Friday. At UM the SRA is performed off site, with a turnaround time of 3 to 5 business days.

Baseline Data

We retrospectively reviewed PF4 and SRA testing as well as argatroban usage from December 2016 to May 2017. Despite the institutional guidelines, providers were sending PF4 and SRA simultaneously as soon as HIT was suspected; 62% of PF4 tests were ordered simultaneously with the SRA, but only 8% of these PF4 tests were positive with an OD ≥0.400. Of those patients with negative PF4 testing, argatroban was continued until the SRA returned negative, leading to many days of unnecessary argatroban usage. An informal survey of the anticoagulation pharmacists revealed that many recommended discontinuing argatroban when the PF4 test was negative, but providers routinely did not feel comfortable with this approach. This suggested many providers misunderstood the performance characteristics of the PF4 test.

Intervention

Our team consisted of hematology and internal medicine faculty, pharmacists, coagulation laboratory personnel, and quality improvement specialists. We designed and implemented an intervention in November 2017 focused on controlling the ordering of the SRA test. We chose to focus on this step due to the excellent sensitivity of the PF4 test with a cutoff of OD <0.400 and the significant expense of the SRA test. Under direction of the Coagulation Laboratory Director, a standard operating procedure was developed where the coagulation laboratory personnel did not send out the SRA until a positive PF4 test (OD ≥ 0.400) was reported. If the PF4 was negative, the SRA was canceled and the ordering provider received notification of the cancelled test via the electronic medical record, accompanied by education about HIT testing (Figure 1). In addition, the lab increased the availability of PF4 testing from 5 days to 7 days a week so there were no delays in tests ordered on Fridays or weekends.

Outcomes

Our primary goals were to decrease both SRA testing and argatroban use. Secondarily, we examined the cost-effectiveness of this intervention. We hypothesized that controlling the SRA testing at the laboratory level would decrease both SRA testing and argatroban use.

Data Collection

Pre- and postintervention data were collected retrospectively. Pre-intervention data were from January 2016 through November 2017, and postintervention data were from December 2017 through March 2020. The number of SRA tests performed were identified retrospectively via review of electronic ordering records. All patients who had a hospital admission after January 1, 2016, were included. These patients were filtered to include only those who had a result for an SRA test. In order to calculate cost-savings, we identified both the number of SRA tests ordered retrospectively as well as patients who had both an SRA resulted and had been administered argatroban. Cost-savings were calculated based on our institutional cost of $357 per SRA test.

At our institution, argatroban is supplied in 50-mL bags; therefore, we utilized the number of bags to identify argatroban usage. Savings were calculated using the average wholesale price (AWP) of $292.50 per 50-mL bag. The amounts billed or collected for the SRA testing or argatroban treatment were not collected. Costs were estimated using only direct costs to the institution. Safety data were not collected. As the intent of our project was a quality improvement activity, this project did not require institutional review board regulation per our institutional guidance.

Results

During the pre-intervention period, the average number of admissions (adults and children) at UM was 5863 per month. Post intervention there was an average of 5842 admissions per month. A total of 1192 PF4 tests were ordered before the intervention and 1148 were ordered post intervention. Prior to the intervention, 481 SRA tests were completed, while post intervention 105 were completed. Serotonin-release testing decreased from an average of 3.7 SRA results per 1000 admissions during the pre-intervention period to an average of 0.6 per 1000 admissions post intervention (Figure 2). Cost-savings were $1045 per 1000 admissions.

During the pre-intervention period, 2539 bags of argatroban were used, while 2337 bags were used post intervention. The number of 50-mL argatroban bags used per 1000 admissions decreased from 18.8 before the intervention to 14.3 post intervention. Cost-savings were $1316.20 per 1000 admissions. Figure 3 illustrates the monthly argatroban utilization per 1000 admissions during each quarter from January 2016 through March 2020.

Discussion

We designed and implemented an evidence-based strategy for HIT at our academic institution which led to a decrease in unnecessary SRA testing and argatroban utilization, with associated cost savings. By focusing on a single point of intervention at the laboratory level where SRA tests were held and canceled if the PF4 test was negative, we helped offload the decision-making from the provider while simultaneously providing just-in-time education to the provider. This intervention was designed with input from multiple stakeholders, including physicians, quality improvement specialists, pharmacists, and coagulation laboratory personnel.

Serotonin-release testing dramatically decreased post intervention even though a similar number of PF4 tests were performed before and after the intervention. This suggests that the decrease in SRA testing was a direct consequence of our intervention. Post intervention the number of completed SRA tests was 9% of the number of PF4 tests sent. This is consistent with our baseline pre-intervention data showing that only 8% of all PF4 tests sent were positive.

While the absolute number of argatroban bags utilized did not dramatically decrease after the intervention, the quarterly rate did, particularly after 2018. Given that argatroban data were only drawn from patients with a concurrent SRA test, this decrease is clearly from decreased usage in patients with suspected HIT. We suspect the decrease occurred because argatroban was not being continued while awaiting an SRA test in patients with a negative PF4 test. Decreasing the utilization of argatroban not only saved money but also reduced days of exposure to argatroban. While we do not have data regarding adverse events related to argatroban prior to the intervention, it is logical to conclude that reducing unnecessary exposure to argatroban reduces the risk of adverse events related to bleeding. Future studies would ideally address specific safety outcome metrics such as adverse events, bleeding risk, or missed diagnoses of HIT.

Our institutional guidelines for the diagnosis of HIT are evidence-based and helpful but are rarely followed by busy inpatient providers. Controlling the utilization of the SRA at the laboratory level had several advantages. First, removing SRA decision-making from providers who are not experts in the diagnosis of HIT guaranteed adherence to evidence-based guidelines. Second, pharmacists could safely recommend discontinuing argatroban when the PF4 test was negative as there was no SRA pending. Third, with cancellation at the laboratory level there was no need to further burden providers with yet another alert in the electronic health record. Fourth, just-in-time education was provided to the providers with justification for why the SRA test was canceled. Last, ruling out HIT within 24 hours with the PF4 test alone allowed providers to evaluate patients for other causes of thrombocytopenia much earlier than the 3 to 5 business days before the SRA results returned.

A limitation of this study is that it was conducted at a single center. Our approach is also limited by the lack of universal applicability. At our institution we are fortunate to have PF4 testing available in our coagulation laboratory 7 days a week. In addition, the coagulation laboratory controls sending the SRA to the reference laboratory. The specific intervention of controlling the SRA testing is therefore applicable only to institutions similar to ours; however, the concept of removing control of specialized testing from the provider is not unique. Inpatient thrombophilia testing has been a successful target of this approach.^11-13 While electronic alerts and education of individual providers can also be effective initially, the effectiveness of these interventions has been repeatedly shown to wane over time.^14-16

Conclusion

At our institution we were able to implement practical, evidence-based testing for HIT by implementing control over SRA testing at the level of the laboratory. This approach led to decreased argatroban utilization and cost savings.

Corresponding author: Alice Cusick, MD; LTC Charles S Kettles VA Medical Center, 2215 Fuller Road, Ann Arbor, MI 48105; [email protected]

Disclosures: None reported.

doi: 10.12788/jcom.0087

From the Veterans Affairs Ann Arbor Healthcare System Medicine Service (Dr. Cusick), University of Michigan College of Pharmacy, Clinical Pharmacy Service, Michigan Medicine (Dr. Hanigan), Department of Internal Medicine Clinical Experience and Quality, Michigan Medicine (Linda Bashaw), Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI (Dr. Heidemann), and the Operational Excellence Department, Sparrow Health System, Lansing, MI (Matthew Johnson).

Abstract

Background: Diagnosis of heparin-induced thrombocytopenia (HIT) requires completion of an enzyme-linked immunosorbent assay (ELISA)–based heparin-platelet factor 4 (PF4) antibody test. If this test is negative, HIT is excluded. If positive, a serotonin-release assay (SRA) test is indicated. The SRA is expensive and sometimes inappropriately ordered despite negative PF4 results, leading to unnecessary treatment with argatroban while awaiting SRA results.

Objectives: The primary objectives of this project were to reduce unnecessary SRA testing and argatroban utilization in patients with suspected HIT.

Methods: The authors implemented an intervention at a tertiary care academic hospital in November 2017 targeting patients hospitalized with suspected HIT. The intervention was controlled at the level of the laboratory and prevented ordering of SRA tests in the absence of a positive PF4 test. The number of SRA tests performed and argatroban bags administered were identified retrospectively via chart review before the intervention (January 2016 to November 2017) and post intervention (December 2017 to March 2020). Associated costs were calculated based on institutional SRA testing cost as well as the average wholesale price of argatroban.

Results: SRA testing decreased from an average of 3.7 SRA results per 1000 admissions before the intervention to an average of 0.6 results per 1000 admissions post intervention. The number of 50-mL argatroban bags used per 1000 admissions decreased from 18.8 prior to the intervention to 14.3 post intervention. Total estimated cost savings per 1000 admissions was $2361.20.

Conclusion: An evidence-based testing strategy for HIT can be effectively implemented at the level of the laboratory. This approach led to reductions in SRA testing and argatroban utilization with resultant cost savings.

Keywords: HIT, argatroban, anticoagulation, serotonin-release assay.

Thrombocytopenia is a common finding in hospitalized patients.^1,2 Heparin-induced thrombocytopenia (HIT) is one of the many potential causes of thrombocytopenia in hospitalized patients and occurs when antibodies to the heparin-platelet factor 4 (PF4) complex develop after heparin exposure. This triggers a cascade of events, leading to platelet activation, platelet consumption, and thrombosis. While HIT is relatively rare, occurring in 0.3% to 0.5% of critically ill patients, many patients will be tested to rule out this potentially life-threatening cause of thrombocytopenia.³

The diagnosis of HIT utilizes a combination of both clinical suspicion and laboratory testing.⁴ The 4T score (Table) was developed to evaluate the clinical probability of HIT and involves assessing the degree and timing of thrombocytopenia, the presence or absence of thrombosis, and other potential causes of the thrombocytopenia.⁵ The 4T score is designed to be utilized to identify patients who require laboratory testing for HIT; however, it has low inter-rater agreement in patients undergoing evaluation for HIT,⁶ and, in our experience, completion of this scoring is time-consuming.

The enzyme-linked immunosorbent assay (ELISA) is a commonly used laboratory test to diagnose HIT that detects antibodies to the heparin-PF4 complex utilizing optical density (OD) units. When using an OD cutoff of 0.400, ELISA PF4 (PF4) tests have a sensitivity of 99.6%, but poor specificity at 69.3%.⁷ When the PF4 antibody test is positive with an OD ≥0.400, then a functional test is used to determine whether the antibodies detected will activate platelets. The serotonin-release assay (SRA) is a functional test that measures 14C-labeled serotonin release from donor platelets when mixed with patient serum or plasma containing HIT antibodies. In the correct clinical context, a positive ELISA PF4 antibody test along with a positive SRA is diagnostic of HIT.⁸

The process of diagnosing HIT in a timely and cost-effective manner is dependent on the clinician’s experience in diagnosing HIT as well as access to the laboratory testing necessary to confirm the diagnosis. PF4 antibody tests are time-consuming and not always available daily and/or are not available onsite. The SRA requires access to donor platelets and specialized radioactivity counting equipment, making it available only at particular centers.

The treatment of HIT is more straightforward and involves stopping all heparin products and starting a nonheparin anticoagulant. The direct thrombin inhibitor argatroban is one of the standard nonheparin anticoagulants used in patients with suspected HIT.⁴ While it is expensive, its short half-life and lack of renal clearance make it ideal for treatment of hospitalized patients with suspected HIT, many of whom need frequent procedures and/or have renal disease.

At our academic tertiary care center, we performed a retrospective analysis that showed inappropriate ordering of diagnostic HIT testing as well as unnecessary use of argatroban even when there was low suspicion for HIT based on laboratory findings. The aim of our project was to reduce unnecessary HIT testing and argatroban utilization without overburdening providers or interfering with established workflows.

Methods

Setting

The University of Michigan (UM) hospital is a 1000-bed tertiary care center in Ann Arbor, Michigan. The UM guidelines reflect evidence-based guidelines for the diagnosis and treatment of HIT.⁴ In 2016 the UM guidelines for laboratory testing included sending the PF4 antibody test first when there was clinical suspicion of HIT. The SRA was to be sent separately only when the PF4 returned positive (OD ≥ 0.400). Standard guidelines at UM also included switching patients with suspected HIT from heparin to a nonheparin anticoagulant and stopping all heparin products while awaiting the SRA results. The direct thrombin inhibitor argatroban is utilized at UM and monitored with anti-IIa levels. University of Michigan Hospital utilizes the Immucor PF4 IgG ELISA for detecting heparin-associated antibodies.⁹ In 2016, this PF4 test was performed in the UM onsite laboratory Monday through Friday. At UM the SRA is performed off site, with a turnaround time of 3 to 5 business days.

Baseline Data

We retrospectively reviewed PF4 and SRA testing as well as argatroban usage from December 2016 to May 2017. Despite the institutional guidelines, providers were sending PF4 and SRA simultaneously as soon as HIT was suspected; 62% of PF4 tests were ordered simultaneously with the SRA, but only 8% of these PF4 tests were positive with an OD ≥0.400. Of those patients with negative PF4 testing, argatroban was continued until the SRA returned negative, leading to many days of unnecessary argatroban usage. An informal survey of the anticoagulation pharmacists revealed that many recommended discontinuing argatroban when the PF4 test was negative, but providers routinely did not feel comfortable with this approach. This suggested many providers misunderstood the performance characteristics of the PF4 test.

Intervention

Our team consisted of hematology and internal medicine faculty, pharmacists, coagulation laboratory personnel, and quality improvement specialists. We designed and implemented an intervention in November 2017 focused on controlling the ordering of the SRA test. We chose to focus on this step due to the excellent sensitivity of the PF4 test with a cutoff of OD <0.400 and the significant expense of the SRA test. Under direction of the Coagulation Laboratory Director, a standard operating procedure was developed where the coagulation laboratory personnel did not send out the SRA until a positive PF4 test (OD ≥ 0.400) was reported. If the PF4 was negative, the SRA was canceled and the ordering provider received notification of the cancelled test via the electronic medical record, accompanied by education about HIT testing (Figure 1). In addition, the lab increased the availability of PF4 testing from 5 days to 7 days a week so there were no delays in tests ordered on Fridays or weekends.

Outcomes

Our primary goals were to decrease both SRA testing and argatroban use. Secondarily, we examined the cost-effectiveness of this intervention. We hypothesized that controlling the SRA testing at the laboratory level would decrease both SRA testing and argatroban use.

Data Collection

Pre- and postintervention data were collected retrospectively. Pre-intervention data were from January 2016 through November 2017, and postintervention data were from December 2017 through March 2020. The number of SRA tests performed were identified retrospectively via review of electronic ordering records. All patients who had a hospital admission after January 1, 2016, were included. These patients were filtered to include only those who had a result for an SRA test. In order to calculate cost-savings, we identified both the number of SRA tests ordered retrospectively as well as patients who had both an SRA resulted and had been administered argatroban. Cost-savings were calculated based on our institutional cost of $357 per SRA test.

At our institution, argatroban is supplied in 50-mL bags; therefore, we utilized the number of bags to identify argatroban usage. Savings were calculated using the average wholesale price (AWP) of $292.50 per 50-mL bag. The amounts billed or collected for the SRA testing or argatroban treatment were not collected. Costs were estimated using only direct costs to the institution. Safety data were not collected. As the intent of our project was a quality improvement activity, this project did not require institutional review board regulation per our institutional guidance.

Results

During the pre-intervention period, the average number of admissions (adults and children) at UM was 5863 per month. Post intervention there was an average of 5842 admissions per month. A total of 1192 PF4 tests were ordered before the intervention and 1148 were ordered post intervention. Prior to the intervention, 481 SRA tests were completed, while post intervention 105 were completed. Serotonin-release testing decreased from an average of 3.7 SRA results per 1000 admissions during the pre-intervention period to an average of 0.6 per 1000 admissions post intervention (Figure 2). Cost-savings were $1045 per 1000 admissions.

During the pre-intervention period, 2539 bags of argatroban were used, while 2337 bags were used post intervention. The number of 50-mL argatroban bags used per 1000 admissions decreased from 18.8 before the intervention to 14.3 post intervention. Cost-savings were $1316.20 per 1000 admissions. Figure 3 illustrates the monthly argatroban utilization per 1000 admissions during each quarter from January 2016 through March 2020.

Discussion

We designed and implemented an evidence-based strategy for HIT at our academic institution which led to a decrease in unnecessary SRA testing and argatroban utilization, with associated cost savings. By focusing on a single point of intervention at the laboratory level where SRA tests were held and canceled if the PF4 test was negative, we helped offload the decision-making from the provider while simultaneously providing just-in-time education to the provider. This intervention was designed with input from multiple stakeholders, including physicians, quality improvement specialists, pharmacists, and coagulation laboratory personnel.

Serotonin-release testing dramatically decreased post intervention even though a similar number of PF4 tests were performed before and after the intervention. This suggests that the decrease in SRA testing was a direct consequence of our intervention. Post intervention the number of completed SRA tests was 9% of the number of PF4 tests sent. This is consistent with our baseline pre-intervention data showing that only 8% of all PF4 tests sent were positive.

While the absolute number of argatroban bags utilized did not dramatically decrease after the intervention, the quarterly rate did, particularly after 2018. Given that argatroban data were only drawn from patients with a concurrent SRA test, this decrease is clearly from decreased usage in patients with suspected HIT. We suspect the decrease occurred because argatroban was not being continued while awaiting an SRA test in patients with a negative PF4 test. Decreasing the utilization of argatroban not only saved money but also reduced days of exposure to argatroban. While we do not have data regarding adverse events related to argatroban prior to the intervention, it is logical to conclude that reducing unnecessary exposure to argatroban reduces the risk of adverse events related to bleeding. Future studies would ideally address specific safety outcome metrics such as adverse events, bleeding risk, or missed diagnoses of HIT.

Our institutional guidelines for the diagnosis of HIT are evidence-based and helpful but are rarely followed by busy inpatient providers. Controlling the utilization of the SRA at the laboratory level had several advantages. First, removing SRA decision-making from providers who are not experts in the diagnosis of HIT guaranteed adherence to evidence-based guidelines. Second, pharmacists could safely recommend discontinuing argatroban when the PF4 test was negative as there was no SRA pending. Third, with cancellation at the laboratory level there was no need to further burden providers with yet another alert in the electronic health record. Fourth, just-in-time education was provided to the providers with justification for why the SRA test was canceled. Last, ruling out HIT within 24 hours with the PF4 test alone allowed providers to evaluate patients for other causes of thrombocytopenia much earlier than the 3 to 5 business days before the SRA results returned.

A limitation of this study is that it was conducted at a single center. Our approach is also limited by the lack of universal applicability. At our institution we are fortunate to have PF4 testing available in our coagulation laboratory 7 days a week. In addition, the coagulation laboratory controls sending the SRA to the reference laboratory. The specific intervention of controlling the SRA testing is therefore applicable only to institutions similar to ours; however, the concept of removing control of specialized testing from the provider is not unique. Inpatient thrombophilia testing has been a successful target of this approach.^11-13 While electronic alerts and education of individual providers can also be effective initially, the effectiveness of these interventions has been repeatedly shown to wane over time.^14-16

Conclusion

At our institution we were able to implement practical, evidence-based testing for HIT by implementing control over SRA testing at the level of the laboratory. This approach led to decreased argatroban utilization and cost savings.

Corresponding author: Alice Cusick, MD; LTC Charles S Kettles VA Medical Center, 2215 Fuller Road, Ann Arbor, MI 48105; [email protected]

Disclosures: None reported.

doi: 10.12788/jcom.0087

From Hassenfeld Children’s Hospital at NYU Langone Health, New York, NY (Dr Gallagher), T1D Exchange, Boston, MA (Saketh Rompicherla; Drs Ebekozien, Noor, Odugbesan, and Mungmode; Nicole Rioles, Emma Ospelt), University of Mississippi School of Population Health, Jackson, MS (Dr. Ebekozien), Icahn School of Medicine at Mount Sinai, New York, NY (Drs. Wilkes, O’Malley, and Rapaport), Weill Cornell Medicine, New York, NY (Drs. Antal and Feuer), NYU Long Island School of Medicine, Mineola, NY (Dr. Gabriel), NYU Langone Health, New York, NY (Dr. Golden), Barbara Davis Center, Aurora, CO (Dr. Alonso), Texas Children’s Hospital/Baylor College of Medicine, Houston, TX (Dr. Lyons), Stanford University, Stanford, CA (Dr. Prahalad), Children Mercy Kansas City, MO (Dr. Clements), Indiana University School of Medicine, IN (Dr. Neyman), Rady Children’s Hospital, University of California, San Diego, CA (Dr. Demeterco-Berggren).

Background: Patient outcomes of COVID-19 have improved throughout the pandemic. However, because it is not known whether outcomes of COVID-19 in the type 1 diabetes (T1D) population improved over time, we investigated differences in COVID-19 outcomes for patients with T1D in the United States.

Methods: We analyzed data collected via a registry of patients with T1D and COVID-19 from 56 sites between April 2020 and January 2021. We grouped cases into first surge (April 9, 2020, to July 31, 2020, n = 188) and late surge (August 1, 2020, to January 31, 2021, n = 410), and then compared outcomes between both groups using descriptive statistics and logistic regression models.

Results: Adverse outcomes were more frequent during the first surge, including diabetic ketoacidosis (32% vs 15%, P < .001), severe hypoglycemia (4% vs 1%, P = .04), and hospitalization (52% vs 22%, P < .001). Patients in the first surge were older (28 [SD,18.8] years vs 18.0 [SD, 11.1] years, P < .001), had higher median hemoglobin A1c levels (9.3 [interquartile range {IQR}, 4.0] vs 8.4 (IQR, 2.8), P < .001), and were more likely to use public insurance (107 [57%] vs 154 [38%], P < .001). The odds of hospitalization for adults in the first surge were 5 times higher compared to the late surge (odds ratio, 5.01; 95% CI, 2.11-12.63).

Conclusion: Patients with T1D who presented with COVID-19 during the first surge had a higher proportion of adverse outcomes than those who presented in a later surge.

Keywords: TD1, diabetic ketoacidosis, hypoglycemia.

After the World Health Organization declared the disease caused by the novel coronavirus SARS-CoV-2, COVID-19, a pandemic on March 11, 2020, the Centers for Disease Control and Prevention identified patients with diabetes as high risk for severe illness.^1-7 The case-fatality rate for COVID-19 has significantly improved over the past 2 years. Public health measures, less severe COVID-19 variants, increased access to testing, and new treatments for COVID-19 have contributed to improved outcomes.

The T1D Exchange has previously published findings on COVID-19 outcomes for patients with type 1 diabetes (T1D) using data from the T1D COVID-19 Surveillance Registry.^8-12 Given improved outcomes in COVID-19 in the general population, we sought to determine if outcomes for cases of COVID-19 reported to this registry changed over time.

Methods

This study was coordinated by the T1D Exchange and approved as nonhuman subject research by the Western Institutional Review Board. All participating centers also obtained local institutional review board approval. No identifiable patient information was collected as part of this noninterventional, cross-sectional study.

The T1D Exchange Multi-center COVID-19 Surveillance Study collected data from endocrinology clinics that completed a retrospective chart review and submitted information to T1D Exchange via an online questionnaire for all patients with T1D at their sites who tested positive for COVID-19.^13,14 The questionnaire was administered using the Qualtrics survey platform (www.qualtrics.com version XM) and contained 33 pre-coded and free-text response fields to collect patient and clinical attributes.

Each participating center identified 1 team member for reporting to avoid duplicate case submission. Each submitted case was reviewed for potential errors and incomplete information. The coordinating center verified the number of cases per site for data quality assurance.

Quantitative data were represented as mean (standard deviation) or median (interquartile range). Categorical data were described as the number (percentage) of patients. Summary statistics, including frequency and percentage for categorical variables, were calculated for all patient-related and clinical characteristics. The date August 1, 2021, was selected as the end of the first surge based on a review of national COVID-19 surges.

We used the Fisher’s exact test to assess associations between hospitalization and demographics, HbA1c, diabetes duration, symptoms, and adverse outcomes. In addition, multivariate logistic regression was used to calculate odds ratios (OR). Logistic regression models were used to determine the association between time of surge and hospitalization separately for both the pediatric and adult populations. Each model was adjusted for potential sociodemographic confounders, specifically age, sex, race, insurance, and HbA1c.

All tests were 2-sided, with type 1 error set at 5%. Fisher’s exact test and logistic regression were performed using statistical software R, version 3.6.2 (R Foundation for Statistical Computing).

Results

The characteristics of COVID-19 cases in patients with T1D that were reported early in the pandemic, before August 1, 2020 (first surge), compared with those of cases reported on and after August 1, 2020 (later surges) are shown in Table 1.

Patients with T1D who presented with COVID-19 during the first surge as compared to the later surges were older (mean age 28 [SD, 18.0] years vs 18.8 [SD, 11.1] years; P < .001) and had a longer duration of diabetes (P < .001). The first-surge group also had more patients with >20 years’ diabetes duration (20% vs 9%, P < .001). Obesity, hypertension, and chronic kidney disease were also more commonly reported in first-surge cases (all P < .001).

There was a significant difference in race and ethnicity reported in the first surge vs the later surge cases, with fewer patients identifying as non-Hispanic White (39% vs, 63%, P < .001) and more patients identifying as non-Hispanic Black (29% vs 12%, P < .001). The groups also differed significantly in terms of insurance type, with more people on public insurance in the first-surge group (57% vs 38%, P < .001). In addition, median HbA1c was higher (9.3% vs 8.4%, P < .001) and continuous glucose monitor and insulin pump use were less common (P = .02 and <.001, respectively) in the early surge.

All symptoms and adverse outcomes were reported more often in the first surge, including diabetic ketoacidosis (DKA; 32% vs 15%; P < .001) and severe hypoglycemia (4% vs 1%, P = .04). Hospitalization (52% vs 13%, P < .001) and ICU admission (24% vs 9%, P < .001) were reported more often in the first-surge group.

Regression Analyses

Table 2 shows the results of logistic regression analyses for hospitalization in the pediatric (≤19 years of age) and adult (>19 years of age) groups, along with the odds of hospitalization during the first vs late surge among COVID-positive people with T1D. Adult patients who tested positive in the first surge were about 5 times more likely to be hospitalized than adults who tested positive for infection in the late surge after adjusting for age, insurance type, sex, race, and HbA1c levels. Pediatric patients also had an increased odds for hospitalization during the first surge, but this increase was not statistically significant.

Discussion

Our analysis of COVID-19 cases in patients with T1D reported by diabetes providers across the United States found that adverse outcomes were more prevalent early in the pandemic. There may be a number of reasons for this difference in outcomes between patients who presented in the first surge vs a later surge. First, because testing for COVID-19 was extremely limited and reserved for hospitalized patients early in the pandemic, the first-surge patients with confirmed COVID-19 likely represent a skewed population of higher-acuity patients. This may also explain the relative paucity of cases in younger patients reported early in the pandemic. Second, worse outcomes in the early surge may also have been associated with overwhelmed hospitals in New York City at the start of the outbreak. According to Cummings et al, the abrupt surge of critically ill patients hospitalized with severe acute respiratory distress syndrome initially outpaced their capacity to provide prone-positioning ventilation, which has been expanded since then.¹⁵ While there was very little hypertension, cardiovascular disease, or kidney disease reported in the pediatric groups, there was a higher prevalence of obesity in the pediatric group from the mid-Atlantic region. Obesity has been associated with a worse prognosis for COVID-19 illness in children.¹⁶ Finally, there were 5 deaths reported in this study, all of which were reported during the first surge. Older age and increased rates of cardiovascular disease and chronic kidney disease in the first surge cases likely contributed to worse outcomes for adults in mid-Atlantic region relative to the other regions. Minority race and the use of public insurance, risk factors for more severe outcomes in all regions, were also more common in cases reported from the mid-Atlantic region.

This study has several limitations. First, it is a cross-sectional study that relies upon voluntary provider reports. Second, availability of COVID-19 testing was limited in all regions in spring 2020. Third, different regions of the country experienced subsequent surges at different times within the reported timeframes in this analysis. Fourth, this report time period does not include the impact of the newer COVID-19 variants. Finally, trends in COVID-19 outcomes were affected by the evolution of care that developed throughout 2020.

Conclusion

Adult patients with T1D and COVID-19 who reported during the first surge had about 5 times higher hospitalization odds than those who presented in a later surge.

Corresponding author: Osagie Ebekozien, MD, MPH, 11 Avenue de Lafayette, Boston, MA 02111; [email protected]

Disclosures: Dr Ebekozien reports receiving research grants from Medtronic Diabetes, Eli Lilly, and Dexcom, and receiving honoraria from Medtronic Diabetes.

From Hassenfeld Children’s Hospital at NYU Langone Health, New York, NY (Dr Gallagher), T1D Exchange, Boston, MA (Saketh Rompicherla; Drs Ebekozien, Noor, Odugbesan, and Mungmode; Nicole Rioles, Emma Ospelt), University of Mississippi School of Population Health, Jackson, MS (Dr. Ebekozien), Icahn School of Medicine at Mount Sinai, New York, NY (Drs. Wilkes, O’Malley, and Rapaport), Weill Cornell Medicine, New York, NY (Drs. Antal and Feuer), NYU Long Island School of Medicine, Mineola, NY (Dr. Gabriel), NYU Langone Health, New York, NY (Dr. Golden), Barbara Davis Center, Aurora, CO (Dr. Alonso), Texas Children’s Hospital/Baylor College of Medicine, Houston, TX (Dr. Lyons), Stanford University, Stanford, CA (Dr. Prahalad), Children Mercy Kansas City, MO (Dr. Clements), Indiana University School of Medicine, IN (Dr. Neyman), Rady Children’s Hospital, University of California, San Diego, CA (Dr. Demeterco-Berggren).

Background: Patient outcomes of COVID-19 have improved throughout the pandemic. However, because it is not known whether outcomes of COVID-19 in the type 1 diabetes (T1D) population improved over time, we investigated differences in COVID-19 outcomes for patients with T1D in the United States.

Methods: We analyzed data collected via a registry of patients with T1D and COVID-19 from 56 sites between April 2020 and January 2021. We grouped cases into first surge (April 9, 2020, to July 31, 2020, n = 188) and late surge (August 1, 2020, to January 31, 2021, n = 410), and then compared outcomes between both groups using descriptive statistics and logistic regression models.

Results: Adverse outcomes were more frequent during the first surge, including diabetic ketoacidosis (32% vs 15%, P < .001), severe hypoglycemia (4% vs 1%, P = .04), and hospitalization (52% vs 22%, P < .001). Patients in the first surge were older (28 [SD,18.8] years vs 18.0 [SD, 11.1] years, P < .001), had higher median hemoglobin A1c levels (9.3 [interquartile range {IQR}, 4.0] vs 8.4 (IQR, 2.8), P < .001), and were more likely to use public insurance (107 [57%] vs 154 [38%], P < .001). The odds of hospitalization for adults in the first surge were 5 times higher compared to the late surge (odds ratio, 5.01; 95% CI, 2.11-12.63).

Conclusion: Patients with T1D who presented with COVID-19 during the first surge had a higher proportion of adverse outcomes than those who presented in a later surge.

Keywords: TD1, diabetic ketoacidosis, hypoglycemia.

After the World Health Organization declared the disease caused by the novel coronavirus SARS-CoV-2, COVID-19, a pandemic on March 11, 2020, the Centers for Disease Control and Prevention identified patients with diabetes as high risk for severe illness.^1-7 The case-fatality rate for COVID-19 has significantly improved over the past 2 years. Public health measures, less severe COVID-19 variants, increased access to testing, and new treatments for COVID-19 have contributed to improved outcomes.

The T1D Exchange has previously published findings on COVID-19 outcomes for patients with type 1 diabetes (T1D) using data from the T1D COVID-19 Surveillance Registry.^8-12 Given improved outcomes in COVID-19 in the general population, we sought to determine if outcomes for cases of COVID-19 reported to this registry changed over time.

Methods

This study was coordinated by the T1D Exchange and approved as nonhuman subject research by the Western Institutional Review Board. All participating centers also obtained local institutional review board approval. No identifiable patient information was collected as part of this noninterventional, cross-sectional study.

The T1D Exchange Multi-center COVID-19 Surveillance Study collected data from endocrinology clinics that completed a retrospective chart review and submitted information to T1D Exchange via an online questionnaire for all patients with T1D at their sites who tested positive for COVID-19.^13,14 The questionnaire was administered using the Qualtrics survey platform (www.qualtrics.com version XM) and contained 33 pre-coded and free-text response fields to collect patient and clinical attributes.

Each participating center identified 1 team member for reporting to avoid duplicate case submission. Each submitted case was reviewed for potential errors and incomplete information. The coordinating center verified the number of cases per site for data quality assurance.

Quantitative data were represented as mean (standard deviation) or median (interquartile range). Categorical data were described as the number (percentage) of patients. Summary statistics, including frequency and percentage for categorical variables, were calculated for all patient-related and clinical characteristics. The date August 1, 2021, was selected as the end of the first surge based on a review of national COVID-19 surges.

We used the Fisher’s exact test to assess associations between hospitalization and demographics, HbA1c, diabetes duration, symptoms, and adverse outcomes. In addition, multivariate logistic regression was used to calculate odds ratios (OR). Logistic regression models were used to determine the association between time of surge and hospitalization separately for both the pediatric and adult populations. Each model was adjusted for potential sociodemographic confounders, specifically age, sex, race, insurance, and HbA1c.

All tests were 2-sided, with type 1 error set at 5%. Fisher’s exact test and logistic regression were performed using statistical software R, version 3.6.2 (R Foundation for Statistical Computing).

Results

The characteristics of COVID-19 cases in patients with T1D that were reported early in the pandemic, before August 1, 2020 (first surge), compared with those of cases reported on and after August 1, 2020 (later surges) are shown in Table 1.

Patients with T1D who presented with COVID-19 during the first surge as compared to the later surges were older (mean age 28 [SD, 18.0] years vs 18.8 [SD, 11.1] years; P < .001) and had a longer duration of diabetes (P < .001). The first-surge group also had more patients with >20 years’ diabetes duration (20% vs 9%, P < .001). Obesity, hypertension, and chronic kidney disease were also more commonly reported in first-surge cases (all P < .001).

There was a significant difference in race and ethnicity reported in the first surge vs the later surge cases, with fewer patients identifying as non-Hispanic White (39% vs, 63%, P < .001) and more patients identifying as non-Hispanic Black (29% vs 12%, P < .001). The groups also differed significantly in terms of insurance type, with more people on public insurance in the first-surge group (57% vs 38%, P < .001). In addition, median HbA1c was higher (9.3% vs 8.4%, P < .001) and continuous glucose monitor and insulin pump use were less common (P = .02 and <.001, respectively) in the early surge.

All symptoms and adverse outcomes were reported more often in the first surge, including diabetic ketoacidosis (DKA; 32% vs 15%; P < .001) and severe hypoglycemia (4% vs 1%, P = .04). Hospitalization (52% vs 13%, P < .001) and ICU admission (24% vs 9%, P < .001) were reported more often in the first-surge group.

Regression Analyses

Table 2 shows the results of logistic regression analyses for hospitalization in the pediatric (≤19 years of age) and adult (>19 years of age) groups, along with the odds of hospitalization during the first vs late surge among COVID-positive people with T1D. Adult patients who tested positive in the first surge were about 5 times more likely to be hospitalized than adults who tested positive for infection in the late surge after adjusting for age, insurance type, sex, race, and HbA1c levels. Pediatric patients also had an increased odds for hospitalization during the first surge, but this increase was not statistically significant.

Discussion

Our analysis of COVID-19 cases in patients with T1D reported by diabetes providers across the United States found that adverse outcomes were more prevalent early in the pandemic. There may be a number of reasons for this difference in outcomes between patients who presented in the first surge vs a later surge. First, because testing for COVID-19 was extremely limited and reserved for hospitalized patients early in the pandemic, the first-surge patients with confirmed COVID-19 likely represent a skewed population of higher-acuity patients. This may also explain the relative paucity of cases in younger patients reported early in the pandemic. Second, worse outcomes in the early surge may also have been associated with overwhelmed hospitals in New York City at the start of the outbreak. According to Cummings et al, the abrupt surge of critically ill patients hospitalized with severe acute respiratory distress syndrome initially outpaced their capacity to provide prone-positioning ventilation, which has been expanded since then.¹⁵ While there was very little hypertension, cardiovascular disease, or kidney disease reported in the pediatric groups, there was a higher prevalence of obesity in the pediatric group from the mid-Atlantic region. Obesity has been associated with a worse prognosis for COVID-19 illness in children.¹⁶ Finally, there were 5 deaths reported in this study, all of which were reported during the first surge. Older age and increased rates of cardiovascular disease and chronic kidney disease in the first surge cases likely contributed to worse outcomes for adults in mid-Atlantic region relative to the other regions. Minority race and the use of public insurance, risk factors for more severe outcomes in all regions, were also more common in cases reported from the mid-Atlantic region.

This study has several limitations. First, it is a cross-sectional study that relies upon voluntary provider reports. Second, availability of COVID-19 testing was limited in all regions in spring 2020. Third, different regions of the country experienced subsequent surges at different times within the reported timeframes in this analysis. Fourth, this report time period does not include the impact of the newer COVID-19 variants. Finally, trends in COVID-19 outcomes were affected by the evolution of care that developed throughout 2020.

Conclusion

Adult patients with T1D and COVID-19 who reported during the first surge had about 5 times higher hospitalization odds than those who presented in a later surge.

Corresponding author: Osagie Ebekozien, MD, MPH, 11 Avenue de Lafayette, Boston, MA 02111; [email protected]

Disclosures: Dr Ebekozien reports receiving research grants from Medtronic Diabetes, Eli Lilly, and Dexcom, and receiving honoraria from Medtronic Diabetes.

From Hassenfeld Children’s Hospital at NYU Langone Health, New York, NY (Dr Gallagher), T1D Exchange, Boston, MA (Saketh Rompicherla; Drs Ebekozien, Noor, Odugbesan, and Mungmode; Nicole Rioles, Emma Ospelt), University of Mississippi School of Population Health, Jackson, MS (Dr. Ebekozien), Icahn School of Medicine at Mount Sinai, New York, NY (Drs. Wilkes, O’Malley, and Rapaport), Weill Cornell Medicine, New York, NY (Drs. Antal and Feuer), NYU Long Island School of Medicine, Mineola, NY (Dr. Gabriel), NYU Langone Health, New York, NY (Dr. Golden), Barbara Davis Center, Aurora, CO (Dr. Alonso), Texas Children’s Hospital/Baylor College of Medicine, Houston, TX (Dr. Lyons), Stanford University, Stanford, CA (Dr. Prahalad), Children Mercy Kansas City, MO (Dr. Clements), Indiana University School of Medicine, IN (Dr. Neyman), Rady Children’s Hospital, University of California, San Diego, CA (Dr. Demeterco-Berggren).

Background: Patient outcomes of COVID-19 have improved throughout the pandemic. However, because it is not known whether outcomes of COVID-19 in the type 1 diabetes (T1D) population improved over time, we investigated differences in COVID-19 outcomes for patients with T1D in the United States.

Methods: We analyzed data collected via a registry of patients with T1D and COVID-19 from 56 sites between April 2020 and January 2021. We grouped cases into first surge (April 9, 2020, to July 31, 2020, n = 188) and late surge (August 1, 2020, to January 31, 2021, n = 410), and then compared outcomes between both groups using descriptive statistics and logistic regression models.

Results: Adverse outcomes were more frequent during the first surge, including diabetic ketoacidosis (32% vs 15%, P < .001), severe hypoglycemia (4% vs 1%, P = .04), and hospitalization (52% vs 22%, P < .001). Patients in the first surge were older (28 [SD,18.8] years vs 18.0 [SD, 11.1] years, P < .001), had higher median hemoglobin A1c levels (9.3 [interquartile range {IQR}, 4.0] vs 8.4 (IQR, 2.8), P < .001), and were more likely to use public insurance (107 [57%] vs 154 [38%], P < .001). The odds of hospitalization for adults in the first surge were 5 times higher compared to the late surge (odds ratio, 5.01; 95% CI, 2.11-12.63).

Conclusion: Patients with T1D who presented with COVID-19 during the first surge had a higher proportion of adverse outcomes than those who presented in a later surge.

Keywords: TD1, diabetic ketoacidosis, hypoglycemia.

After the World Health Organization declared the disease caused by the novel coronavirus SARS-CoV-2, COVID-19, a pandemic on March 11, 2020, the Centers for Disease Control and Prevention identified patients with diabetes as high risk for severe illness.^1-7 The case-fatality rate for COVID-19 has significantly improved over the past 2 years. Public health measures, less severe COVID-19 variants, increased access to testing, and new treatments for COVID-19 have contributed to improved outcomes.

The T1D Exchange has previously published findings on COVID-19 outcomes for patients with type 1 diabetes (T1D) using data from the T1D COVID-19 Surveillance Registry.^8-12 Given improved outcomes in COVID-19 in the general population, we sought to determine if outcomes for cases of COVID-19 reported to this registry changed over time.

Methods

This study was coordinated by the T1D Exchange and approved as nonhuman subject research by the Western Institutional Review Board. All participating centers also obtained local institutional review board approval. No identifiable patient information was collected as part of this noninterventional, cross-sectional study.

The T1D Exchange Multi-center COVID-19 Surveillance Study collected data from endocrinology clinics that completed a retrospective chart review and submitted information to T1D Exchange via an online questionnaire for all patients with T1D at their sites who tested positive for COVID-19.^13,14 The questionnaire was administered using the Qualtrics survey platform (www.qualtrics.com version XM) and contained 33 pre-coded and free-text response fields to collect patient and clinical attributes.

Each participating center identified 1 team member for reporting to avoid duplicate case submission. Each submitted case was reviewed for potential errors and incomplete information. The coordinating center verified the number of cases per site for data quality assurance.

Quantitative data were represented as mean (standard deviation) or median (interquartile range). Categorical data were described as the number (percentage) of patients. Summary statistics, including frequency and percentage for categorical variables, were calculated for all patient-related and clinical characteristics. The date August 1, 2021, was selected as the end of the first surge based on a review of national COVID-19 surges.

We used the Fisher’s exact test to assess associations between hospitalization and demographics, HbA1c, diabetes duration, symptoms, and adverse outcomes. In addition, multivariate logistic regression was used to calculate odds ratios (OR). Logistic regression models were used to determine the association between time of surge and hospitalization separately for both the pediatric and adult populations. Each model was adjusted for potential sociodemographic confounders, specifically age, sex, race, insurance, and HbA1c.

All tests were 2-sided, with type 1 error set at 5%. Fisher’s exact test and logistic regression were performed using statistical software R, version 3.6.2 (R Foundation for Statistical Computing).

Results

The characteristics of COVID-19 cases in patients with T1D that were reported early in the pandemic, before August 1, 2020 (first surge), compared with those of cases reported on and after August 1, 2020 (later surges) are shown in Table 1.

Patients with T1D who presented with COVID-19 during the first surge as compared to the later surges were older (mean age 28 [SD, 18.0] years vs 18.8 [SD, 11.1] years; P < .001) and had a longer duration of diabetes (P < .001). The first-surge group also had more patients with >20 years’ diabetes duration (20% vs 9%, P < .001). Obesity, hypertension, and chronic kidney disease were also more commonly reported in first-surge cases (all P < .001).

There was a significant difference in race and ethnicity reported in the first surge vs the later surge cases, with fewer patients identifying as non-Hispanic White (39% vs, 63%, P < .001) and more patients identifying as non-Hispanic Black (29% vs 12%, P < .001). The groups also differed significantly in terms of insurance type, with more people on public insurance in the first-surge group (57% vs 38%, P < .001). In addition, median HbA1c was higher (9.3% vs 8.4%, P < .001) and continuous glucose monitor and insulin pump use were less common (P = .02 and <.001, respectively) in the early surge.

All symptoms and adverse outcomes were reported more often in the first surge, including diabetic ketoacidosis (DKA; 32% vs 15%; P < .001) and severe hypoglycemia (4% vs 1%, P = .04). Hospitalization (52% vs 13%, P < .001) and ICU admission (24% vs 9%, P < .001) were reported more often in the first-surge group.

Regression Analyses

Table 2 shows the results of logistic regression analyses for hospitalization in the pediatric (≤19 years of age) and adult (>19 years of age) groups, along with the odds of hospitalization during the first vs late surge among COVID-positive people with T1D. Adult patients who tested positive in the first surge were about 5 times more likely to be hospitalized than adults who tested positive for infection in the late surge after adjusting for age, insurance type, sex, race, and HbA1c levels. Pediatric patients also had an increased odds for hospitalization during the first surge, but this increase was not statistically significant.

Discussion

Our analysis of COVID-19 cases in patients with T1D reported by diabetes providers across the United States found that adverse outcomes were more prevalent early in the pandemic. There may be a number of reasons for this difference in outcomes between patients who presented in the first surge vs a later surge. First, because testing for COVID-19 was extremely limited and reserved for hospitalized patients early in the pandemic, the first-surge patients with confirmed COVID-19 likely represent a skewed population of higher-acuity patients. This may also explain the relative paucity of cases in younger patients reported early in the pandemic. Second, worse outcomes in the early surge may also have been associated with overwhelmed hospitals in New York City at the start of the outbreak. According to Cummings et al, the abrupt surge of critically ill patients hospitalized with severe acute respiratory distress syndrome initially outpaced their capacity to provide prone-positioning ventilation, which has been expanded since then.¹⁵ While there was very little hypertension, cardiovascular disease, or kidney disease reported in the pediatric groups, there was a higher prevalence of obesity in the pediatric group from the mid-Atlantic region. Obesity has been associated with a worse prognosis for COVID-19 illness in children.¹⁶ Finally, there were 5 deaths reported in this study, all of which were reported during the first surge. Older age and increased rates of cardiovascular disease and chronic kidney disease in the first surge cases likely contributed to worse outcomes for adults in mid-Atlantic region relative to the other regions. Minority race and the use of public insurance, risk factors for more severe outcomes in all regions, were also more common in cases reported from the mid-Atlantic region.

This study has several limitations. First, it is a cross-sectional study that relies upon voluntary provider reports. Second, availability of COVID-19 testing was limited in all regions in spring 2020. Third, different regions of the country experienced subsequent surges at different times within the reported timeframes in this analysis. Fourth, this report time period does not include the impact of the newer COVID-19 variants. Finally, trends in COVID-19 outcomes were affected by the evolution of care that developed throughout 2020.

Conclusion

Adult patients with T1D and COVID-19 who reported during the first surge had about 5 times higher hospitalization odds than those who presented in a later surge.

Corresponding author: Osagie Ebekozien, MD, MPH, 11 Avenue de Lafayette, Boston, MA 02111; [email protected]

Disclosures: Dr Ebekozien reports receiving research grants from Medtronic Diabetes, Eli Lilly, and Dexcom, and receiving honoraria from Medtronic Diabetes.

From the Department of Emergency Medicine, Santa Croce e Carle Hospital, Cuneo, Italy (Drs. Abram, Tosello, Emanuele Bernardi, Allione, Cavalot, Dutto, Corsini, Martini, Sciolla, Sara Bernardi, and Lauria). From the School of Emergency Medicine, University of Turin, Turin, Italy (Drs. Paglietta and Giamello).

Objective: This retrospective and prospective cohort study was designed to describe the characteristics, treatments, and outcomes of patients with SARS-CoV-2 infection (COVID-19) admitted to subintensive care units (SICU) and to identify the variables associated with outcomes. SICUs have been extremely stressed during the pandemic, but most data regarding critically ill COVID-19 patients come from intensive care units (ICUs). Studies about COVID-19 patients in SICUs are lacking.

Setting and participants: The study included 88 COVID-19 patients admitted to our SICU in Cuneo, Italy, between March and May 2020.

Measurements: Clinical and ventilatory data were collected, and patients were divided by outcome. Multivariable logistic regression analysis examined the variables associated with negative outcomes (transfer to the ICU, palliation, or death in a SICU).

Results: A total of 60 patients (68%) had a positive outcome, and 28 patients (32%) had a negative outcome; 69 patients (78%) underwent continuous positive airway pressure (CPAP). Pronation (n = 37 [42%]) had been more frequently adopted in patients who had a positive outcome vs a negative outcome (n = 30 [50%] vs n = 7 [25%]; P = .048), and the median (interquartile range) Pao₂/Fio₂ ratio after 6 hours of prone positioning was lower in patients who had a negative outcome vs a positive outcome (144 [140-168] vs 249 [195-268], P = .006). Independent predictors of a negative outcome were diabetes (odds ratio [OR], 8.22; 95% CI, 1.50-44.70; P = .015), higher D-dimer (OR, 1.28; 95% CI, 1.04-1.57; P = .019), higher lactate dehydrogenase level (OR, 1.003; 95% CI, 1.000-1.006; P = .039), and lower lymphocytes count (OR, 0.996; 95% CI, 0.993-0.999; P = .004).

Conclusion: SICUs have a fundamental role in the treatment of critically ill patients with COVID-19, who require long-term CPAP and pronation cycles. Diabetes, lymphopenia, and high D-dimer and LDH levels are associated with negative outcomes.

Keywords: emergency medicine, noninvasive ventilation, prone position, continuous positive airway pressure.

The COVID-19 pandemic has led to large increases in hospital admissions. Subintensive care units (SICUs) are among the wards most under pressure worldwide,¹ dealing with the increased number of critically ill patients who need noninvasive ventilation, as well as serving as the best alternative to overfilled intensive care units (ICUs). In Italy, SICUs are playing a fundamental role in the management of COVID-19 patients, providing early treatment of respiratory failure by continuous noninvasive ventilation in order to reduce the need for intubation.^2-5 Nevertheless, the great majority of available data about critically ill COVID-19 patients comes from ICUs. Full studies about outcomes of patients in SICUs are lacking and need to be conducted.

We sought to evaluate the characteristics and outcomes of patients admitted to our SICU for COVID-19 to describe the treatments they needed and their impact on prognosis, and to identify the variables associated with patient outcomes.

Methods

Study Design

This cohort study used data from patients who were admitted in the very first weeks of the pandemic. Data were collected retrospectively as well as prospectively, since the ethical committee approved our project. The quality and quantity of data in the 2 groups were comparable.

Data were collected from electronic and written medical records gathered during the patient’s entire stay in our SICU. Data were entered in a database with limited and controlled access. This study complied with the Declaration of Helsinki and was approved by the local ethics committees (ID: MEDURG10).

Study Population

We studied 88 consecutive patients admitted to the SICU of the Santa Croce e Carle Teaching Hospital, Cuneo, Italy, for COVID-19, from March 8 to May 1, 2020. The diagnosis was based on acute respiratory failure associated with SARS-CoV-2 RNA detection on nasopharyngeal swab or tracheal aspirate and/or typical COVID-19 features on a pulmonary computed tomography (CT) scan.⁶ Exclusion criteria were age younger than 18 years and patient denial of permission to use their data for research purposes (the great majority of patients could actively give consent; for patients who were too sick to do so, family members were asked whether they were aware of any reason why the patient would deny consent).

The past medical history and recent symptoms description were obtained by manually reviewing medical records. Epidemiological exposure was defined as contact with SARS-CoV-2–positive people or staying in an epidemic outbreak area. Initial vital parameters, venous blood tests, arterial blood gas analysis, chest x-ray, as well as the result of the nasopharyngeal swab were gathered from the emergency department (ED) examination. (Additional swabs could be requested when the first one was negative but clinical suspicion for COVID-19 was high.) Upon admission to the SICU, a standardized panel of blood tests was performed, which was repeated the next day and then every 48 hours. Arterial blood gas analysis was performed when clinically indicated, at least twice a day, or following a scheduled time in patients undergoing pronation. Charlson Comorbidity Index⁷ and MuLBSTA score⁸ were calculated based on the collected data.

Imaging

Chest ultrasonography was performed in the ED at the time of hospitalization and once a day in the SICU. Pulmonary high-resolution computed tomography (HRCT) was performed when clinically indicated or when the results of nasopharyngeal swabs and/or x-ray results were discordant with COVID-19 clinical suspicion. Contrast CT was performed when pulmonary embolism was suspected.

Medical Therapy

Hydroxychloroquine, antiviral agents, tocilizumab, and ruxolitinib were used in the early phase of the pandemic, then were dismissed after evidence of no efficacy.^9-11 Steroids and low-molecular-weight heparin were used afterward. Enoxaparin was used at the standard prophylactic dosage, and 70% of the anticoagulant dosage was also adopted in patients with moderate-to-severe COVID-19 and D-dimer values >3 times the normal value.^12-14 Antibiotics were given when a bacterial superinfection was suspected.

Oxygen and Ventilatory Therapy

Oxygen support or noninvasive ventilation were started based on patients’ respiratory efficacy, estimated by respiratory rate and the ratio of partial pressure of arterial oxygen and fraction of inspired oxygen (P/F ratio).^15,16 Oxygen support was delivered through nasal cannula, Venturi mask, or reservoir mask. Noninvasive ventilation was performed by continuous positive airway pressure (CPAP) when the P/F ratio was <250 or the respiratory rate was >25 breaths per minute, using the helmet interface.^5,17 Prone positioning during CPAP^18-20 was adopted in patients meeting the acute respiratory distress syndrome (ARDS) criteria²¹ and having persistence of respiratory distress and P/F <300 after a 1-hour trial of CPAP.

The prone position was maintained based on patient tolerance. P/F ratio was measured before pronation (T0), after 1 hour of prone position (T1), before resupination (T2), and 6 hours after resupination (T3). With the same timing, the patient was asked to rate their comfort in each position, from 0 (lack of comfort) to 10 (optimal comfort). Delta P/F was defined as the difference between P/F at T3 and basal P/F at T0.

Outcomes

Positive outcomes were defined as patient discharge from the SICU or transfer to a lower-intensity care ward for treatment continuation. Negative outcomes were defined as need for transfer to the ICU, transfer to another ward for palliation, or death in the SICU.

Statistical Analysis

Continuous data are reported as median and interquartile range (IQR); normal distribution of variables was tested using the Shapiro-Wilk test. Categorical variables were reported as absolute number and percentage. The Mann-Whitney test was used to compare continuous variables between groups, and chi-square test with continuity correction was used for categorical variables. The variables that were most significantly associated with a negative outcome on the univariate analysis were included in a stepwise logistic regression analysis, in order to identify independent predictors of patient outcome. Statistical analysis was performed using JASP (JASP Team) software.

Study Population

Of the 88 patients included in the study, 70% were male; the median age was 66 years (IQR, 60-77). In most patients, the diagnosis of COVID-19 was derived from a positive SARS-CoV-2 nasopharyngeal swab. Six patients, however, maintained a negative swab at all determinations but had clinical and imaging features strongly suggesting COVID-19. No patients met the exclusion criteria. Most patients came from the ED (n = 58 [66%]) or general wards (n = 22 [25%]), while few were transferred from the ICU (n = 8 [9%]). The median length of stay in the SICU was 4 days (IQR, 2-7). An epidemiological link to affected persons or a known virus exposure was identifiable in 37 patients (42%).

Clinical, Laboratory, and Imaging Data

The clinical and anthropometric characteristics of patients are shown in Table 1. Hypertension and smoking habits were prevalent in our population, and the median Charlson Comorbidity Index was 3. Most patients experienced fever, dyspnea, and cough during the days before hospitalization.

Laboratory data showed a marked inflammatory milieu in all studied patients, both at baseline and after 24 and 72 hours. Lymphopenia was observed, along with a significant increase of lactate dehydrogenase (LDH), C-reactive protein (CPR), and D-dimer, and a mild increase of procalcitonin. N-terminal pro-brain natriuretic peptide (NT-proBNP) values were also increased, with normal troponin I values (Table 2).

Medical Therapy

Most patients (89%) received hydroxychloroquine, whereas steroids were used in one-third of the population (36%). Immunomodulators (tocilizumab and ruxolitinib) were restricted to 12 patients (14%). Empirical antiviral therapy was introduced in the first 41 patients (47%). Enoxaparin was the default agent for thromboembolism prophylaxis, and 6 patients (7%) received 70% of the anticoagulating dose.

Oxygen and Ventilatory Therapy

Basal median P/F ratio was 253 (IQR, 218-291), and respiratory rate at triage was 20 breaths/min (IQR, 16-28), underlining a moderate-to-severe respiratory insufficiency at presentation. A total of 69 patients (78%) underwent CPAP, with a median positive end-expiratory pressure (PEEP) of 10.0 cm H₂O (IQR, 7.5-10.0) and fraction of inspired oxygen (Fio₂) of 0.40 (IQR, 0.40-0.50). In 37 patients (42%) who received ongoing CPAP, prone positioning was adopted. In this subgroup, respiratory rate was not significantly different from baseline to resupination (24 vs 25 breaths/min). The median P/F improved from 197 (IQR, 154-236) at baseline to 217 (IQR, 180-262) after pronation (the duration of the prone position was variable, depending on patients’ tolerance: 1 to 6 hours or every pronation cycle). The median delta P/F ratio was 39.4 (IQR, –17.0 to 78.0).

Outcomes

A total of 28 patients (32%) had a negative outcome in the SICU: 8 patients (9%) died, having no clinical indication for higher-intensity care; 6 patients (7%) were transferred to general wards for palliation; and 14 patients (16%) needed an upgrade of cure intensity and were transferred to the ICU. Of these 14 patients, 9 died in the ICU. The total in-hospital mortality of COVID-19 patients, including patients transferred from the SICU to general wards in fair condition, was 27% (n = 24). Clinical, laboratory, and therapeutic characteristics between the 2 groups are shown in Table 4.

Patients who had a negative outcome were significantly older and had more comorbidities, as suggested by a significantly higher prevalence of diabetes and higher Charlson Comorbidity scores (reflecting the mortality risk based on age and comorbidities). The median MuLBSTA score, which estimates the 90-day mortality risk from viral pneumonia, was also higher in patients who had a negative outcome (9.33%). Symptom occurrence was not different in patients with a negative outcome (apart from cough, which was less frequent), but these patients underwent hospitalization earlier—since the appearance of their first COVID-19 symptoms—compared to patients who had a positive outcome. No difference was found in antihypertensive therapy with angiotensin-converting enzyme inhibitors or angiotensin-receptor blockers among outcome groups.

More pronounced laboratory abnormalities were found in patients who had a negative outcome, compared to patients who had a positive outcome: lower lymphocytes and higher C-reactive protein (CRP), procalcitonin, D-dimer, LDH, and NT-proBNP. We found no differences in the radiological distribution of pulmonary involvement in patients who had negative or positive outcomes, nor in the adopted medical treatment.

Data showed no difference in CPAP implementation in the 2 groups. However, prone positioning had been more frequently adopted in the group of patients who had a positive outcome, compared with patients who had a negative outcome. No differences of basal P/F were found in patients who had a negative or positive outcome, but the median P/F after 6 hours of prone position was significantly lower in patients who had a negative outcome. The delta P/F ratio did not differ in the 2 groups of patients.

Multivariate Analysis

A logistic regression model was created, including the variables significantly associated with outcomes in the univariate analysis (age, sex, history of diabetes, lymphocytes, CRP, procalcitonin, LDH, NT-proBNP, and D-dimer). In the multivariate analysis, independent predictors of a negative outcome were history of diabetes (odds ratio [OR], 8.22; 95% CI, 1.50-44.70; P =.015), high D-dimer values (OR, 1.28; CI, 1.04-1.57; P = .019), high LDH values (OR, 1.003; CI, 1.000-1.006; P = .039), and low lymphocytes count (OR, 0.996; CI, 0.993-0.999; P = .004).

Discussion

Role of Subintensive Units and Mortality

The novelty of our report is its attempt to investigate the specific group of COVID-19 patients admitted to a SICU. In Italy, SICUs receive acutely ill, spontaneously breathing patients who need (invasive) hemodynamic monitoring, vasoactive medication, renal replacement therapy, chest- tube placement, thrombolysis, and respiratory noninvasive support. The nurse-to-patient ratio is higher than for general wards (usually 1 nurse to every 4 or 5 patients), though lower than for ICUs. In northern Italy, a great number of COVID-19 patients have required this kind of high-intensity care during the pandemic: Noninvasive ventilation support had to be maintained for several days, pronation maneuvers required a high number of people 2 or 3 times a day, and strict monitoring had to be assured. The SICU setting allows patients to buy time as a bridge to progressive reduction of pulmonary involvement, sometimes preventing the need for intubation.

The high prevalence of negative outcomes in the SICU underlines the complexity of COVID-19 patients in this setting. In fact, published data about mortality for patients with severe COVID-19 pneumonia are similar to ours.^22,23

Clinical, Laboratory, and Imaging Data

Our analysis confirmed a high rate of comorbidities in COVID-19 patients²⁴ and their prognostic role with age.^25,26 A marked inflammatory milieu was a negative prognostic indicator, and associated concomitant bacterial superinfection could have led to a worse prognosis (procalcitonin was associated with negative outcomes).²⁷ The cardiovascular system was nevertheless stressed, as suggested by higher values of NT-proBNP in patients with negative outcomes, which could reflect sepsis-related systemic involvement.²⁸

It is known that the pulmonary damage caused by SARS-CoV-2 has a dynamic radiological and clinical course, with early areas of subsegmental consolidation, and bilateral ground-glass opacities predominating later in the course of the disease.²⁹ This could explain why in our population we found no specific radiological pattern leading to a worse outcome.

Medical Therapy

No specific pharmacological therapy was found to be associated with a positive outcome in our study, just like antiviral and immunomodulator therapies failed to demonstrate effectiveness in subsequent pandemic surges. The low statistical power of our study did not allow us to give insight into the effectiveness of steroids and heparin at any dosage.

PEEP Support and Prone Positioning

Continuous positive airway pressure was initiated in the majority of patients and maintained for several days. This was an absolute novelty, because we rarely had to keep patients in helmets for long. This was feasible thanks to the SICU’s high nurse-to-patient ratio and the possibility of providing monitored sedation. Patients who could no longer tolerate CPAP helmets or did not improve with CPAP support were evaluated with anesthetists for programming further management. No initial data on respiratory rate, level of hypoxemia, or oxygen support need (level of PEEP and Fio₂) could discriminate between outcomes.

Prone positioning during CPAP was implemented in 42% of our study population: P/F ratio amelioration after prone positioning was highly variable, ranging from very good P/F ratio improvements to few responses or no response. No significantly greater delta P/F ratio was seen after the first prone positioning cycle in patients who had a positive outcome, probably due to the small size of our population, but we observed a clear positive trend. Interestingly, patients showing a negative outcome had a lower percentage of long-term responses to prone positioning: 6 hours after resupination, they lost the benefit of prone positioning in terms of P/F ratio amelioration. Similarly, a greater number of patients tolerating prone positioning had a positive outcome. These data give insight on the possible benefits of prone positioning in a noninvasively supported cohort of patients, which has been mentioned in previous studies.^30,31

Outcomes and Variables Associated With Negative Outcomes

After correction for age and sex, we found in multiple regression analysis that higher D-dimer and LDH values, lymphopenia, and history of diabetes were independently associated with a worse outcome. Although our results had low statistical significance, we consider the trend of the obtained odds ratios important from a clinical point of view. These results could lead to greater attention being placed on COVID-19 patients who present with these characteristics upon their arrival to the ED because they have increased risk of death or intensive care need. Clinicians should consider SICU admission for these patients in order to guarantee closer monitoring and possibly more aggressive ventilatory treatments, earlier pronation, or earlier transfer to the ICU.

Limitations

The major limitation to our study is undoubtedly its statistical power, due to its relatively low patient population. Particularly, the small number of patients who underwent pronation did not allow speculation about the efficacy of this technique, although preliminary data seem promising. However, ours is among the first studies regarding patients with COVID-19 admitted to a SICU, and these preliminary data truthfully describe the Italian, and perhaps international, experience with the first surge of the pandemic.

Conclusions

Our data highlight the primary role of the SICU in COVID-19 in adequately treating critically ill patients who have high care needs different from intubation, and who require noninvasive ventilation for prolonged times as well as frequent pronation cycles. This setting of care may represent a valid, reliable, and effective option for critically ill respiratory patients. History of diabetes, lymphopenia, and high D-dimer and LDH values are independently associated with negative outcomes, and patients presenting with these characteristics should be strictly monitored.

Acknowledgments: The authors thank the Informatica System S.R.L., as well as Allessando Mendolia for the pro bono creation of the ISCovidCollect data collecting app.

Corresponding author: Sara Abram, MD, via Coppino, 12100 Cuneo, Italy; [email protected].

Disclosures: None.

From the Department of Emergency Medicine, Santa Croce e Carle Hospital, Cuneo, Italy (Drs. Abram, Tosello, Emanuele Bernardi, Allione, Cavalot, Dutto, Corsini, Martini, Sciolla, Sara Bernardi, and Lauria). From the School of Emergency Medicine, University of Turin, Turin, Italy (Drs. Paglietta and Giamello).

Objective: This retrospective and prospective cohort study was designed to describe the characteristics, treatments, and outcomes of patients with SARS-CoV-2 infection (COVID-19) admitted to subintensive care units (SICU) and to identify the variables associated with outcomes. SICUs have been extremely stressed during the pandemic, but most data regarding critically ill COVID-19 patients come from intensive care units (ICUs). Studies about COVID-19 patients in SICUs are lacking.

Setting and participants: The study included 88 COVID-19 patients admitted to our SICU in Cuneo, Italy, between March and May 2020.

Measurements: Clinical and ventilatory data were collected, and patients were divided by outcome. Multivariable logistic regression analysis examined the variables associated with negative outcomes (transfer to the ICU, palliation, or death in a SICU).

Results: A total of 60 patients (68%) had a positive outcome, and 28 patients (32%) had a negative outcome; 69 patients (78%) underwent continuous positive airway pressure (CPAP). Pronation (n = 37 [42%]) had been more frequently adopted in patients who had a positive outcome vs a negative outcome (n = 30 [50%] vs n = 7 [25%]; P = .048), and the median (interquartile range) Pao₂/Fio₂ ratio after 6 hours of prone positioning was lower in patients who had a negative outcome vs a positive outcome (144 [140-168] vs 249 [195-268], P = .006). Independent predictors of a negative outcome were diabetes (odds ratio [OR], 8.22; 95% CI, 1.50-44.70; P = .015), higher D-dimer (OR, 1.28; 95% CI, 1.04-1.57; P = .019), higher lactate dehydrogenase level (OR, 1.003; 95% CI, 1.000-1.006; P = .039), and lower lymphocytes count (OR, 0.996; 95% CI, 0.993-0.999; P = .004).

Conclusion: SICUs have a fundamental role in the treatment of critically ill patients with COVID-19, who require long-term CPAP and pronation cycles. Diabetes, lymphopenia, and high D-dimer and LDH levels are associated with negative outcomes.

Keywords: emergency medicine, noninvasive ventilation, prone position, continuous positive airway pressure.

The COVID-19 pandemic has led to large increases in hospital admissions. Subintensive care units (SICUs) are among the wards most under pressure worldwide,¹ dealing with the increased number of critically ill patients who need noninvasive ventilation, as well as serving as the best alternative to overfilled intensive care units (ICUs). In Italy, SICUs are playing a fundamental role in the management of COVID-19 patients, providing early treatment of respiratory failure by continuous noninvasive ventilation in order to reduce the need for intubation.^2-5 Nevertheless, the great majority of available data about critically ill COVID-19 patients comes from ICUs. Full studies about outcomes of patients in SICUs are lacking and need to be conducted.

We sought to evaluate the characteristics and outcomes of patients admitted to our SICU for COVID-19 to describe the treatments they needed and their impact on prognosis, and to identify the variables associated with patient outcomes.

Methods

Study Design

This cohort study used data from patients who were admitted in the very first weeks of the pandemic. Data were collected retrospectively as well as prospectively, since the ethical committee approved our project. The quality and quantity of data in the 2 groups were comparable.

Data were collected from electronic and written medical records gathered during the patient’s entire stay in our SICU. Data were entered in a database with limited and controlled access. This study complied with the Declaration of Helsinki and was approved by the local ethics committees (ID: MEDURG10).

Study Population

We studied 88 consecutive patients admitted to the SICU of the Santa Croce e Carle Teaching Hospital, Cuneo, Italy, for COVID-19, from March 8 to May 1, 2020. The diagnosis was based on acute respiratory failure associated with SARS-CoV-2 RNA detection on nasopharyngeal swab or tracheal aspirate and/or typical COVID-19 features on a pulmonary computed tomography (CT) scan.⁶ Exclusion criteria were age younger than 18 years and patient denial of permission to use their data for research purposes (the great majority of patients could actively give consent; for patients who were too sick to do so, family members were asked whether they were aware of any reason why the patient would deny consent).

The past medical history and recent symptoms description were obtained by manually reviewing medical records. Epidemiological exposure was defined as contact with SARS-CoV-2–positive people or staying in an epidemic outbreak area. Initial vital parameters, venous blood tests, arterial blood gas analysis, chest x-ray, as well as the result of the nasopharyngeal swab were gathered from the emergency department (ED) examination. (Additional swabs could be requested when the first one was negative but clinical suspicion for COVID-19 was high.) Upon admission to the SICU, a standardized panel of blood tests was performed, which was repeated the next day and then every 48 hours. Arterial blood gas analysis was performed when clinically indicated, at least twice a day, or following a scheduled time in patients undergoing pronation. Charlson Comorbidity Index⁷ and MuLBSTA score⁸ were calculated based on the collected data.

Imaging

Chest ultrasonography was performed in the ED at the time of hospitalization and once a day in the SICU. Pulmonary high-resolution computed tomography (HRCT) was performed when clinically indicated or when the results of nasopharyngeal swabs and/or x-ray results were discordant with COVID-19 clinical suspicion. Contrast CT was performed when pulmonary embolism was suspected.

Medical Therapy

Hydroxychloroquine, antiviral agents, tocilizumab, and ruxolitinib were used in the early phase of the pandemic, then were dismissed after evidence of no efficacy.^9-11 Steroids and low-molecular-weight heparin were used afterward. Enoxaparin was used at the standard prophylactic dosage, and 70% of the anticoagulant dosage was also adopted in patients with moderate-to-severe COVID-19 and D-dimer values >3 times the normal value.^12-14 Antibiotics were given when a bacterial superinfection was suspected.

Oxygen and Ventilatory Therapy

Oxygen support or noninvasive ventilation were started based on patients’ respiratory efficacy, estimated by respiratory rate and the ratio of partial pressure of arterial oxygen and fraction of inspired oxygen (P/F ratio).^15,16 Oxygen support was delivered through nasal cannula, Venturi mask, or reservoir mask. Noninvasive ventilation was performed by continuous positive airway pressure (CPAP) when the P/F ratio was <250 or the respiratory rate was >25 breaths per minute, using the helmet interface.^5,17 Prone positioning during CPAP^18-20 was adopted in patients meeting the acute respiratory distress syndrome (ARDS) criteria²¹ and having persistence of respiratory distress and P/F <300 after a 1-hour trial of CPAP.

The prone position was maintained based on patient tolerance. P/F ratio was measured before pronation (T0), after 1 hour of prone position (T1), before resupination (T2), and 6 hours after resupination (T3). With the same timing, the patient was asked to rate their comfort in each position, from 0 (lack of comfort) to 10 (optimal comfort). Delta P/F was defined as the difference between P/F at T3 and basal P/F at T0.

Outcomes

Positive outcomes were defined as patient discharge from the SICU or transfer to a lower-intensity care ward for treatment continuation. Negative outcomes were defined as need for transfer to the ICU, transfer to another ward for palliation, or death in the SICU.

Statistical Analysis

Continuous data are reported as median and interquartile range (IQR); normal distribution of variables was tested using the Shapiro-Wilk test. Categorical variables were reported as absolute number and percentage. The Mann-Whitney test was used to compare continuous variables between groups, and chi-square test with continuity correction was used for categorical variables. The variables that were most significantly associated with a negative outcome on the univariate analysis were included in a stepwise logistic regression analysis, in order to identify independent predictors of patient outcome. Statistical analysis was performed using JASP (JASP Team) software.

Study Population

Of the 88 patients included in the study, 70% were male; the median age was 66 years (IQR, 60-77). In most patients, the diagnosis of COVID-19 was derived from a positive SARS-CoV-2 nasopharyngeal swab. Six patients, however, maintained a negative swab at all determinations but had clinical and imaging features strongly suggesting COVID-19. No patients met the exclusion criteria. Most patients came from the ED (n = 58 [66%]) or general wards (n = 22 [25%]), while few were transferred from the ICU (n = 8 [9%]). The median length of stay in the SICU was 4 days (IQR, 2-7). An epidemiological link to affected persons or a known virus exposure was identifiable in 37 patients (42%).

Clinical, Laboratory, and Imaging Data

The clinical and anthropometric characteristics of patients are shown in Table 1. Hypertension and smoking habits were prevalent in our population, and the median Charlson Comorbidity Index was 3. Most patients experienced fever, dyspnea, and cough during the days before hospitalization.

Laboratory data showed a marked inflammatory milieu in all studied patients, both at baseline and after 24 and 72 hours. Lymphopenia was observed, along with a significant increase of lactate dehydrogenase (LDH), C-reactive protein (CPR), and D-dimer, and a mild increase of procalcitonin. N-terminal pro-brain natriuretic peptide (NT-proBNP) values were also increased, with normal troponin I values (Table 2).

Medical Therapy

Most patients (89%) received hydroxychloroquine, whereas steroids were used in one-third of the population (36%). Immunomodulators (tocilizumab and ruxolitinib) were restricted to 12 patients (14%). Empirical antiviral therapy was introduced in the first 41 patients (47%). Enoxaparin was the default agent for thromboembolism prophylaxis, and 6 patients (7%) received 70% of the anticoagulating dose.

Oxygen and Ventilatory Therapy

Basal median P/F ratio was 253 (IQR, 218-291), and respiratory rate at triage was 20 breaths/min (IQR, 16-28), underlining a moderate-to-severe respiratory insufficiency at presentation. A total of 69 patients (78%) underwent CPAP, with a median positive end-expiratory pressure (PEEP) of 10.0 cm H₂O (IQR, 7.5-10.0) and fraction of inspired oxygen (Fio₂) of 0.40 (IQR, 0.40-0.50). In 37 patients (42%) who received ongoing CPAP, prone positioning was adopted. In this subgroup, respiratory rate was not significantly different from baseline to resupination (24 vs 25 breaths/min). The median P/F improved from 197 (IQR, 154-236) at baseline to 217 (IQR, 180-262) after pronation (the duration of the prone position was variable, depending on patients’ tolerance: 1 to 6 hours or every pronation cycle). The median delta P/F ratio was 39.4 (IQR, –17.0 to 78.0).

Outcomes

A total of 28 patients (32%) had a negative outcome in the SICU: 8 patients (9%) died, having no clinical indication for higher-intensity care; 6 patients (7%) were transferred to general wards for palliation; and 14 patients (16%) needed an upgrade of cure intensity and were transferred to the ICU. Of these 14 patients, 9 died in the ICU. The total in-hospital mortality of COVID-19 patients, including patients transferred from the SICU to general wards in fair condition, was 27% (n = 24). Clinical, laboratory, and therapeutic characteristics between the 2 groups are shown in Table 4.

Patients who had a negative outcome were significantly older and had more comorbidities, as suggested by a significantly higher prevalence of diabetes and higher Charlson Comorbidity scores (reflecting the mortality risk based on age and comorbidities). The median MuLBSTA score, which estimates the 90-day mortality risk from viral pneumonia, was also higher in patients who had a negative outcome (9.33%). Symptom occurrence was not different in patients with a negative outcome (apart from cough, which was less frequent), but these patients underwent hospitalization earlier—since the appearance of their first COVID-19 symptoms—compared to patients who had a positive outcome. No difference was found in antihypertensive therapy with angiotensin-converting enzyme inhibitors or angiotensin-receptor blockers among outcome groups.

More pronounced laboratory abnormalities were found in patients who had a negative outcome, compared to patients who had a positive outcome: lower lymphocytes and higher C-reactive protein (CRP), procalcitonin, D-dimer, LDH, and NT-proBNP. We found no differences in the radiological distribution of pulmonary involvement in patients who had negative or positive outcomes, nor in the adopted medical treatment.

Data showed no difference in CPAP implementation in the 2 groups. However, prone positioning had been more frequently adopted in the group of patients who had a positive outcome, compared with patients who had a negative outcome. No differences of basal P/F were found in patients who had a negative or positive outcome, but the median P/F after 6 hours of prone position was significantly lower in patients who had a negative outcome. The delta P/F ratio did not differ in the 2 groups of patients.

Multivariate Analysis

A logistic regression model was created, including the variables significantly associated with outcomes in the univariate analysis (age, sex, history of diabetes, lymphocytes, CRP, procalcitonin, LDH, NT-proBNP, and D-dimer). In the multivariate analysis, independent predictors of a negative outcome were history of diabetes (odds ratio [OR], 8.22; 95% CI, 1.50-44.70; P =.015), high D-dimer values (OR, 1.28; CI, 1.04-1.57; P = .019), high LDH values (OR, 1.003; CI, 1.000-1.006; P = .039), and low lymphocytes count (OR, 0.996; CI, 0.993-0.999; P = .004).

Discussion

Role of Subintensive Units and Mortality

The novelty of our report is its attempt to investigate the specific group of COVID-19 patients admitted to a SICU. In Italy, SICUs receive acutely ill, spontaneously breathing patients who need (invasive) hemodynamic monitoring, vasoactive medication, renal replacement therapy, chest- tube placement, thrombolysis, and respiratory noninvasive support. The nurse-to-patient ratio is higher than for general wards (usually 1 nurse to every 4 or 5 patients), though lower than for ICUs. In northern Italy, a great number of COVID-19 patients have required this kind of high-intensity care during the pandemic: Noninvasive ventilation support had to be maintained for several days, pronation maneuvers required a high number of people 2 or 3 times a day, and strict monitoring had to be assured. The SICU setting allows patients to buy time as a bridge to progressive reduction of pulmonary involvement, sometimes preventing the need for intubation.

The high prevalence of negative outcomes in the SICU underlines the complexity of COVID-19 patients in this setting. In fact, published data about mortality for patients with severe COVID-19 pneumonia are similar to ours.^22,23

Clinical, Laboratory, and Imaging Data

Our analysis confirmed a high rate of comorbidities in COVID-19 patients²⁴ and their prognostic role with age.^25,26 A marked inflammatory milieu was a negative prognostic indicator, and associated concomitant bacterial superinfection could have led to a worse prognosis (procalcitonin was associated with negative outcomes).²⁷ The cardiovascular system was nevertheless stressed, as suggested by higher values of NT-proBNP in patients with negative outcomes, which could reflect sepsis-related systemic involvement.²⁸

It is known that the pulmonary damage caused by SARS-CoV-2 has a dynamic radiological and clinical course, with early areas of subsegmental consolidation, and bilateral ground-glass opacities predominating later in the course of the disease.²⁹ This could explain why in our population we found no specific radiological pattern leading to a worse outcome.

Medical Therapy

No specific pharmacological therapy was found to be associated with a positive outcome in our study, just like antiviral and immunomodulator therapies failed to demonstrate effectiveness in subsequent pandemic surges. The low statistical power of our study did not allow us to give insight into the effectiveness of steroids and heparin at any dosage.

PEEP Support and Prone Positioning

Continuous positive airway pressure was initiated in the majority of patients and maintained for several days. This was an absolute novelty, because we rarely had to keep patients in helmets for long. This was feasible thanks to the SICU’s high nurse-to-patient ratio and the possibility of providing monitored sedation. Patients who could no longer tolerate CPAP helmets or did not improve with CPAP support were evaluated with anesthetists for programming further management. No initial data on respiratory rate, level of hypoxemia, or oxygen support need (level of PEEP and Fio₂) could discriminate between outcomes.

Prone positioning during CPAP was implemented in 42% of our study population: P/F ratio amelioration after prone positioning was highly variable, ranging from very good P/F ratio improvements to few responses or no response. No significantly greater delta P/F ratio was seen after the first prone positioning cycle in patients who had a positive outcome, probably due to the small size of our population, but we observed a clear positive trend. Interestingly, patients showing a negative outcome had a lower percentage of long-term responses to prone positioning: 6 hours after resupination, they lost the benefit of prone positioning in terms of P/F ratio amelioration. Similarly, a greater number of patients tolerating prone positioning had a positive outcome. These data give insight on the possible benefits of prone positioning in a noninvasively supported cohort of patients, which has been mentioned in previous studies.^30,31

Outcomes and Variables Associated With Negative Outcomes

After correction for age and sex, we found in multiple regression analysis that higher D-dimer and LDH values, lymphopenia, and history of diabetes were independently associated with a worse outcome. Although our results had low statistical significance, we consider the trend of the obtained odds ratios important from a clinical point of view. These results could lead to greater attention being placed on COVID-19 patients who present with these characteristics upon their arrival to the ED because they have increased risk of death or intensive care need. Clinicians should consider SICU admission for these patients in order to guarantee closer monitoring and possibly more aggressive ventilatory treatments, earlier pronation, or earlier transfer to the ICU.

Limitations

The major limitation to our study is undoubtedly its statistical power, due to its relatively low patient population. Particularly, the small number of patients who underwent pronation did not allow speculation about the efficacy of this technique, although preliminary data seem promising. However, ours is among the first studies regarding patients with COVID-19 admitted to a SICU, and these preliminary data truthfully describe the Italian, and perhaps international, experience with the first surge of the pandemic.

Conclusions

Our data highlight the primary role of the SICU in COVID-19 in adequately treating critically ill patients who have high care needs different from intubation, and who require noninvasive ventilation for prolonged times as well as frequent pronation cycles. This setting of care may represent a valid, reliable, and effective option for critically ill respiratory patients. History of diabetes, lymphopenia, and high D-dimer and LDH values are independently associated with negative outcomes, and patients presenting with these characteristics should be strictly monitored.

Acknowledgments: The authors thank the Informatica System S.R.L., as well as Allessando Mendolia for the pro bono creation of the ISCovidCollect data collecting app.

Corresponding author: Sara Abram, MD, via Coppino, 12100 Cuneo, Italy; [email protected].

Disclosures: None.

From the Department of Emergency Medicine, Santa Croce e Carle Hospital, Cuneo, Italy (Drs. Abram, Tosello, Emanuele Bernardi, Allione, Cavalot, Dutto, Corsini, Martini, Sciolla, Sara Bernardi, and Lauria). From the School of Emergency Medicine, University of Turin, Turin, Italy (Drs. Paglietta and Giamello).

Objective: This retrospective and prospective cohort study was designed to describe the characteristics, treatments, and outcomes of patients with SARS-CoV-2 infection (COVID-19) admitted to subintensive care units (SICU) and to identify the variables associated with outcomes. SICUs have been extremely stressed during the pandemic, but most data regarding critically ill COVID-19 patients come from intensive care units (ICUs). Studies about COVID-19 patients in SICUs are lacking.

Setting and participants: The study included 88 COVID-19 patients admitted to our SICU in Cuneo, Italy, between March and May 2020.

Measurements: Clinical and ventilatory data were collected, and patients were divided by outcome. Multivariable logistic regression analysis examined the variables associated with negative outcomes (transfer to the ICU, palliation, or death in a SICU).

Results: A total of 60 patients (68%) had a positive outcome, and 28 patients (32%) had a negative outcome; 69 patients (78%) underwent continuous positive airway pressure (CPAP). Pronation (n = 37 [42%]) had been more frequently adopted in patients who had a positive outcome vs a negative outcome (n = 30 [50%] vs n = 7 [25%]; P = .048), and the median (interquartile range) Pao₂/Fio₂ ratio after 6 hours of prone positioning was lower in patients who had a negative outcome vs a positive outcome (144 [140-168] vs 249 [195-268], P = .006). Independent predictors of a negative outcome were diabetes (odds ratio [OR], 8.22; 95% CI, 1.50-44.70; P = .015), higher D-dimer (OR, 1.28; 95% CI, 1.04-1.57; P = .019), higher lactate dehydrogenase level (OR, 1.003; 95% CI, 1.000-1.006; P = .039), and lower lymphocytes count (OR, 0.996; 95% CI, 0.993-0.999; P = .004).

Conclusion: SICUs have a fundamental role in the treatment of critically ill patients with COVID-19, who require long-term CPAP and pronation cycles. Diabetes, lymphopenia, and high D-dimer and LDH levels are associated with negative outcomes.

Keywords: emergency medicine, noninvasive ventilation, prone position, continuous positive airway pressure.

The COVID-19 pandemic has led to large increases in hospital admissions. Subintensive care units (SICUs) are among the wards most under pressure worldwide,¹ dealing with the increased number of critically ill patients who need noninvasive ventilation, as well as serving as the best alternative to overfilled intensive care units (ICUs). In Italy, SICUs are playing a fundamental role in the management of COVID-19 patients, providing early treatment of respiratory failure by continuous noninvasive ventilation in order to reduce the need for intubation.^2-5 Nevertheless, the great majority of available data about critically ill COVID-19 patients comes from ICUs. Full studies about outcomes of patients in SICUs are lacking and need to be conducted.

We sought to evaluate the characteristics and outcomes of patients admitted to our SICU for COVID-19 to describe the treatments they needed and their impact on prognosis, and to identify the variables associated with patient outcomes.

Methods

Study Design

This cohort study used data from patients who were admitted in the very first weeks of the pandemic. Data were collected retrospectively as well as prospectively, since the ethical committee approved our project. The quality and quantity of data in the 2 groups were comparable.

Data were collected from electronic and written medical records gathered during the patient’s entire stay in our SICU. Data were entered in a database with limited and controlled access. This study complied with the Declaration of Helsinki and was approved by the local ethics committees (ID: MEDURG10).

Study Population

We studied 88 consecutive patients admitted to the SICU of the Santa Croce e Carle Teaching Hospital, Cuneo, Italy, for COVID-19, from March 8 to May 1, 2020. The diagnosis was based on acute respiratory failure associated with SARS-CoV-2 RNA detection on nasopharyngeal swab or tracheal aspirate and/or typical COVID-19 features on a pulmonary computed tomography (CT) scan.⁶ Exclusion criteria were age younger than 18 years and patient denial of permission to use their data for research purposes (the great majority of patients could actively give consent; for patients who were too sick to do so, family members were asked whether they were aware of any reason why the patient would deny consent).

The past medical history and recent symptoms description were obtained by manually reviewing medical records. Epidemiological exposure was defined as contact with SARS-CoV-2–positive people or staying in an epidemic outbreak area. Initial vital parameters, venous blood tests, arterial blood gas analysis, chest x-ray, as well as the result of the nasopharyngeal swab were gathered from the emergency department (ED) examination. (Additional swabs could be requested when the first one was negative but clinical suspicion for COVID-19 was high.) Upon admission to the SICU, a standardized panel of blood tests was performed, which was repeated the next day and then every 48 hours. Arterial blood gas analysis was performed when clinically indicated, at least twice a day, or following a scheduled time in patients undergoing pronation. Charlson Comorbidity Index⁷ and MuLBSTA score⁸ were calculated based on the collected data.

Imaging

Chest ultrasonography was performed in the ED at the time of hospitalization and once a day in the SICU. Pulmonary high-resolution computed tomography (HRCT) was performed when clinically indicated or when the results of nasopharyngeal swabs and/or x-ray results were discordant with COVID-19 clinical suspicion. Contrast CT was performed when pulmonary embolism was suspected.

Medical Therapy

Hydroxychloroquine, antiviral agents, tocilizumab, and ruxolitinib were used in the early phase of the pandemic, then were dismissed after evidence of no efficacy.^9-11 Steroids and low-molecular-weight heparin were used afterward. Enoxaparin was used at the standard prophylactic dosage, and 70% of the anticoagulant dosage was also adopted in patients with moderate-to-severe COVID-19 and D-dimer values >3 times the normal value.^12-14 Antibiotics were given when a bacterial superinfection was suspected.

Oxygen and Ventilatory Therapy

Oxygen support or noninvasive ventilation were started based on patients’ respiratory efficacy, estimated by respiratory rate and the ratio of partial pressure of arterial oxygen and fraction of inspired oxygen (P/F ratio).^15,16 Oxygen support was delivered through nasal cannula, Venturi mask, or reservoir mask. Noninvasive ventilation was performed by continuous positive airway pressure (CPAP) when the P/F ratio was <250 or the respiratory rate was >25 breaths per minute, using the helmet interface.^5,17 Prone positioning during CPAP^18-20 was adopted in patients meeting the acute respiratory distress syndrome (ARDS) criteria²¹ and having persistence of respiratory distress and P/F <300 after a 1-hour trial of CPAP.

The prone position was maintained based on patient tolerance. P/F ratio was measured before pronation (T0), after 1 hour of prone position (T1), before resupination (T2), and 6 hours after resupination (T3). With the same timing, the patient was asked to rate their comfort in each position, from 0 (lack of comfort) to 10 (optimal comfort). Delta P/F was defined as the difference between P/F at T3 and basal P/F at T0.

Outcomes

Positive outcomes were defined as patient discharge from the SICU or transfer to a lower-intensity care ward for treatment continuation. Negative outcomes were defined as need for transfer to the ICU, transfer to another ward for palliation, or death in the SICU.

Statistical Analysis

Continuous data are reported as median and interquartile range (IQR); normal distribution of variables was tested using the Shapiro-Wilk test. Categorical variables were reported as absolute number and percentage. The Mann-Whitney test was used to compare continuous variables between groups, and chi-square test with continuity correction was used for categorical variables. The variables that were most significantly associated with a negative outcome on the univariate analysis were included in a stepwise logistic regression analysis, in order to identify independent predictors of patient outcome. Statistical analysis was performed using JASP (JASP Team) software.

Study Population

Of the 88 patients included in the study, 70% were male; the median age was 66 years (IQR, 60-77). In most patients, the diagnosis of COVID-19 was derived from a positive SARS-CoV-2 nasopharyngeal swab. Six patients, however, maintained a negative swab at all determinations but had clinical and imaging features strongly suggesting COVID-19. No patients met the exclusion criteria. Most patients came from the ED (n = 58 [66%]) or general wards (n = 22 [25%]), while few were transferred from the ICU (n = 8 [9%]). The median length of stay in the SICU was 4 days (IQR, 2-7). An epidemiological link to affected persons or a known virus exposure was identifiable in 37 patients (42%).

Clinical, Laboratory, and Imaging Data

The clinical and anthropometric characteristics of patients are shown in Table 1. Hypertension and smoking habits were prevalent in our population, and the median Charlson Comorbidity Index was 3. Most patients experienced fever, dyspnea, and cough during the days before hospitalization.

Laboratory data showed a marked inflammatory milieu in all studied patients, both at baseline and after 24 and 72 hours. Lymphopenia was observed, along with a significant increase of lactate dehydrogenase (LDH), C-reactive protein (CPR), and D-dimer, and a mild increase of procalcitonin. N-terminal pro-brain natriuretic peptide (NT-proBNP) values were also increased, with normal troponin I values (Table 2).

Medical Therapy

Most patients (89%) received hydroxychloroquine, whereas steroids were used in one-third of the population (36%). Immunomodulators (tocilizumab and ruxolitinib) were restricted to 12 patients (14%). Empirical antiviral therapy was introduced in the first 41 patients (47%). Enoxaparin was the default agent for thromboembolism prophylaxis, and 6 patients (7%) received 70% of the anticoagulating dose.

Oxygen and Ventilatory Therapy

Basal median P/F ratio was 253 (IQR, 218-291), and respiratory rate at triage was 20 breaths/min (IQR, 16-28), underlining a moderate-to-severe respiratory insufficiency at presentation. A total of 69 patients (78%) underwent CPAP, with a median positive end-expiratory pressure (PEEP) of 10.0 cm H₂O (IQR, 7.5-10.0) and fraction of inspired oxygen (Fio₂) of 0.40 (IQR, 0.40-0.50). In 37 patients (42%) who received ongoing CPAP, prone positioning was adopted. In this subgroup, respiratory rate was not significantly different from baseline to resupination (24 vs 25 breaths/min). The median P/F improved from 197 (IQR, 154-236) at baseline to 217 (IQR, 180-262) after pronation (the duration of the prone position was variable, depending on patients’ tolerance: 1 to 6 hours or every pronation cycle). The median delta P/F ratio was 39.4 (IQR, –17.0 to 78.0).

Outcomes

A total of 28 patients (32%) had a negative outcome in the SICU: 8 patients (9%) died, having no clinical indication for higher-intensity care; 6 patients (7%) were transferred to general wards for palliation; and 14 patients (16%) needed an upgrade of cure intensity and were transferred to the ICU. Of these 14 patients, 9 died in the ICU. The total in-hospital mortality of COVID-19 patients, including patients transferred from the SICU to general wards in fair condition, was 27% (n = 24). Clinical, laboratory, and therapeutic characteristics between the 2 groups are shown in Table 4.

Patients who had a negative outcome were significantly older and had more comorbidities, as suggested by a significantly higher prevalence of diabetes and higher Charlson Comorbidity scores (reflecting the mortality risk based on age and comorbidities). The median MuLBSTA score, which estimates the 90-day mortality risk from viral pneumonia, was also higher in patients who had a negative outcome (9.33%). Symptom occurrence was not different in patients with a negative outcome (apart from cough, which was less frequent), but these patients underwent hospitalization earlier—since the appearance of their first COVID-19 symptoms—compared to patients who had a positive outcome. No difference was found in antihypertensive therapy with angiotensin-converting enzyme inhibitors or angiotensin-receptor blockers among outcome groups.

More pronounced laboratory abnormalities were found in patients who had a negative outcome, compared to patients who had a positive outcome: lower lymphocytes and higher C-reactive protein (CRP), procalcitonin, D-dimer, LDH, and NT-proBNP. We found no differences in the radiological distribution of pulmonary involvement in patients who had negative or positive outcomes, nor in the adopted medical treatment.

Data showed no difference in CPAP implementation in the 2 groups. However, prone positioning had been more frequently adopted in the group of patients who had a positive outcome, compared with patients who had a negative outcome. No differences of basal P/F were found in patients who had a negative or positive outcome, but the median P/F after 6 hours of prone position was significantly lower in patients who had a negative outcome. The delta P/F ratio did not differ in the 2 groups of patients.

Multivariate Analysis

A logistic regression model was created, including the variables significantly associated with outcomes in the univariate analysis (age, sex, history of diabetes, lymphocytes, CRP, procalcitonin, LDH, NT-proBNP, and D-dimer). In the multivariate analysis, independent predictors of a negative outcome were history of diabetes (odds ratio [OR], 8.22; 95% CI, 1.50-44.70; P =.015), high D-dimer values (OR, 1.28; CI, 1.04-1.57; P = .019), high LDH values (OR, 1.003; CI, 1.000-1.006; P = .039), and low lymphocytes count (OR, 0.996; CI, 0.993-0.999; P = .004).

Discussion

Role of Subintensive Units and Mortality

The novelty of our report is its attempt to investigate the specific group of COVID-19 patients admitted to a SICU. In Italy, SICUs receive acutely ill, spontaneously breathing patients who need (invasive) hemodynamic monitoring, vasoactive medication, renal replacement therapy, chest- tube placement, thrombolysis, and respiratory noninvasive support. The nurse-to-patient ratio is higher than for general wards (usually 1 nurse to every 4 or 5 patients), though lower than for ICUs. In northern Italy, a great number of COVID-19 patients have required this kind of high-intensity care during the pandemic: Noninvasive ventilation support had to be maintained for several days, pronation maneuvers required a high number of people 2 or 3 times a day, and strict monitoring had to be assured. The SICU setting allows patients to buy time as a bridge to progressive reduction of pulmonary involvement, sometimes preventing the need for intubation.

The high prevalence of negative outcomes in the SICU underlines the complexity of COVID-19 patients in this setting. In fact, published data about mortality for patients with severe COVID-19 pneumonia are similar to ours.^22,23

Clinical, Laboratory, and Imaging Data

Our analysis confirmed a high rate of comorbidities in COVID-19 patients²⁴ and their prognostic role with age.^25,26 A marked inflammatory milieu was a negative prognostic indicator, and associated concomitant bacterial superinfection could have led to a worse prognosis (procalcitonin was associated with negative outcomes).²⁷ The cardiovascular system was nevertheless stressed, as suggested by higher values of NT-proBNP in patients with negative outcomes, which could reflect sepsis-related systemic involvement.²⁸

It is known that the pulmonary damage caused by SARS-CoV-2 has a dynamic radiological and clinical course, with early areas of subsegmental consolidation, and bilateral ground-glass opacities predominating later in the course of the disease.²⁹ This could explain why in our population we found no specific radiological pattern leading to a worse outcome.

Medical Therapy

No specific pharmacological therapy was found to be associated with a positive outcome in our study, just like antiviral and immunomodulator therapies failed to demonstrate effectiveness in subsequent pandemic surges. The low statistical power of our study did not allow us to give insight into the effectiveness of steroids and heparin at any dosage.

PEEP Support and Prone Positioning

Continuous positive airway pressure was initiated in the majority of patients and maintained for several days. This was an absolute novelty, because we rarely had to keep patients in helmets for long. This was feasible thanks to the SICU’s high nurse-to-patient ratio and the possibility of providing monitored sedation. Patients who could no longer tolerate CPAP helmets or did not improve with CPAP support were evaluated with anesthetists for programming further management. No initial data on respiratory rate, level of hypoxemia, or oxygen support need (level of PEEP and Fio₂) could discriminate between outcomes.

Prone positioning during CPAP was implemented in 42% of our study population: P/F ratio amelioration after prone positioning was highly variable, ranging from very good P/F ratio improvements to few responses or no response. No significantly greater delta P/F ratio was seen after the first prone positioning cycle in patients who had a positive outcome, probably due to the small size of our population, but we observed a clear positive trend. Interestingly, patients showing a negative outcome had a lower percentage of long-term responses to prone positioning: 6 hours after resupination, they lost the benefit of prone positioning in terms of P/F ratio amelioration. Similarly, a greater number of patients tolerating prone positioning had a positive outcome. These data give insight on the possible benefits of prone positioning in a noninvasively supported cohort of patients, which has been mentioned in previous studies.^30,31

Outcomes and Variables Associated With Negative Outcomes

After correction for age and sex, we found in multiple regression analysis that higher D-dimer and LDH values, lymphopenia, and history of diabetes were independently associated with a worse outcome. Although our results had low statistical significance, we consider the trend of the obtained odds ratios important from a clinical point of view. These results could lead to greater attention being placed on COVID-19 patients who present with these characteristics upon their arrival to the ED because they have increased risk of death or intensive care need. Clinicians should consider SICU admission for these patients in order to guarantee closer monitoring and possibly more aggressive ventilatory treatments, earlier pronation, or earlier transfer to the ICU.

Limitations

The major limitation to our study is undoubtedly its statistical power, due to its relatively low patient population. Particularly, the small number of patients who underwent pronation did not allow speculation about the efficacy of this technique, although preliminary data seem promising. However, ours is among the first studies regarding patients with COVID-19 admitted to a SICU, and these preliminary data truthfully describe the Italian, and perhaps international, experience with the first surge of the pandemic.

Conclusions

Our data highlight the primary role of the SICU in COVID-19 in adequately treating critically ill patients who have high care needs different from intubation, and who require noninvasive ventilation for prolonged times as well as frequent pronation cycles. This setting of care may represent a valid, reliable, and effective option for critically ill respiratory patients. History of diabetes, lymphopenia, and high D-dimer and LDH values are independently associated with negative outcomes, and patients presenting with these characteristics should be strictly monitored.

Acknowledgments: The authors thank the Informatica System S.R.L., as well as Allessando Mendolia for the pro bono creation of the ISCovidCollect data collecting app.

Corresponding author: Sara Abram, MD, via Coppino, 12100 Cuneo, Italy; [email protected].

Disclosures: None.

From the Department of Medicine (Drs. Meisenberg, Muganlinskaya, Sharma, Amjadi, Arnold, Barnes, Clance, Khalil, Miller, Mooradian, O’Connell, Patel, Press, Samaras, Shanmugam, Tavadze, and Thompson), Department of Pharmacy (Drs. Jiang, Jarawan, Sheth, and Trinh), Department of Nursing (Dr. Ohnmacht), and Department of Women and Children’s Services (Dr. Raji), Luminis Health, Annapolis, MD, and Lanham, MD.

Objective: The COVID-19 pandemic has been a challenge for hospital medical staffs worldwide due to high volumes of patients acutely ill with novel syndromes and prevailing uncertainty regarding optimum supportive and therapeutic interventions. Additionally, the response to this crisis was driven by a plethora of nontraditional information sources, such as email chains, websites, non–peer-reviewed preprints, and press releases. Care patterns became idiosyncratic and often incorporated unproven interventions driven by these nontraditional information sources. This report evaluates the efforts of a health system to create and empower a multidisciplinary committee to develop, implement, and monitor evidence-based, standardized protocols for patients with COVID-19.

Methods: This report describes the composition of the committee, its scope, and its important interactions with the health system pharmacy and therapeutics committee, research teams, and other work groups planning other aspects of COVID-19 management. It illustrates how the committee was used to demonstrate for trainees the process and value of critically examining evidence, even in a chaotic environment.

Results: Data show successful interventions in reducing excessive ordering of certain laboratory tests, reduction of nonrecommended therapies, and rapid uptake of evidence-based or guidelines-supported interventions.

Conclusions: A multidisciplinary committee dedicated solely to planning, implementing, and monitoring standard approaches that eventually became evidence-based decision-making led to an improved focus on treatment options and outcomes for COVID-19 patients. Data presented illustrate the attainable success that is both adaptable and suitable for similar emergencies in the future.

Keywords: COVID-19; clinical management; pharmacy and therapeutics; treatment; therapy.

The COVID-19 pandemic has spread to nearly all countries, carrying with it high morbidity, mortality, and severe impacts on both well-developed and less-well-developed health systems. Media reports of chaos within overwhelmed hospitals have been prominent.^1,2 As of January 5, 2022, SARS-CoV-2 has infected more than 295 million people globally and directly caused the death of more than 5.4 million,³ though this number is likely an undercount even in countries with well-developed mortality tracking.⁴

Throughout the COVID-19 pandemic, hospital-based medical teams have been confronted with a flood of severely ill patients with novel syndromes. Initially, there were no standards for therapy or supportive care except for treatments borrowed from similar syndromes. In the setting of high volumes, high acuity, and public dismay, it is unsurprising that the usual deliberative methods for weighing evidence and initiating interventions were often pushed aside in favor of the solace of active intervention.⁵ In this milieu of limited evidence, there was a lamentable, if understandable, tendency to seek guidance from “nontraditional” sources,⁶ including email chains from colleagues, hospital websites, non–peer-reviewed manuscripts, advanced publication by medical journals,⁷ and nonscientific media presentations. In many localities, practitioners responded in idiosyncratic ways. For example, findings of high cytokine levels in COVID-19,⁸ along with reports of in-vitro antiviral activity with drugs like hydroxychloroquine against both SARS⁹ and SARS-CoV-2,¹⁰ drove laboratory test ordering and therapeutic interventions, respectively, carving shortcuts into the traditional clinical trial–dependent standards. Clinical trial results eventually emerged.¹¹COVID-19 created a clinical dilemma for hospital medical staffs in terms of how to organize, standardize, and rapidly adapt to a flood of new information. In this report, we describe how 1 health system responded to these challenges by forming a COVID-19 Clinical Management Committee (CCMC) and empowering this interdisciplinary team to review evidence, create and adjust order sets, educate practitioners, oversee care, and collaborate across teams addressing other aspects of the COVID-19 response.

Program Overview

Health System Description

Luminis Health is a health system with 2 acute care hospitals that was formed in 2019 just before the start of the pandemic. Anne Arundel Medical Center (hospital A) is a 385-bed teaching hospital in Annapolis, MD. It has more than 23 000 discharges annually. Patients with COVID-19 were cared for by either an internal medicine teaching service or nonteaching hospitalist services on cohorted nursing units. Doctor’s Community Medical Center, in Lanham, MD (hospital B), is a 206-bed acute care hospital with more than 10 350 annual discharges. COVID-19 patients were cared for by hospitalist groups, initially in noncohorted units with transition to cohorted nursing units after a few months. The medical staffs are generally distinct, with different leadership structures, though the Luminis Health Department of Medicine has oversight responsibilities at both hospitals. More than 47 physicians attended COVID-19 patients at hospital A (with medical residents) and 30 individual physicians at hospital B, respectively, including intensivists. The nursing and pharmacy staffs are distinct, but there is a shared oversight Pharmacy and Therapeutics (P&T) Committee.

The 2 hospitals had distinct electronic medical records (EMR) until January 2021, when hospital B adopted the same EMR as hospital A (Epic).

Mission and Formation of CCMC

In order to coordinate the therapeutic approach across the health system, it was important for the CCMC to be designated by the health system P&T committee as an official subcommittee so that decisions on restrictions of medications and/or new or revised order sets could be rapidly initiated across the system without waiting for the subsequent P&T meetings. The full committee retained oversight of the CCMC. Some P&T members were also on the CCMC.

The committee reviewed new reports in medical journals and prepublication servers and consulted recommendations of professional societies, such as the National Institutes of Health (NIH) COVID-19 guidelines, Infectious Diseases Society of America, Society of Critical Care Medicine, and US Food and Drug Administration (FDA) Emergency Use Authorizations (EUA), among other sources.

Composition of the CCMC

Physician leaders from both hospitals in the following specialties were solicited for participation: critical care, epidemiology, hospital medicine (internal medicine), emergency medicine, infectious diseases, nephrology, women and children’s services, and medical informatics. Specialists in other areas, such as hematology, were invited for topic-specific discussions. Hospital pharmacists with different specialties and nursing leadership were essential contributors. The committee members were expected to use various communication channels to inform frontline clinicians of new care standards and the existence of new order sets, which were embedded in the EMR.

Clinical Research

An important connection for the CCMC was with theCOVID-19 clinical research team. Three members of the research team were also members of the CCMC. All new study proposals for therapeutics were discussed with the CCMC as they were being considered by the research team. In this way, feedback on the feasibility and acceptance of new study opportunities could be discussed with the CCMC. Occasionally, CCMC decisions impacted clinical research accrual strategies. For example, new data from randomized trials about tocilizumab^1,2 demonstrated benefits in some subsets of patients and resulted in a recommendation for use by the NIH guideline committee in these populations.¹ The CCMC quickly adopted this recommendation, which required a reprioritization of clinical research enrollment for studies testing other immune-modulating agents. This important dialogue was mediated within the CCMC.

Guideline Distribution, Reinforcement, and Platform for Feedback

New guidelines were disseminated to clinicians via daily brief patient huddles held on COVID units, with participation by nursing and pharmacy, and by weekly meetings with hospitalist leaders and frontline hospital physicians. Order sets and guidelines were maintained on the intranet. Adherence was reinforced by unit-based and central pharmacists. Order sets, including admission order sets, could be created only by designated informatics personnel, thus enforcing standardization. Feedback on the utility of the order sets was obtained during the weekly meetings or huddles, as described above. To ensure a sense of transparency, physicians who had interest in commenting on a particular therapy, or who wished to discuss a particular manuscript, news article, or website, were invited to attend CCMC meetings.

Scope of CCMC

In order to be effective and timely, we limited the scope of our work to the report to the inpatient therapeutic environment, allowing other committees to work on other aspects of the pandemic response. In addition to issuing guidance and creating order sets to direct clinical practice, the CCMC also monitored COVID-19 therapeutic shortages^15,16 and advised on prioritization of such treatments as convalescent plasma, remdesivir (prioritization and duration of therapy, 5 vs 10 days), baricitinib, and tocilizumab, depending upon the location of the patient (critical care or not). The CCMC was not involved in the management of non–COVID-19 shortages brought about by supply chain deficiencies.

Table 1 shows some aspects of the health system pandemic-response planning and the committee workforce that undertook that work. Though many items were out of scope for the CCMC, members of the CCMC did participate in the planning work of these other committees and therefore stayed connected to this complementary work.

A Teaching Opportunity About Making Thoughtful Choices

Another important feature of the CCMC was the contributions of residents from both pharmacy and internal medicine. The purpose and operations of the committee were recognized as an opportunity to involve learners in a curriculum based on Kern’s 6-step approach.¹⁷ Though the problem identification and general needs assessment were easily defined, the targeted needs assessment, extracted from individual and group interviews with learners and the committee members, pointed at the need to learn how to assess and analyze a rapidly growing body of literature on several relevant clinical aspects of SARS-CoV-2 and COVID-19. To achieve goals and objectives, residents were assigned to present current literature on a particular intervention during a committee meeting, specifically commenting on the merit or deficiencies of the study design, the strength of the data, and applicability to the local context with a recommendation. Prior to the presentations, the residents worked with faculty to identify the best studies or systematic analyses with potential to alter current practices. We thus used the CCMC process as a teaching tool about evidence-based medicine and the dilemma of clinical equipoise. This was imperative, since trainees thrust into the COVID-19 response have often keenly observed a movement away from deliberative decision-making.¹⁸ Indeed, including residents in the process of deliberative responses to COVID-19 addresses a recent call to adjust medical education during COVID-19 to “adapt curriculum to current issues in real time.”¹⁹

Interventions and Therapies Considered

Table 2 shows the topics reviewed by the CCMC. By the time of the first meeting, nonstandardization of care was already a source of concern for clinicians. Dialogue often continued outside of the formal meetings. Many topics were considered more than once as new guidance developed, changes to EUAs occurred, and new data or new publicity arose.

Methods

The Human Protections Administrator determined that this work constituted “quality improvement, and not research” and was therefore exempt from institutional review board review.

Quantitative Analysis

All admitted patients from March 10, 2020, through April 20, 2021, were considered in the quantitative aspects of this report except as noted. Patients diagnosed with COVID-19 were identified by searching our internal data base using diagnostic codes. Patient admissions with the following diagnostic codes were included (prior to April 1, 2020): J12.89, J20.8, J40, J22, J98.8, J80, each with the additional code of B97.29. After April 1, 2020, the guideline for coding COVID-19 was U07.1.

Descriptive statistics were used to measure utilization rates of certain medications and laboratory tests of interest over time. These data were adjusted for number of unique admissions. In a few cases, not all data elements were available from both hospitals due to differences in the EMR.

Case fatality rate was calculated based upon whether the patient died or was admitted to inpatient hospice as a result of COVID-19. Four patients transferred out of hospital A and 18 transferred out of hospital B were censored from case-fatality-rate determination.

Figure 1 shows the number of admissions for each acute care hospital in the health system and the combined COVID-19 case-fatality rate over time.

Results

A total of 5955 consecutive COVID-19 patients admitted from March 10, 2020, through April 30, 2021, were analyzed. Patients with International Statistical Classification of Diseases, Tenth Revision codes J12.89. J20.8, J40, J22, J98.8, J80, each with the additional code of B97.29 (or the code UO7.1 after April 1, 2020), were included in the analysis. The median age of admitted patients was 65 years (range 19-91 years). Using the NIH classification system for severity,²⁰ the distribution of severity during the first 24 hours after the time of hospital admission was as follows: asymptomatic/presymptomatic, 0.5%; mild illness, 5.3%; moderate illness, 37.1%; severe illness, 55.5%; and critical illness, 1.1%.

The impact of the CCMC can be estimated by looking at care patterns over time. Since the work of the CCMC was aimed at influencing and standardizing physician ordering and therapy choices through order set creation and other forms of oversight, we measured the use of the CCMC-approved order sets at both hospitals and the use of certain laboratory tests and therapies that the CCMC sought either to limit or increase. These counts were adjusted for number of unique COVID-19 admissions. But the limits of the case collection tool meant it also collected cases that were not eligible for some of the interventions. For example, COVID-19 admissions without hypoxemia would not have been eligible for remdesivir or glucocorticoids. When admitted, some patients were already on steroids for other medical indications and did not receive the prescribed dexamethasone dose that we measured in pharmacy databases. Similarly, a few patients were hospitalized for indications unrelated to COVID-19, such as surgery or childbirth, and were found to be SARS-CoV-2-positive on routine screening.

Figure 2 shows the utilization of CCMC-approved standard COVID-19 admission order sets as a proportion of all COVID-19 admissions over time. The trend reveals a modest increase in usage (R² = 0.34), but these data do not reflect the progressive build of content into order sets over time. One of the goals of the order sets was to standardize and reduce the ordering of certain biomarkers: C-reactive protein, serum ferritin, and D-dimer, which were ordered frequently in many early patients. Orders for these 3 laboratory tests are combined and expressed as an average number of labs per COVID-19 admission in Figure 2. A downward trend, with an R² value of 0.65, is suggestive of impact from the order sets, though other explanations are possible.

Medication guidance was also a goal of the CCMC, simultaneously discouraging poorly supported interventions and driving uptake of the recommended evidence-based interventions in appropriate patients. Figure 3 shows the utilization pattern for some drugs of interest over the course of the pandemic, specifically the proportion of patients receiving at least 1 dose of medication among all COVID-19 admissions by month. (Data for hospital B was excluded from this analysis because it did not include all admitted patients.)

Hydroxychloroquine, which enjoyed a wave of popularity early on during the pandemic, was a target of successful order stewardship through the CCMC. Use of hydroxychloroquine as a COVID-19 therapeutic option after the first 2 months of the pandemic stopped, and subsequent use at low levels likely represented continuation therapy for outpatients who took hydroxychloroquine for rheumatologic indications.

Dexamethasone, as used in the RECOVERY trial,²¹ had a swift uptake among physicians after it was incorporated into order sets and its use encouraged. Similarly, uptake was immediate for remdesivir when, in May 2020, preliminary reports showed at least some benefits, confirmed by later analysis,²² and it received an FDA EUA.

Our data also show successful stewardship of the interleukin-6 antagonist toclilizumab, which was discouraged early on by the CCMC due to lack of data or negative results. But in March 2021, with new studies releasing data^12,13 and new recommendations¹⁴ for its use in some subsets of patients with COVID-19, this drug was encouraged in appropriate subsets. A new order set with qualifying indications was prepared by the CCMC and new educational efforts made to encourage its use in appropriate patients.

Ivermectin was nonformulary at the start of the pandemic. This drug enjoyed much publicity from media sources and was promoted by certain physicians and on websites,²³ based on in-vitro activity against coronaviruses. Eventually, the World Health Organization²⁴ and the FDA²⁵ found it necessary to issue advisory statements to the public against its use outside of clinical trials. The CCMC had requests from physicians to incorporate ivermectin but declined to add it to the formulary and recommended not approving nonformulary requests due to lack of data. As a result, ivermectin was not used at either hospital.

Discussion

COVID-19 represents many challenges to health systems all over the world. For Luminis Health, the high volume of acutely ill patients with novel syndromes was a particular challenge for the hospital-based care teams. A flood of information from preprints, press releases, preliminary reports, and many other nontraditional sources made deliberative management decisions difficult for individual physicians. Much commentary has appeared around the phenomenon but with less practical advice about how to make day-to-day care decisions at a time of scientific uncertainty and intense pressure to intervene.^26,27 The CCMC was designed to overcome the information management dilemma. The need to coordinate, standardize, and oversee care was necessary given the large number of physicians who cared for COVID-19 patients on inpatient services.

It should be noted that creating order sets and issuing guidance is necessary, but not sufficient, to achieve our goals of being updated and consistent. This is especially true with large cadres of health care workers attending COVID-19 patients. Guidelines and recommendations were reinforced by unit-based oversight and stewardship from pharmacy and other leaders who constituted the CCMC.

The reduction in COVID-19 mortality over time experienced in this health care system was not unique and cannot necessarily be attributed to standardization of care. Similar improvements in mortality have been reported at many US hospitals in aggregate.²⁸ Many other factors, including changes in patient characteristics, may be responsible for reduction in mortality over time.

Throughout this report we have relied upon an implicit assumption that standardization of medical therapeutics is desirable and leads to better outcomes as compared with allowing unlimited empiricism by individual physicians, either consultants or hospitalists. Our program represents a single health system with 2 acute care hospitals located 25 miles apart and which thus were similarly impacted by the different phases of the pandemic. Generalizability to health systems either smaller or larger, or in different geographical areas, has not been established. Data limitations have already been discussed.

We did not measure user satisfaction with the program either from physicians or nurses. However, the high rate of compliance suggests general agreement with the content and process.

We cannot definitively ascribe reduction in utilization of some nonrecommended treatments and increased utilization of the recommended therapies to the work of the CCMC. Individual physicians may have made these adjustments on their own or under the influence of other sources.

Finally, it should be noted that the mission to rapidly respond to data from well-conducted trials might be thwarted by too rigid a process or a committee’s lack of a sense of urgency. Organizing a committee and then empowering it to act is no guarantee of success; commitment to the mission is.

Conclusion

COVID-19 represented a challenge to medical staffs everywhere, inundating them with high volumes of acutely ill patients presenting with unfamiliar syndromes. Initial responses were characterized by idiosyncratic management approaches based on nontraditional sources of opinion and influences.

This report describes how a complex medical system brought order and standardization through a deliberative, but urgent, multidisciplinary committee with responsibility for planning, implementing, and monitoring standard approaches that eventually became evidence based. The composition of the committee and its scope of influence, limited to inpatient management, were important elements of success, allowing for better focus on the many treatment decisions. The important connection between the management committee and the system P&T committee, the clinical research effort, and teaching programs in both medicine and pharmacy are offered as exemplars of coordination. The data presented show success in achieving standardized, guideline-directed care. The approach is adoptable and suitable for similar emergencies in the future.

Acknowledgments: The authors thank Gary Scabis, Kip Waite, John Moxley, Angela Clubb, and David Woodley for their assistance in gathering data. We express appreciation and admiration for all our colleagues at the bedside.

Corresponding author: Barry R. Meisenberg, MD, Department of Medicine, Luminis Health, 2001 Medical Pkwy, Annapolis, MD 21401; [email protected].

Financial disclosures: None.

From the Department of Medicine (Drs. Meisenberg, Muganlinskaya, Sharma, Amjadi, Arnold, Barnes, Clance, Khalil, Miller, Mooradian, O’Connell, Patel, Press, Samaras, Shanmugam, Tavadze, and Thompson), Department of Pharmacy (Drs. Jiang, Jarawan, Sheth, and Trinh), Department of Nursing (Dr. Ohnmacht), and Department of Women and Children’s Services (Dr. Raji), Luminis Health, Annapolis, MD, and Lanham, MD.

Objective: The COVID-19 pandemic has been a challenge for hospital medical staffs worldwide due to high volumes of patients acutely ill with novel syndromes and prevailing uncertainty regarding optimum supportive and therapeutic interventions. Additionally, the response to this crisis was driven by a plethora of nontraditional information sources, such as email chains, websites, non–peer-reviewed preprints, and press releases. Care patterns became idiosyncratic and often incorporated unproven interventions driven by these nontraditional information sources. This report evaluates the efforts of a health system to create and empower a multidisciplinary committee to develop, implement, and monitor evidence-based, standardized protocols for patients with COVID-19.

Methods: This report describes the composition of the committee, its scope, and its important interactions with the health system pharmacy and therapeutics committee, research teams, and other work groups planning other aspects of COVID-19 management. It illustrates how the committee was used to demonstrate for trainees the process and value of critically examining evidence, even in a chaotic environment.

Results: Data show successful interventions in reducing excessive ordering of certain laboratory tests, reduction of nonrecommended therapies, and rapid uptake of evidence-based or guidelines-supported interventions.

Conclusions: A multidisciplinary committee dedicated solely to planning, implementing, and monitoring standard approaches that eventually became evidence-based decision-making led to an improved focus on treatment options and outcomes for COVID-19 patients. Data presented illustrate the attainable success that is both adaptable and suitable for similar emergencies in the future.

Keywords: COVID-19; clinical management; pharmacy and therapeutics; treatment; therapy.

The COVID-19 pandemic has spread to nearly all countries, carrying with it high morbidity, mortality, and severe impacts on both well-developed and less-well-developed health systems. Media reports of chaos within overwhelmed hospitals have been prominent.^1,2 As of January 5, 2022, SARS-CoV-2 has infected more than 295 million people globally and directly caused the death of more than 5.4 million,³ though this number is likely an undercount even in countries with well-developed mortality tracking.⁴

Throughout the COVID-19 pandemic, hospital-based medical teams have been confronted with a flood of severely ill patients with novel syndromes. Initially, there were no standards for therapy or supportive care except for treatments borrowed from similar syndromes. In the setting of high volumes, high acuity, and public dismay, it is unsurprising that the usual deliberative methods for weighing evidence and initiating interventions were often pushed aside in favor of the solace of active intervention.⁵ In this milieu of limited evidence, there was a lamentable, if understandable, tendency to seek guidance from “nontraditional” sources,⁶ including email chains from colleagues, hospital websites, non–peer-reviewed manuscripts, advanced publication by medical journals,⁷ and nonscientific media presentations. In many localities, practitioners responded in idiosyncratic ways. For example, findings of high cytokine levels in COVID-19,⁸ along with reports of in-vitro antiviral activity with drugs like hydroxychloroquine against both SARS⁹ and SARS-CoV-2,¹⁰ drove laboratory test ordering and therapeutic interventions, respectively, carving shortcuts into the traditional clinical trial–dependent standards. Clinical trial results eventually emerged.¹¹COVID-19 created a clinical dilemma for hospital medical staffs in terms of how to organize, standardize, and rapidly adapt to a flood of new information. In this report, we describe how 1 health system responded to these challenges by forming a COVID-19 Clinical Management Committee (CCMC) and empowering this interdisciplinary team to review evidence, create and adjust order sets, educate practitioners, oversee care, and collaborate across teams addressing other aspects of the COVID-19 response.

Program Overview

Health System Description

Luminis Health is a health system with 2 acute care hospitals that was formed in 2019 just before the start of the pandemic. Anne Arundel Medical Center (hospital A) is a 385-bed teaching hospital in Annapolis, MD. It has more than 23 000 discharges annually. Patients with COVID-19 were cared for by either an internal medicine teaching service or nonteaching hospitalist services on cohorted nursing units. Doctor’s Community Medical Center, in Lanham, MD (hospital B), is a 206-bed acute care hospital with more than 10 350 annual discharges. COVID-19 patients were cared for by hospitalist groups, initially in noncohorted units with transition to cohorted nursing units after a few months. The medical staffs are generally distinct, with different leadership structures, though the Luminis Health Department of Medicine has oversight responsibilities at both hospitals. More than 47 physicians attended COVID-19 patients at hospital A (with medical residents) and 30 individual physicians at hospital B, respectively, including intensivists. The nursing and pharmacy staffs are distinct, but there is a shared oversight Pharmacy and Therapeutics (P&T) Committee.

The 2 hospitals had distinct electronic medical records (EMR) until January 2021, when hospital B adopted the same EMR as hospital A (Epic).

Mission and Formation of CCMC

In order to coordinate the therapeutic approach across the health system, it was important for the CCMC to be designated by the health system P&T committee as an official subcommittee so that decisions on restrictions of medications and/or new or revised order sets could be rapidly initiated across the system without waiting for the subsequent P&T meetings. The full committee retained oversight of the CCMC. Some P&T members were also on the CCMC.

The committee reviewed new reports in medical journals and prepublication servers and consulted recommendations of professional societies, such as the National Institutes of Health (NIH) COVID-19 guidelines, Infectious Diseases Society of America, Society of Critical Care Medicine, and US Food and Drug Administration (FDA) Emergency Use Authorizations (EUA), among other sources.

Composition of the CCMC

Physician leaders from both hospitals in the following specialties were solicited for participation: critical care, epidemiology, hospital medicine (internal medicine), emergency medicine, infectious diseases, nephrology, women and children’s services, and medical informatics. Specialists in other areas, such as hematology, were invited for topic-specific discussions. Hospital pharmacists with different specialties and nursing leadership were essential contributors. The committee members were expected to use various communication channels to inform frontline clinicians of new care standards and the existence of new order sets, which were embedded in the EMR.

Clinical Research

An important connection for the CCMC was with theCOVID-19 clinical research team. Three members of the research team were also members of the CCMC. All new study proposals for therapeutics were discussed with the CCMC as they were being considered by the research team. In this way, feedback on the feasibility and acceptance of new study opportunities could be discussed with the CCMC. Occasionally, CCMC decisions impacted clinical research accrual strategies. For example, new data from randomized trials about tocilizumab^1,2 demonstrated benefits in some subsets of patients and resulted in a recommendation for use by the NIH guideline committee in these populations.¹ The CCMC quickly adopted this recommendation, which required a reprioritization of clinical research enrollment for studies testing other immune-modulating agents. This important dialogue was mediated within the CCMC.

Guideline Distribution, Reinforcement, and Platform for Feedback

New guidelines were disseminated to clinicians via daily brief patient huddles held on COVID units, with participation by nursing and pharmacy, and by weekly meetings with hospitalist leaders and frontline hospital physicians. Order sets and guidelines were maintained on the intranet. Adherence was reinforced by unit-based and central pharmacists. Order sets, including admission order sets, could be created only by designated informatics personnel, thus enforcing standardization. Feedback on the utility of the order sets was obtained during the weekly meetings or huddles, as described above. To ensure a sense of transparency, physicians who had interest in commenting on a particular therapy, or who wished to discuss a particular manuscript, news article, or website, were invited to attend CCMC meetings.

Scope of CCMC

In order to be effective and timely, we limited the scope of our work to the report to the inpatient therapeutic environment, allowing other committees to work on other aspects of the pandemic response. In addition to issuing guidance and creating order sets to direct clinical practice, the CCMC also monitored COVID-19 therapeutic shortages^15,16 and advised on prioritization of such treatments as convalescent plasma, remdesivir (prioritization and duration of therapy, 5 vs 10 days), baricitinib, and tocilizumab, depending upon the location of the patient (critical care or not). The CCMC was not involved in the management of non–COVID-19 shortages brought about by supply chain deficiencies.

Table 1 shows some aspects of the health system pandemic-response planning and the committee workforce that undertook that work. Though many items were out of scope for the CCMC, members of the CCMC did participate in the planning work of these other committees and therefore stayed connected to this complementary work.

A Teaching Opportunity About Making Thoughtful Choices

Another important feature of the CCMC was the contributions of residents from both pharmacy and internal medicine. The purpose and operations of the committee were recognized as an opportunity to involve learners in a curriculum based on Kern’s 6-step approach.¹⁷ Though the problem identification and general needs assessment were easily defined, the targeted needs assessment, extracted from individual and group interviews with learners and the committee members, pointed at the need to learn how to assess and analyze a rapidly growing body of literature on several relevant clinical aspects of SARS-CoV-2 and COVID-19. To achieve goals and objectives, residents were assigned to present current literature on a particular intervention during a committee meeting, specifically commenting on the merit or deficiencies of the study design, the strength of the data, and applicability to the local context with a recommendation. Prior to the presentations, the residents worked with faculty to identify the best studies or systematic analyses with potential to alter current practices. We thus used the CCMC process as a teaching tool about evidence-based medicine and the dilemma of clinical equipoise. This was imperative, since trainees thrust into the COVID-19 response have often keenly observed a movement away from deliberative decision-making.¹⁸ Indeed, including residents in the process of deliberative responses to COVID-19 addresses a recent call to adjust medical education during COVID-19 to “adapt curriculum to current issues in real time.”¹⁹

Interventions and Therapies Considered

Table 2 shows the topics reviewed by the CCMC. By the time of the first meeting, nonstandardization of care was already a source of concern for clinicians. Dialogue often continued outside of the formal meetings. Many topics were considered more than once as new guidance developed, changes to EUAs occurred, and new data or new publicity arose.

Methods

The Human Protections Administrator determined that this work constituted “quality improvement, and not research” and was therefore exempt from institutional review board review.

Quantitative Analysis

All admitted patients from March 10, 2020, through April 20, 2021, were considered in the quantitative aspects of this report except as noted. Patients diagnosed with COVID-19 were identified by searching our internal data base using diagnostic codes. Patient admissions with the following diagnostic codes were included (prior to April 1, 2020): J12.89, J20.8, J40, J22, J98.8, J80, each with the additional code of B97.29. After April 1, 2020, the guideline for coding COVID-19 was U07.1.

Descriptive statistics were used to measure utilization rates of certain medications and laboratory tests of interest over time. These data were adjusted for number of unique admissions. In a few cases, not all data elements were available from both hospitals due to differences in the EMR.

Case fatality rate was calculated based upon whether the patient died or was admitted to inpatient hospice as a result of COVID-19. Four patients transferred out of hospital A and 18 transferred out of hospital B were censored from case-fatality-rate determination.

Figure 1 shows the number of admissions for each acute care hospital in the health system and the combined COVID-19 case-fatality rate over time.

Results

A total of 5955 consecutive COVID-19 patients admitted from March 10, 2020, through April 30, 2021, were analyzed. Patients with International Statistical Classification of Diseases, Tenth Revision codes J12.89. J20.8, J40, J22, J98.8, J80, each with the additional code of B97.29 (or the code UO7.1 after April 1, 2020), were included in the analysis. The median age of admitted patients was 65 years (range 19-91 years). Using the NIH classification system for severity,²⁰ the distribution of severity during the first 24 hours after the time of hospital admission was as follows: asymptomatic/presymptomatic, 0.5%; mild illness, 5.3%; moderate illness, 37.1%; severe illness, 55.5%; and critical illness, 1.1%.

The impact of the CCMC can be estimated by looking at care patterns over time. Since the work of the CCMC was aimed at influencing and standardizing physician ordering and therapy choices through order set creation and other forms of oversight, we measured the use of the CCMC-approved order sets at both hospitals and the use of certain laboratory tests and therapies that the CCMC sought either to limit or increase. These counts were adjusted for number of unique COVID-19 admissions. But the limits of the case collection tool meant it also collected cases that were not eligible for some of the interventions. For example, COVID-19 admissions without hypoxemia would not have been eligible for remdesivir or glucocorticoids. When admitted, some patients were already on steroids for other medical indications and did not receive the prescribed dexamethasone dose that we measured in pharmacy databases. Similarly, a few patients were hospitalized for indications unrelated to COVID-19, such as surgery or childbirth, and were found to be SARS-CoV-2-positive on routine screening.

Figure 2 shows the utilization of CCMC-approved standard COVID-19 admission order sets as a proportion of all COVID-19 admissions over time. The trend reveals a modest increase in usage (R² = 0.34), but these data do not reflect the progressive build of content into order sets over time. One of the goals of the order sets was to standardize and reduce the ordering of certain biomarkers: C-reactive protein, serum ferritin, and D-dimer, which were ordered frequently in many early patients. Orders for these 3 laboratory tests are combined and expressed as an average number of labs per COVID-19 admission in Figure 2. A downward trend, with an R² value of 0.65, is suggestive of impact from the order sets, though other explanations are possible.

Medication guidance was also a goal of the CCMC, simultaneously discouraging poorly supported interventions and driving uptake of the recommended evidence-based interventions in appropriate patients. Figure 3 shows the utilization pattern for some drugs of interest over the course of the pandemic, specifically the proportion of patients receiving at least 1 dose of medication among all COVID-19 admissions by month. (Data for hospital B was excluded from this analysis because it did not include all admitted patients.)

Hydroxychloroquine, which enjoyed a wave of popularity early on during the pandemic, was a target of successful order stewardship through the CCMC. Use of hydroxychloroquine as a COVID-19 therapeutic option after the first 2 months of the pandemic stopped, and subsequent use at low levels likely represented continuation therapy for outpatients who took hydroxychloroquine for rheumatologic indications.

Dexamethasone, as used in the RECOVERY trial,²¹ had a swift uptake among physicians after it was incorporated into order sets and its use encouraged. Similarly, uptake was immediate for remdesivir when, in May 2020, preliminary reports showed at least some benefits, confirmed by later analysis,²² and it received an FDA EUA.

Our data also show successful stewardship of the interleukin-6 antagonist toclilizumab, which was discouraged early on by the CCMC due to lack of data or negative results. But in March 2021, with new studies releasing data^12,13 and new recommendations¹⁴ for its use in some subsets of patients with COVID-19, this drug was encouraged in appropriate subsets. A new order set with qualifying indications was prepared by the CCMC and new educational efforts made to encourage its use in appropriate patients.

Ivermectin was nonformulary at the start of the pandemic. This drug enjoyed much publicity from media sources and was promoted by certain physicians and on websites,²³ based on in-vitro activity against coronaviruses. Eventually, the World Health Organization²⁴ and the FDA²⁵ found it necessary to issue advisory statements to the public against its use outside of clinical trials. The CCMC had requests from physicians to incorporate ivermectin but declined to add it to the formulary and recommended not approving nonformulary requests due to lack of data. As a result, ivermectin was not used at either hospital.

Discussion

COVID-19 represents many challenges to health systems all over the world. For Luminis Health, the high volume of acutely ill patients with novel syndromes was a particular challenge for the hospital-based care teams. A flood of information from preprints, press releases, preliminary reports, and many other nontraditional sources made deliberative management decisions difficult for individual physicians. Much commentary has appeared around the phenomenon but with less practical advice about how to make day-to-day care decisions at a time of scientific uncertainty and intense pressure to intervene.^26,27 The CCMC was designed to overcome the information management dilemma. The need to coordinate, standardize, and oversee care was necessary given the large number of physicians who cared for COVID-19 patients on inpatient services.

It should be noted that creating order sets and issuing guidance is necessary, but not sufficient, to achieve our goals of being updated and consistent. This is especially true with large cadres of health care workers attending COVID-19 patients. Guidelines and recommendations were reinforced by unit-based oversight and stewardship from pharmacy and other leaders who constituted the CCMC.

The reduction in COVID-19 mortality over time experienced in this health care system was not unique and cannot necessarily be attributed to standardization of care. Similar improvements in mortality have been reported at many US hospitals in aggregate.²⁸ Many other factors, including changes in patient characteristics, may be responsible for reduction in mortality over time.

Throughout this report we have relied upon an implicit assumption that standardization of medical therapeutics is desirable and leads to better outcomes as compared with allowing unlimited empiricism by individual physicians, either consultants or hospitalists. Our program represents a single health system with 2 acute care hospitals located 25 miles apart and which thus were similarly impacted by the different phases of the pandemic. Generalizability to health systems either smaller or larger, or in different geographical areas, has not been established. Data limitations have already been discussed.

We did not measure user satisfaction with the program either from physicians or nurses. However, the high rate of compliance suggests general agreement with the content and process.

We cannot definitively ascribe reduction in utilization of some nonrecommended treatments and increased utilization of the recommended therapies to the work of the CCMC. Individual physicians may have made these adjustments on their own or under the influence of other sources.

Finally, it should be noted that the mission to rapidly respond to data from well-conducted trials might be thwarted by too rigid a process or a committee’s lack of a sense of urgency. Organizing a committee and then empowering it to act is no guarantee of success; commitment to the mission is.

Conclusion

COVID-19 represented a challenge to medical staffs everywhere, inundating them with high volumes of acutely ill patients presenting with unfamiliar syndromes. Initial responses were characterized by idiosyncratic management approaches based on nontraditional sources of opinion and influences.

This report describes how a complex medical system brought order and standardization through a deliberative, but urgent, multidisciplinary committee with responsibility for planning, implementing, and monitoring standard approaches that eventually became evidence based. The composition of the committee and its scope of influence, limited to inpatient management, were important elements of success, allowing for better focus on the many treatment decisions. The important connection between the management committee and the system P&T committee, the clinical research effort, and teaching programs in both medicine and pharmacy are offered as exemplars of coordination. The data presented show success in achieving standardized, guideline-directed care. The approach is adoptable and suitable for similar emergencies in the future.

Acknowledgments: The authors thank Gary Scabis, Kip Waite, John Moxley, Angela Clubb, and David Woodley for their assistance in gathering data. We express appreciation and admiration for all our colleagues at the bedside.

Corresponding author: Barry R. Meisenberg, MD, Department of Medicine, Luminis Health, 2001 Medical Pkwy, Annapolis, MD 21401; [email protected].

Financial disclosures: None.

From the Department of Medicine (Drs. Meisenberg, Muganlinskaya, Sharma, Amjadi, Arnold, Barnes, Clance, Khalil, Miller, Mooradian, O’Connell, Patel, Press, Samaras, Shanmugam, Tavadze, and Thompson), Department of Pharmacy (Drs. Jiang, Jarawan, Sheth, and Trinh), Department of Nursing (Dr. Ohnmacht), and Department of Women and Children’s Services (Dr. Raji), Luminis Health, Annapolis, MD, and Lanham, MD.

Objective: The COVID-19 pandemic has been a challenge for hospital medical staffs worldwide due to high volumes of patients acutely ill with novel syndromes and prevailing uncertainty regarding optimum supportive and therapeutic interventions. Additionally, the response to this crisis was driven by a plethora of nontraditional information sources, such as email chains, websites, non–peer-reviewed preprints, and press releases. Care patterns became idiosyncratic and often incorporated unproven interventions driven by these nontraditional information sources. This report evaluates the efforts of a health system to create and empower a multidisciplinary committee to develop, implement, and monitor evidence-based, standardized protocols for patients with COVID-19.

Methods: This report describes the composition of the committee, its scope, and its important interactions with the health system pharmacy and therapeutics committee, research teams, and other work groups planning other aspects of COVID-19 management. It illustrates how the committee was used to demonstrate for trainees the process and value of critically examining evidence, even in a chaotic environment.

Results: Data show successful interventions in reducing excessive ordering of certain laboratory tests, reduction of nonrecommended therapies, and rapid uptake of evidence-based or guidelines-supported interventions.

Conclusions: A multidisciplinary committee dedicated solely to planning, implementing, and monitoring standard approaches that eventually became evidence-based decision-making led to an improved focus on treatment options and outcomes for COVID-19 patients. Data presented illustrate the attainable success that is both adaptable and suitable for similar emergencies in the future.

Keywords: COVID-19; clinical management; pharmacy and therapeutics; treatment; therapy.

The COVID-19 pandemic has spread to nearly all countries, carrying with it high morbidity, mortality, and severe impacts on both well-developed and less-well-developed health systems. Media reports of chaos within overwhelmed hospitals have been prominent.^1,2 As of January 5, 2022, SARS-CoV-2 has infected more than 295 million people globally and directly caused the death of more than 5.4 million,³ though this number is likely an undercount even in countries with well-developed mortality tracking.⁴

Throughout the COVID-19 pandemic, hospital-based medical teams have been confronted with a flood of severely ill patients with novel syndromes. Initially, there were no standards for therapy or supportive care except for treatments borrowed from similar syndromes. In the setting of high volumes, high acuity, and public dismay, it is unsurprising that the usual deliberative methods for weighing evidence and initiating interventions were often pushed aside in favor of the solace of active intervention.⁵ In this milieu of limited evidence, there was a lamentable, if understandable, tendency to seek guidance from “nontraditional” sources,⁶ including email chains from colleagues, hospital websites, non–peer-reviewed manuscripts, advanced publication by medical journals,⁷ and nonscientific media presentations. In many localities, practitioners responded in idiosyncratic ways. For example, findings of high cytokine levels in COVID-19,⁸ along with reports of in-vitro antiviral activity with drugs like hydroxychloroquine against both SARS⁹ and SARS-CoV-2,¹⁰ drove laboratory test ordering and therapeutic interventions, respectively, carving shortcuts into the traditional clinical trial–dependent standards. Clinical trial results eventually emerged.¹¹COVID-19 created a clinical dilemma for hospital medical staffs in terms of how to organize, standardize, and rapidly adapt to a flood of new information. In this report, we describe how 1 health system responded to these challenges by forming a COVID-19 Clinical Management Committee (CCMC) and empowering this interdisciplinary team to review evidence, create and adjust order sets, educate practitioners, oversee care, and collaborate across teams addressing other aspects of the COVID-19 response.

Program Overview

Health System Description

Luminis Health is a health system with 2 acute care hospitals that was formed in 2019 just before the start of the pandemic. Anne Arundel Medical Center (hospital A) is a 385-bed teaching hospital in Annapolis, MD. It has more than 23 000 discharges annually. Patients with COVID-19 were cared for by either an internal medicine teaching service or nonteaching hospitalist services on cohorted nursing units. Doctor’s Community Medical Center, in Lanham, MD (hospital B), is a 206-bed acute care hospital with more than 10 350 annual discharges. COVID-19 patients were cared for by hospitalist groups, initially in noncohorted units with transition to cohorted nursing units after a few months. The medical staffs are generally distinct, with different leadership structures, though the Luminis Health Department of Medicine has oversight responsibilities at both hospitals. More than 47 physicians attended COVID-19 patients at hospital A (with medical residents) and 30 individual physicians at hospital B, respectively, including intensivists. The nursing and pharmacy staffs are distinct, but there is a shared oversight Pharmacy and Therapeutics (P&T) Committee.

The 2 hospitals had distinct electronic medical records (EMR) until January 2021, when hospital B adopted the same EMR as hospital A (Epic).

Mission and Formation of CCMC

In order to coordinate the therapeutic approach across the health system, it was important for the CCMC to be designated by the health system P&T committee as an official subcommittee so that decisions on restrictions of medications and/or new or revised order sets could be rapidly initiated across the system without waiting for the subsequent P&T meetings. The full committee retained oversight of the CCMC. Some P&T members were also on the CCMC.

The committee reviewed new reports in medical journals and prepublication servers and consulted recommendations of professional societies, such as the National Institutes of Health (NIH) COVID-19 guidelines, Infectious Diseases Society of America, Society of Critical Care Medicine, and US Food and Drug Administration (FDA) Emergency Use Authorizations (EUA), among other sources.

Composition of the CCMC

Physician leaders from both hospitals in the following specialties were solicited for participation: critical care, epidemiology, hospital medicine (internal medicine), emergency medicine, infectious diseases, nephrology, women and children’s services, and medical informatics. Specialists in other areas, such as hematology, were invited for topic-specific discussions. Hospital pharmacists with different specialties and nursing leadership were essential contributors. The committee members were expected to use various communication channels to inform frontline clinicians of new care standards and the existence of new order sets, which were embedded in the EMR.

Clinical Research

An important connection for the CCMC was with theCOVID-19 clinical research team. Three members of the research team were also members of the CCMC. All new study proposals for therapeutics were discussed with the CCMC as they were being considered by the research team. In this way, feedback on the feasibility and acceptance of new study opportunities could be discussed with the CCMC. Occasionally, CCMC decisions impacted clinical research accrual strategies. For example, new data from randomized trials about tocilizumab^1,2 demonstrated benefits in some subsets of patients and resulted in a recommendation for use by the NIH guideline committee in these populations.¹ The CCMC quickly adopted this recommendation, which required a reprioritization of clinical research enrollment for studies testing other immune-modulating agents. This important dialogue was mediated within the CCMC.

Guideline Distribution, Reinforcement, and Platform for Feedback

New guidelines were disseminated to clinicians via daily brief patient huddles held on COVID units, with participation by nursing and pharmacy, and by weekly meetings with hospitalist leaders and frontline hospital physicians. Order sets and guidelines were maintained on the intranet. Adherence was reinforced by unit-based and central pharmacists. Order sets, including admission order sets, could be created only by designated informatics personnel, thus enforcing standardization. Feedback on the utility of the order sets was obtained during the weekly meetings or huddles, as described above. To ensure a sense of transparency, physicians who had interest in commenting on a particular therapy, or who wished to discuss a particular manuscript, news article, or website, were invited to attend CCMC meetings.

Scope of CCMC

In order to be effective and timely, we limited the scope of our work to the report to the inpatient therapeutic environment, allowing other committees to work on other aspects of the pandemic response. In addition to issuing guidance and creating order sets to direct clinical practice, the CCMC also monitored COVID-19 therapeutic shortages^15,16 and advised on prioritization of such treatments as convalescent plasma, remdesivir (prioritization and duration of therapy, 5 vs 10 days), baricitinib, and tocilizumab, depending upon the location of the patient (critical care or not). The CCMC was not involved in the management of non–COVID-19 shortages brought about by supply chain deficiencies.

Table 1 shows some aspects of the health system pandemic-response planning and the committee workforce that undertook that work. Though many items were out of scope for the CCMC, members of the CCMC did participate in the planning work of these other committees and therefore stayed connected to this complementary work.

A Teaching Opportunity About Making Thoughtful Choices

Another important feature of the CCMC was the contributions of residents from both pharmacy and internal medicine. The purpose and operations of the committee were recognized as an opportunity to involve learners in a curriculum based on Kern’s 6-step approach.¹⁷ Though the problem identification and general needs assessment were easily defined, the targeted needs assessment, extracted from individual and group interviews with learners and the committee members, pointed at the need to learn how to assess and analyze a rapidly growing body of literature on several relevant clinical aspects of SARS-CoV-2 and COVID-19. To achieve goals and objectives, residents were assigned to present current literature on a particular intervention during a committee meeting, specifically commenting on the merit or deficiencies of the study design, the strength of the data, and applicability to the local context with a recommendation. Prior to the presentations, the residents worked with faculty to identify the best studies or systematic analyses with potential to alter current practices. We thus used the CCMC process as a teaching tool about evidence-based medicine and the dilemma of clinical equipoise. This was imperative, since trainees thrust into the COVID-19 response have often keenly observed a movement away from deliberative decision-making.¹⁸ Indeed, including residents in the process of deliberative responses to COVID-19 addresses a recent call to adjust medical education during COVID-19 to “adapt curriculum to current issues in real time.”¹⁹

Interventions and Therapies Considered

Table 2 shows the topics reviewed by the CCMC. By the time of the first meeting, nonstandardization of care was already a source of concern for clinicians. Dialogue often continued outside of the formal meetings. Many topics were considered more than once as new guidance developed, changes to EUAs occurred, and new data or new publicity arose.

Methods

The Human Protections Administrator determined that this work constituted “quality improvement, and not research” and was therefore exempt from institutional review board review.

Quantitative Analysis

All admitted patients from March 10, 2020, through April 20, 2021, were considered in the quantitative aspects of this report except as noted. Patients diagnosed with COVID-19 were identified by searching our internal data base using diagnostic codes. Patient admissions with the following diagnostic codes were included (prior to April 1, 2020): J12.89, J20.8, J40, J22, J98.8, J80, each with the additional code of B97.29. After April 1, 2020, the guideline for coding COVID-19 was U07.1.

Descriptive statistics were used to measure utilization rates of certain medications and laboratory tests of interest over time. These data were adjusted for number of unique admissions. In a few cases, not all data elements were available from both hospitals due to differences in the EMR.

Case fatality rate was calculated based upon whether the patient died or was admitted to inpatient hospice as a result of COVID-19. Four patients transferred out of hospital A and 18 transferred out of hospital B were censored from case-fatality-rate determination.

Figure 1 shows the number of admissions for each acute care hospital in the health system and the combined COVID-19 case-fatality rate over time.

Results

A total of 5955 consecutive COVID-19 patients admitted from March 10, 2020, through April 30, 2021, were analyzed. Patients with International Statistical Classification of Diseases, Tenth Revision codes J12.89. J20.8, J40, J22, J98.8, J80, each with the additional code of B97.29 (or the code UO7.1 after April 1, 2020), were included in the analysis. The median age of admitted patients was 65 years (range 19-91 years). Using the NIH classification system for severity,²⁰ the distribution of severity during the first 24 hours after the time of hospital admission was as follows: asymptomatic/presymptomatic, 0.5%; mild illness, 5.3%; moderate illness, 37.1%; severe illness, 55.5%; and critical illness, 1.1%.

The impact of the CCMC can be estimated by looking at care patterns over time. Since the work of the CCMC was aimed at influencing and standardizing physician ordering and therapy choices through order set creation and other forms of oversight, we measured the use of the CCMC-approved order sets at both hospitals and the use of certain laboratory tests and therapies that the CCMC sought either to limit or increase. These counts were adjusted for number of unique COVID-19 admissions. But the limits of the case collection tool meant it also collected cases that were not eligible for some of the interventions. For example, COVID-19 admissions without hypoxemia would not have been eligible for remdesivir or glucocorticoids. When admitted, some patients were already on steroids for other medical indications and did not receive the prescribed dexamethasone dose that we measured in pharmacy databases. Similarly, a few patients were hospitalized for indications unrelated to COVID-19, such as surgery or childbirth, and were found to be SARS-CoV-2-positive on routine screening.

Figure 2 shows the utilization of CCMC-approved standard COVID-19 admission order sets as a proportion of all COVID-19 admissions over time. The trend reveals a modest increase in usage (R² = 0.34), but these data do not reflect the progressive build of content into order sets over time. One of the goals of the order sets was to standardize and reduce the ordering of certain biomarkers: C-reactive protein, serum ferritin, and D-dimer, which were ordered frequently in many early patients. Orders for these 3 laboratory tests are combined and expressed as an average number of labs per COVID-19 admission in Figure 2. A downward trend, with an R² value of 0.65, is suggestive of impact from the order sets, though other explanations are possible.

Medication guidance was also a goal of the CCMC, simultaneously discouraging poorly supported interventions and driving uptake of the recommended evidence-based interventions in appropriate patients. Figure 3 shows the utilization pattern for some drugs of interest over the course of the pandemic, specifically the proportion of patients receiving at least 1 dose of medication among all COVID-19 admissions by month. (Data for hospital B was excluded from this analysis because it did not include all admitted patients.)

Hydroxychloroquine, which enjoyed a wave of popularity early on during the pandemic, was a target of successful order stewardship through the CCMC. Use of hydroxychloroquine as a COVID-19 therapeutic option after the first 2 months of the pandemic stopped, and subsequent use at low levels likely represented continuation therapy for outpatients who took hydroxychloroquine for rheumatologic indications.

Dexamethasone, as used in the RECOVERY trial,²¹ had a swift uptake among physicians after it was incorporated into order sets and its use encouraged. Similarly, uptake was immediate for remdesivir when, in May 2020, preliminary reports showed at least some benefits, confirmed by later analysis,²² and it received an FDA EUA.

Our data also show successful stewardship of the interleukin-6 antagonist toclilizumab, which was discouraged early on by the CCMC due to lack of data or negative results. But in March 2021, with new studies releasing data^12,13 and new recommendations¹⁴ for its use in some subsets of patients with COVID-19, this drug was encouraged in appropriate subsets. A new order set with qualifying indications was prepared by the CCMC and new educational efforts made to encourage its use in appropriate patients.

Ivermectin was nonformulary at the start of the pandemic. This drug enjoyed much publicity from media sources and was promoted by certain physicians and on websites,²³ based on in-vitro activity against coronaviruses. Eventually, the World Health Organization²⁴ and the FDA²⁵ found it necessary to issue advisory statements to the public against its use outside of clinical trials. The CCMC had requests from physicians to incorporate ivermectin but declined to add it to the formulary and recommended not approving nonformulary requests due to lack of data. As a result, ivermectin was not used at either hospital.

Discussion

COVID-19 represents many challenges to health systems all over the world. For Luminis Health, the high volume of acutely ill patients with novel syndromes was a particular challenge for the hospital-based care teams. A flood of information from preprints, press releases, preliminary reports, and many other nontraditional sources made deliberative management decisions difficult for individual physicians. Much commentary has appeared around the phenomenon but with less practical advice about how to make day-to-day care decisions at a time of scientific uncertainty and intense pressure to intervene.^26,27 The CCMC was designed to overcome the information management dilemma. The need to coordinate, standardize, and oversee care was necessary given the large number of physicians who cared for COVID-19 patients on inpatient services.

It should be noted that creating order sets and issuing guidance is necessary, but not sufficient, to achieve our goals of being updated and consistent. This is especially true with large cadres of health care workers attending COVID-19 patients. Guidelines and recommendations were reinforced by unit-based oversight and stewardship from pharmacy and other leaders who constituted the CCMC.

The reduction in COVID-19 mortality over time experienced in this health care system was not unique and cannot necessarily be attributed to standardization of care. Similar improvements in mortality have been reported at many US hospitals in aggregate.²⁸ Many other factors, including changes in patient characteristics, may be responsible for reduction in mortality over time.

Throughout this report we have relied upon an implicit assumption that standardization of medical therapeutics is desirable and leads to better outcomes as compared with allowing unlimited empiricism by individual physicians, either consultants or hospitalists. Our program represents a single health system with 2 acute care hospitals located 25 miles apart and which thus were similarly impacted by the different phases of the pandemic. Generalizability to health systems either smaller or larger, or in different geographical areas, has not been established. Data limitations have already been discussed.

We did not measure user satisfaction with the program either from physicians or nurses. However, the high rate of compliance suggests general agreement with the content and process.

We cannot definitively ascribe reduction in utilization of some nonrecommended treatments and increased utilization of the recommended therapies to the work of the CCMC. Individual physicians may have made these adjustments on their own or under the influence of other sources.

Finally, it should be noted that the mission to rapidly respond to data from well-conducted trials might be thwarted by too rigid a process or a committee’s lack of a sense of urgency. Organizing a committee and then empowering it to act is no guarantee of success; commitment to the mission is.

Conclusion

COVID-19 represented a challenge to medical staffs everywhere, inundating them with high volumes of acutely ill patients presenting with unfamiliar syndromes. Initial responses were characterized by idiosyncratic management approaches based on nontraditional sources of opinion and influences.

This report describes how a complex medical system brought order and standardization through a deliberative, but urgent, multidisciplinary committee with responsibility for planning, implementing, and monitoring standard approaches that eventually became evidence based. The composition of the committee and its scope of influence, limited to inpatient management, were important elements of success, allowing for better focus on the many treatment decisions. The important connection between the management committee and the system P&T committee, the clinical research effort, and teaching programs in both medicine and pharmacy are offered as exemplars of coordination. The data presented show success in achieving standardized, guideline-directed care. The approach is adoptable and suitable for similar emergencies in the future.

Acknowledgments: The authors thank Gary Scabis, Kip Waite, John Moxley, Angela Clubb, and David Woodley for their assistance in gathering data. We express appreciation and admiration for all our colleagues at the bedside.

Corresponding author: Barry R. Meisenberg, MD, Department of Medicine, Luminis Health, 2001 Medical Pkwy, Annapolis, MD 21401; [email protected].

Financial disclosures: None.

From the Department of Medicine, University of California San Diego (Dr. Haponyuk), Department of Emergency Medicine, University of Tennessee (Dr. Dejong), the Department of Family Medicine, University of New Mexico (Dr. Gutfrucht), and the Department of Internal Medicine, University of New Mexico (Dr. Barrett)

Objective: Naloxone availability can reduce the risk of death from opioid overdoses, although prescriber, legislative, and payment barriers to accessing this life-saving medication exist. A previously underreported barrier involves same-day availability, the lack of which may force patients to travel to multiple pharmacies and having delays in access or risking not filling their prescription. This study sought to determine same-day availability of naloxone in pharmacies in the state of New Mexico.

Methods: Same-day availability of naloxone was assessed via an audit survey.

Results: Of the 183 pharamacies screened, only 84.7% had same-day availability, including only 72% in Albuquerque, the state’s most populous city/municipality.

Conclusion: These results highlight the extent of a previously underexplored challenge to patient care and barrier to patient safety, and future directions for more patient-centered care.

Keywords: naloxone; barriers to care; opioid overdose prevention.

The US is enduring an ongoing epidemic of deaths due to opioid use, which have increased in frequency since the onset of the COVID-19 pandemic.¹ One strategy to reduce the risk of mortality from opioid use is to ensure the widespread availability of naloxone. Individual states have implemented harm reduction strategies to increase access to naloxone, including improving availability via a statewide standing order that it may be dispensed without a prescription.^2,3 Such naloxone access laws are being widely adopted and are believed to reduce overdose deaths.⁴

There are many barriers to patients receiving naloxone despite their clinicians providing a prescription for it, including stigmatization, financial cost, and local availability.^5-9 However, the stigma associated with naloxone extends to both patients and pharmacists. Pharmacists in West Virginia, for example, showed widespread concerns about having naloxone available for patients to purchase over the counter, for fear that increasing naloxone access may increase overdoses.⁶ A study in Tennessee also found pharmacists hesitant to recommend naloxone.⁷ Another study of rural pharmacies in Georgia found that just over half carried naloxone despite a state law that naloxone be available without a prescription.⁸ Challenges are not limited to rural areas, however; a study in Philadelphia found that more than one-third of pharmacies required a prescription to dispense naloxone, contrary to state law.⁹ Thus, in a rapidly changing regulatory environment, there are many evolving barriers to patients receiving naloxone.

Methods

To better understand barriers to patients obtaining naloxone, in July and August of 2019 we performed an audit (“secret shopper”) study of all pharmacies in the state, posing as patients wishing to obtain naloxone. A publicly available list of every pharmacy in New Mexico was used to identify 89 pharmacies in Albuquerque (the most populous city in New Mexico) and 106 pharmacies throughout the rest of the state.¹²

Every pharmacy was called via a publicly available phone number during business hours (confirmed via an internet search), at least 2 hours prior to closing. One of 3 researchers telephoned pharmacies posing as a patient and inquired whether naloxone would be available for pick up the same day. If the pharmacy confirmed it was available that day, the call concluded. If naloxone was unavailable for same day pick up, researchers asked when it would be next available. Each pharmacy was called once, and neither insurance information nor cost was offered or requested. All questions were asked in English by native English speakers.

All responses were recorded in a secure spreadsheet. Once all responses were received and reviewed, they were characterized in discrete response categories: same day, within 1 to 2 days, within 3 to 4 days, within a week, or unsure/unknown. Naloxone availability was also tracked by city/municipality, and this was compared to the state’s population distribution.

Results

Responses were recorded from 183 pharmacies. Seventeen locations were eliminated from our analysis because their phone system was inoperable or the pharmacy was permanently closed. Of the pharmacies reached, 84.7% (155/183) reported they have naloxone available for pick up on the same day (Figure 1). Of the 15.3% (28) pharmacies that did not have same-day availability, 60.7% (17 pharmacies) reported availability in 1 to 2 days, 3.6% had availability in 3 to 4 days, 3.6% had availability in 1 week, and 32.1% were unsure of next availability (Figure 2). More than one-third of the state’s patients reside in municipalities where naloxone is immediately available in at least 72% of pharmacies (Table).¹³

Discussion

Increased access to naloxone at the state and community level is associated with reduced risk for death from overdose, and, consequently, widespread availability is recommended.^14-17 Statewide real-time pharmacy availability of naloxone—as patients would experience availability—has not been previously reported. These findings suggest unpredictable same-day availability that may affect experience and care outcomes. That other studies have found similar challenges in naloxone availability in other municipalities and regions suggests this barrier to access is widespread,^6-9 and likely affects patients throughout the country.

Many patients have misgivings about naloxone, and it places an undue burden on them to travel to multiple pharmacies or take repeated trips to fill prescriptions. Additionally, patients without reliable transportation may be unable to return at a later date. Although we found most pharmacies in New Mexico without immediate availability of naloxone reported they could have it within several days, such a delay may reduce the likelihood that patients will fill their prescription at all. It is also concerning that many pharmacies are unsure of when naloxone will be available, particularly when some of these may be the only pharmacy easily accessible to patients or the one where they regularly fill their prescriptions.

Barriers to naloxone availability requires further study due to possible negative consequences for patient safety and risks for exacerbating health disparities among vulnerable populations. Further research may focus on examining the effects on patients when naloxone dispensing is delayed or impossible, why there is variability in naloxone availability between different pharmacies and municipalities, the reasons for uncertainty when naloxone will be available, and effective solutions. Expanded naloxone distribution in community locations and in clinics offers one potential patient-centered solution that should be explored, but it is likely that more widespread and systemic solutions will require policy and regulatory changes at the state and national levels.

Conclusion

Urgent solutions are needed to address the epidemic of deaths from opioid overdoses. Naloxone availability is an important tool for reducing these deaths, resulting in numerous state laws attempting to increase access. Despite this, there are persistent barriers to patients receiving naloxone, including a lack of same-day availability at pharmacies. Our results suggest that this underexplored barrier is widespread. Improving both availability and accessibility of naloxone may include legislative policy solutions as well as patient-oriented solutions, such as distribution in clinics and hospitals when opioid prescriptions are first written. Further research should be conducted to determine patient-centered, effective solutions that can improve outcomes.

Corresponding author: Eileen Barrett, MD, MPH, Department of Internal Medicine, University of New Mexico; [email protected].

Financial disclosures: None.

From the Department of Medicine, University of California San Diego (Dr. Haponyuk), Department of Emergency Medicine, University of Tennessee (Dr. Dejong), the Department of Family Medicine, University of New Mexico (Dr. Gutfrucht), and the Department of Internal Medicine, University of New Mexico (Dr. Barrett)

Objective: Naloxone availability can reduce the risk of death from opioid overdoses, although prescriber, legislative, and payment barriers to accessing this life-saving medication exist. A previously underreported barrier involves same-day availability, the lack of which may force patients to travel to multiple pharmacies and having delays in access or risking not filling their prescription. This study sought to determine same-day availability of naloxone in pharmacies in the state of New Mexico.

Methods: Same-day availability of naloxone was assessed via an audit survey.

Results: Of the 183 pharamacies screened, only 84.7% had same-day availability, including only 72% in Albuquerque, the state’s most populous city/municipality.

Conclusion: These results highlight the extent of a previously underexplored challenge to patient care and barrier to patient safety, and future directions for more patient-centered care.

Keywords: naloxone; barriers to care; opioid overdose prevention.

The US is enduring an ongoing epidemic of deaths due to opioid use, which have increased in frequency since the onset of the COVID-19 pandemic.¹ One strategy to reduce the risk of mortality from opioid use is to ensure the widespread availability of naloxone. Individual states have implemented harm reduction strategies to increase access to naloxone, including improving availability via a statewide standing order that it may be dispensed without a prescription.^2,3 Such naloxone access laws are being widely adopted and are believed to reduce overdose deaths.⁴

There are many barriers to patients receiving naloxone despite their clinicians providing a prescription for it, including stigmatization, financial cost, and local availability.^5-9 However, the stigma associated with naloxone extends to both patients and pharmacists. Pharmacists in West Virginia, for example, showed widespread concerns about having naloxone available for patients to purchase over the counter, for fear that increasing naloxone access may increase overdoses.⁶ A study in Tennessee also found pharmacists hesitant to recommend naloxone.⁷ Another study of rural pharmacies in Georgia found that just over half carried naloxone despite a state law that naloxone be available without a prescription.⁸ Challenges are not limited to rural areas, however; a study in Philadelphia found that more than one-third of pharmacies required a prescription to dispense naloxone, contrary to state law.⁹ Thus, in a rapidly changing regulatory environment, there are many evolving barriers to patients receiving naloxone.

Methods

To better understand barriers to patients obtaining naloxone, in July and August of 2019 we performed an audit (“secret shopper”) study of all pharmacies in the state, posing as patients wishing to obtain naloxone. A publicly available list of every pharmacy in New Mexico was used to identify 89 pharmacies in Albuquerque (the most populous city in New Mexico) and 106 pharmacies throughout the rest of the state.¹²

Every pharmacy was called via a publicly available phone number during business hours (confirmed via an internet search), at least 2 hours prior to closing. One of 3 researchers telephoned pharmacies posing as a patient and inquired whether naloxone would be available for pick up the same day. If the pharmacy confirmed it was available that day, the call concluded. If naloxone was unavailable for same day pick up, researchers asked when it would be next available. Each pharmacy was called once, and neither insurance information nor cost was offered or requested. All questions were asked in English by native English speakers.

All responses were recorded in a secure spreadsheet. Once all responses were received and reviewed, they were characterized in discrete response categories: same day, within 1 to 2 days, within 3 to 4 days, within a week, or unsure/unknown. Naloxone availability was also tracked by city/municipality, and this was compared to the state’s population distribution.

Results

Responses were recorded from 183 pharmacies. Seventeen locations were eliminated from our analysis because their phone system was inoperable or the pharmacy was permanently closed. Of the pharmacies reached, 84.7% (155/183) reported they have naloxone available for pick up on the same day (Figure 1). Of the 15.3% (28) pharmacies that did not have same-day availability, 60.7% (17 pharmacies) reported availability in 1 to 2 days, 3.6% had availability in 3 to 4 days, 3.6% had availability in 1 week, and 32.1% were unsure of next availability (Figure 2). More than one-third of the state’s patients reside in municipalities where naloxone is immediately available in at least 72% of pharmacies (Table).¹³

Discussion

Increased access to naloxone at the state and community level is associated with reduced risk for death from overdose, and, consequently, widespread availability is recommended.^14-17 Statewide real-time pharmacy availability of naloxone—as patients would experience availability—has not been previously reported. These findings suggest unpredictable same-day availability that may affect experience and care outcomes. That other studies have found similar challenges in naloxone availability in other municipalities and regions suggests this barrier to access is widespread,^6-9 and likely affects patients throughout the country.

Many patients have misgivings about naloxone, and it places an undue burden on them to travel to multiple pharmacies or take repeated trips to fill prescriptions. Additionally, patients without reliable transportation may be unable to return at a later date. Although we found most pharmacies in New Mexico without immediate availability of naloxone reported they could have it within several days, such a delay may reduce the likelihood that patients will fill their prescription at all. It is also concerning that many pharmacies are unsure of when naloxone will be available, particularly when some of these may be the only pharmacy easily accessible to patients or the one where they regularly fill their prescriptions.

Barriers to naloxone availability requires further study due to possible negative consequences for patient safety and risks for exacerbating health disparities among vulnerable populations. Further research may focus on examining the effects on patients when naloxone dispensing is delayed or impossible, why there is variability in naloxone availability between different pharmacies and municipalities, the reasons for uncertainty when naloxone will be available, and effective solutions. Expanded naloxone distribution in community locations and in clinics offers one potential patient-centered solution that should be explored, but it is likely that more widespread and systemic solutions will require policy and regulatory changes at the state and national levels.

Conclusion

Urgent solutions are needed to address the epidemic of deaths from opioid overdoses. Naloxone availability is an important tool for reducing these deaths, resulting in numerous state laws attempting to increase access. Despite this, there are persistent barriers to patients receiving naloxone, including a lack of same-day availability at pharmacies. Our results suggest that this underexplored barrier is widespread. Improving both availability and accessibility of naloxone may include legislative policy solutions as well as patient-oriented solutions, such as distribution in clinics and hospitals when opioid prescriptions are first written. Further research should be conducted to determine patient-centered, effective solutions that can improve outcomes.

Corresponding author: Eileen Barrett, MD, MPH, Department of Internal Medicine, University of New Mexico; [email protected].

Financial disclosures: None.

From the Department of Medicine, University of California San Diego (Dr. Haponyuk), Department of Emergency Medicine, University of Tennessee (Dr. Dejong), the Department of Family Medicine, University of New Mexico (Dr. Gutfrucht), and the Department of Internal Medicine, University of New Mexico (Dr. Barrett)

Objective: Naloxone availability can reduce the risk of death from opioid overdoses, although prescriber, legislative, and payment barriers to accessing this life-saving medication exist. A previously underreported barrier involves same-day availability, the lack of which may force patients to travel to multiple pharmacies and having delays in access or risking not filling their prescription. This study sought to determine same-day availability of naloxone in pharmacies in the state of New Mexico.

Methods: Same-day availability of naloxone was assessed via an audit survey.

Results: Of the 183 pharamacies screened, only 84.7% had same-day availability, including only 72% in Albuquerque, the state’s most populous city/municipality.

Conclusion: These results highlight the extent of a previously underexplored challenge to patient care and barrier to patient safety, and future directions for more patient-centered care.

Keywords: naloxone; barriers to care; opioid overdose prevention.

The US is enduring an ongoing epidemic of deaths due to opioid use, which have increased in frequency since the onset of the COVID-19 pandemic.¹ One strategy to reduce the risk of mortality from opioid use is to ensure the widespread availability of naloxone. Individual states have implemented harm reduction strategies to increase access to naloxone, including improving availability via a statewide standing order that it may be dispensed without a prescription.^2,3 Such naloxone access laws are being widely adopted and are believed to reduce overdose deaths.⁴

There are many barriers to patients receiving naloxone despite their clinicians providing a prescription for it, including stigmatization, financial cost, and local availability.^5-9 However, the stigma associated with naloxone extends to both patients and pharmacists. Pharmacists in West Virginia, for example, showed widespread concerns about having naloxone available for patients to purchase over the counter, for fear that increasing naloxone access may increase overdoses.⁶ A study in Tennessee also found pharmacists hesitant to recommend naloxone.⁷ Another study of rural pharmacies in Georgia found that just over half carried naloxone despite a state law that naloxone be available without a prescription.⁸ Challenges are not limited to rural areas, however; a study in Philadelphia found that more than one-third of pharmacies required a prescription to dispense naloxone, contrary to state law.⁹ Thus, in a rapidly changing regulatory environment, there are many evolving barriers to patients receiving naloxone.

Methods

To better understand barriers to patients obtaining naloxone, in July and August of 2019 we performed an audit (“secret shopper”) study of all pharmacies in the state, posing as patients wishing to obtain naloxone. A publicly available list of every pharmacy in New Mexico was used to identify 89 pharmacies in Albuquerque (the most populous city in New Mexico) and 106 pharmacies throughout the rest of the state.¹²

Every pharmacy was called via a publicly available phone number during business hours (confirmed via an internet search), at least 2 hours prior to closing. One of 3 researchers telephoned pharmacies posing as a patient and inquired whether naloxone would be available for pick up the same day. If the pharmacy confirmed it was available that day, the call concluded. If naloxone was unavailable for same day pick up, researchers asked when it would be next available. Each pharmacy was called once, and neither insurance information nor cost was offered or requested. All questions were asked in English by native English speakers.

All responses were recorded in a secure spreadsheet. Once all responses were received and reviewed, they were characterized in discrete response categories: same day, within 1 to 2 days, within 3 to 4 days, within a week, or unsure/unknown. Naloxone availability was also tracked by city/municipality, and this was compared to the state’s population distribution.

Results

Responses were recorded from 183 pharmacies. Seventeen locations were eliminated from our analysis because their phone system was inoperable or the pharmacy was permanently closed. Of the pharmacies reached, 84.7% (155/183) reported they have naloxone available for pick up on the same day (Figure 1). Of the 15.3% (28) pharmacies that did not have same-day availability, 60.7% (17 pharmacies) reported availability in 1 to 2 days, 3.6% had availability in 3 to 4 days, 3.6% had availability in 1 week, and 32.1% were unsure of next availability (Figure 2). More than one-third of the state’s patients reside in municipalities where naloxone is immediately available in at least 72% of pharmacies (Table).¹³

Discussion

Increased access to naloxone at the state and community level is associated with reduced risk for death from overdose, and, consequently, widespread availability is recommended.^14-17 Statewide real-time pharmacy availability of naloxone—as patients would experience availability—has not been previously reported. These findings suggest unpredictable same-day availability that may affect experience and care outcomes. That other studies have found similar challenges in naloxone availability in other municipalities and regions suggests this barrier to access is widespread,^6-9 and likely affects patients throughout the country.

Many patients have misgivings about naloxone, and it places an undue burden on them to travel to multiple pharmacies or take repeated trips to fill prescriptions. Additionally, patients without reliable transportation may be unable to return at a later date. Although we found most pharmacies in New Mexico without immediate availability of naloxone reported they could have it within several days, such a delay may reduce the likelihood that patients will fill their prescription at all. It is also concerning that many pharmacies are unsure of when naloxone will be available, particularly when some of these may be the only pharmacy easily accessible to patients or the one where they regularly fill their prescriptions.

Barriers to naloxone availability requires further study due to possible negative consequences for patient safety and risks for exacerbating health disparities among vulnerable populations. Further research may focus on examining the effects on patients when naloxone dispensing is delayed or impossible, why there is variability in naloxone availability between different pharmacies and municipalities, the reasons for uncertainty when naloxone will be available, and effective solutions. Expanded naloxone distribution in community locations and in clinics offers one potential patient-centered solution that should be explored, but it is likely that more widespread and systemic solutions will require policy and regulatory changes at the state and national levels.

Conclusion

Urgent solutions are needed to address the epidemic of deaths from opioid overdoses. Naloxone availability is an important tool for reducing these deaths, resulting in numerous state laws attempting to increase access. Despite this, there are persistent barriers to patients receiving naloxone, including a lack of same-day availability at pharmacies. Our results suggest that this underexplored barrier is widespread. Improving both availability and accessibility of naloxone may include legislative policy solutions as well as patient-oriented solutions, such as distribution in clinics and hospitals when opioid prescriptions are first written. Further research should be conducted to determine patient-centered, effective solutions that can improve outcomes.

Corresponding author: Eileen Barrett, MD, MPH, Department of Internal Medicine, University of New Mexico; [email protected].

Financial disclosures: None.

Study Overview

Objective. To assess the efficacy and safety of olaparib as an adjuvant treatment in patients with BRCA1 or BRCA2 germline mutations who are at a high-risk for relapse.

Design. A randomized, double-blind, placebo-controlled, multicenter phase III study. The published results are from the prespecified interim analysis.

Intervention. Patients were randomized in 1:1 ratio to either receive 300 mg of olaparib orally twice daily or to receive a matching placebo. Randomization was stratified by hormone receptor status (estrogen receptor and/or progesterone receptor positive/HER2-negative vs triple negative), prior neoadjuvant vs adjuvant chemotherapy, and prior platinum use for breast cancer. Treatment was continued for 52 weeks.

Setting and participants. A total of 1836 patients were randomized in a 1:1 fashion to receive olaparib or a placebo. Eligible patients had a germline BRCA1 or BRCA1 pathogenic or likely pathogenic variant. Patients had high-risk, HER2-negative primary breast cancers and all had received definitive local therapy and neoadjuvant or adjuvant chemotherapy. Patients were enrolled between 2 to 12 weeks after completion of all local therapy. Platinum chemotherapy was allowed. Patients received adjuvant endocrine therapy for hormone receptor positive disease as well as adjuvant bisphosphonates per institutional guidelines. Patients with triple negative disease who received adjuvant chemotherapy were required to be lymph node positive or have at least 2 cm invasive disease. Patients who received neoadjuvant chemotherapy were required to have residual invasive disease to be eligible. For hormone receptor positive patients receiving adjuvant chemotherapy to be eligible they had to have at least 4 pathologically confirmed lymph nodes involved. Hormone receptor positive patients who had neoadjuvant chemotherapy were required to have had residual invasive disease.

Main outcome measures. The primary endpoint for the study was invasive disease-free survival which was defined as time from randomization to date of recurrence or death from any cause. The secondary endpoints included overall survival (OS), distant disease-free survival, safety, and tolerability of olaparib.

Main results. At the time of data cutoff, 284 events had occurred with a median follow-up of 2.5 years in the intention to treat population. A total of 81% of patients had triple negative breast cancer. Most patients (94% in the olaparib group and 92% in the placebo group) received both taxane and anthracycline based chemotherapy regimens. Platinum based chemotherapy was used in 26% of patients in each group. The groups were otherwise well balanced. Germline mutations in BRCA1 were present in 72% of patients and BRCA2 in 27% of patients. These were balanced between groups.

At the time of this analysis, adjuvant olaparib reduced the risk of invasive disease-free survival by 42% compared with placebo (P < .001). At 3 years, invasive disease-free survival was 85.9% in the olaparib group and 77.1% in the placebo group (difference, 8.8 percentage points; 95% CI, 4.5-13.0; hazard ratio [HR], 0.58; 99.5% CI, 0.41-0.82; P < .001). The 3-year distant disease-free survival was 87.5% in the olaparib group and 80.4% in the placebo group (HR 0.57; 99.5% CI, 0.39-0.83; P < .001). Results also showed that olaparib was associated with fewer deaths than placebo (59 and 86, respectively) (HR, 0.68; 99% CI, 0.44-1.05; P = .02); however, there was no significant difference between treatment arms at the time of this interim analysis. Subgroup analysis showed a consistent benefit across all groups with no difference noted regarding BRCA mutation, hormone receptor status or use of neoadjuvant vs adjuvant chemotherapy.

The side effects were consistent with the safety profile of olaparib. Adverse events of grade 3 or higher more common with olaparib included anemia (8.7%), leukopenia (3%), and fatigue (1.8%). Early discontinuation of trial regimen due to adverse events of disease recurrence occurred in 25.9% in the olaparib group and 20.7% in the placebo group. Blood transfusions were required in 5.8% of patients in the olaparib group. Myelodysplasia or acute myleoid leukemia was observed in 2 patients in the olaparib group and 3 patients in the placebo group. Adverse events leading to death occurred in 1 patient in the olaparib group and 2 patients in the placebo group.

Conclusion. Among patients with high-risk, HER2-negative early breast cancer and germline BRCA1 or BRCA2 pathogenic or likely pathogenic variants, adjuvant olaparib after completion of local treatment and neoadjuvant or adjuvant chemotherapy was associated with significantly longer invasive disease-free and distant disease-free survival compared with placebo.

Commentary

The results from the current OlympiA trial provide the first evidence that adjuvant therapy with poly adenosine diphosphate-ribose polymerase (PARP) inhibitors can improve outcomes in high-risk, HER2-negative breast cancer in patients with pathogenic BRCA1 and BRCA2 mutations. The OS, while favoring olaparib, is not yet mature at the time of this analysis. Nevertheless, these results represent an important step forward in improving outcomes in this patient population. The efficacy and safety of PARP inhibitors in BRCA-mutated breast cancer has previously been shown in patients with advanced disease leading to FDA approval of both olaparib and talazoparib in this setting.^1,2 With the current results, PARP inhibitors will certainly play an important role in the adjuvant setting in patients with deleterious BRCA1 or BRCA2 mutations at high risk for relapse. Importantly, the side effect profile appears acceptable with no unexpected events and a very low rate of secondary myeloid malignancies.

Subgroup analysis appears to indicate a benefit across all groups including hormone receptor–positive disease and triple negative breast cancer. Interestingly, approximately 25% of patients in both cohorts received platinum-based chemotherapy. The efficacy of adjuvant olaparib did not appear to be impacted by prior use of platinum-containing chemotherapy regimens. It is important to consider that postneoadjuvant capecitabine, per the results of the CREATE-X trial, in triple-negative patients was not permitted in the current study. Although, this has been widely adopted in clinical practice.³ The CREATE-X trial did not specify the benefit of adjuvant capecitabine in the BRCA-mutated cohort, thus, it is not clear how this subgroup fares with this approach. Thus, one cannot extrapolate the relative efficacy of olaparib compared with capecitabine, as pointed out by the authors, and whether we consider the use of capecitabine and/or olaparib in triple-negative patients with residual invasive disease after neoadjuvant chemotherapy is not clear at this time.

Nevertheless, the magnitude of benefit seen in this trial certainly provide clinically relevant and potentially practice changing results. It will be imperative to follow these results as the survival data matures and ensure no further long-term toxicity, particularly secondary myeloid malignancies, develop. These results should be discussed with each patient and informed decisions regarding the use of adjuvant olaparib should be considered for this patient population. Lastly, these results highlight the importance of germline testing for patients with breast cancer in accordance with national guideline recommendations. Moreover, these results certainly call into question whether it is time to consider expansion of our current germline testing guidelines to detect all potential patients who may benefit from this therapy.

Application for Clinical Practice

Adjuvant olaparib in high-risk patients with germline BRCA1 or BRCA2 mutations improves invasive and distant disease-free survival and should be considered in patients who meet the enrollment criteria of the current study. Furthermore, this highlights the importance of appropriate germline genetic testing in patients with breast cancer.

Financial disclosures: None.

Study Overview

Objective. To assess the efficacy and safety of olaparib as an adjuvant treatment in patients with BRCA1 or BRCA2 germline mutations who are at a high-risk for relapse.

Design. A randomized, double-blind, placebo-controlled, multicenter phase III study. The published results are from the prespecified interim analysis.

Intervention. Patients were randomized in 1:1 ratio to either receive 300 mg of olaparib orally twice daily or to receive a matching placebo. Randomization was stratified by hormone receptor status (estrogen receptor and/or progesterone receptor positive/HER2-negative vs triple negative), prior neoadjuvant vs adjuvant chemotherapy, and prior platinum use for breast cancer. Treatment was continued for 52 weeks.

Setting and participants. A total of 1836 patients were randomized in a 1:1 fashion to receive olaparib or a placebo. Eligible patients had a germline BRCA1 or BRCA1 pathogenic or likely pathogenic variant. Patients had high-risk, HER2-negative primary breast cancers and all had received definitive local therapy and neoadjuvant or adjuvant chemotherapy. Patients were enrolled between 2 to 12 weeks after completion of all local therapy. Platinum chemotherapy was allowed. Patients received adjuvant endocrine therapy for hormone receptor positive disease as well as adjuvant bisphosphonates per institutional guidelines. Patients with triple negative disease who received adjuvant chemotherapy were required to be lymph node positive or have at least 2 cm invasive disease. Patients who received neoadjuvant chemotherapy were required to have residual invasive disease to be eligible. For hormone receptor positive patients receiving adjuvant chemotherapy to be eligible they had to have at least 4 pathologically confirmed lymph nodes involved. Hormone receptor positive patients who had neoadjuvant chemotherapy were required to have had residual invasive disease.

Main outcome measures. The primary endpoint for the study was invasive disease-free survival which was defined as time from randomization to date of recurrence or death from any cause. The secondary endpoints included overall survival (OS), distant disease-free survival, safety, and tolerability of olaparib.

Main results. At the time of data cutoff, 284 events had occurred with a median follow-up of 2.5 years in the intention to treat population. A total of 81% of patients had triple negative breast cancer. Most patients (94% in the olaparib group and 92% in the placebo group) received both taxane and anthracycline based chemotherapy regimens. Platinum based chemotherapy was used in 26% of patients in each group. The groups were otherwise well balanced. Germline mutations in BRCA1 were present in 72% of patients and BRCA2 in 27% of patients. These were balanced between groups.

At the time of this analysis, adjuvant olaparib reduced the risk of invasive disease-free survival by 42% compared with placebo (P < .001). At 3 years, invasive disease-free survival was 85.9% in the olaparib group and 77.1% in the placebo group (difference, 8.8 percentage points; 95% CI, 4.5-13.0; hazard ratio [HR], 0.58; 99.5% CI, 0.41-0.82; P < .001). The 3-year distant disease-free survival was 87.5% in the olaparib group and 80.4% in the placebo group (HR 0.57; 99.5% CI, 0.39-0.83; P < .001). Results also showed that olaparib was associated with fewer deaths than placebo (59 and 86, respectively) (HR, 0.68; 99% CI, 0.44-1.05; P = .02); however, there was no significant difference between treatment arms at the time of this interim analysis. Subgroup analysis showed a consistent benefit across all groups with no difference noted regarding BRCA mutation, hormone receptor status or use of neoadjuvant vs adjuvant chemotherapy.

The side effects were consistent with the safety profile of olaparib. Adverse events of grade 3 or higher more common with olaparib included anemia (8.7%), leukopenia (3%), and fatigue (1.8%). Early discontinuation of trial regimen due to adverse events of disease recurrence occurred in 25.9% in the olaparib group and 20.7% in the placebo group. Blood transfusions were required in 5.8% of patients in the olaparib group. Myelodysplasia or acute myleoid leukemia was observed in 2 patients in the olaparib group and 3 patients in the placebo group. Adverse events leading to death occurred in 1 patient in the olaparib group and 2 patients in the placebo group.

Conclusion. Among patients with high-risk, HER2-negative early breast cancer and germline BRCA1 or BRCA2 pathogenic or likely pathogenic variants, adjuvant olaparib after completion of local treatment and neoadjuvant or adjuvant chemotherapy was associated with significantly longer invasive disease-free and distant disease-free survival compared with placebo.

Commentary

The results from the current OlympiA trial provide the first evidence that adjuvant therapy with poly adenosine diphosphate-ribose polymerase (PARP) inhibitors can improve outcomes in high-risk, HER2-negative breast cancer in patients with pathogenic BRCA1 and BRCA2 mutations. The OS, while favoring olaparib, is not yet mature at the time of this analysis. Nevertheless, these results represent an important step forward in improving outcomes in this patient population. The efficacy and safety of PARP inhibitors in BRCA-mutated breast cancer has previously been shown in patients with advanced disease leading to FDA approval of both olaparib and talazoparib in this setting.^1,2 With the current results, PARP inhibitors will certainly play an important role in the adjuvant setting in patients with deleterious BRCA1 or BRCA2 mutations at high risk for relapse. Importantly, the side effect profile appears acceptable with no unexpected events and a very low rate of secondary myeloid malignancies.

Subgroup analysis appears to indicate a benefit across all groups including hormone receptor–positive disease and triple negative breast cancer. Interestingly, approximately 25% of patients in both cohorts received platinum-based chemotherapy. The efficacy of adjuvant olaparib did not appear to be impacted by prior use of platinum-containing chemotherapy regimens. It is important to consider that postneoadjuvant capecitabine, per the results of the CREATE-X trial, in triple-negative patients was not permitted in the current study. Although, this has been widely adopted in clinical practice.³ The CREATE-X trial did not specify the benefit of adjuvant capecitabine in the BRCA-mutated cohort, thus, it is not clear how this subgroup fares with this approach. Thus, one cannot extrapolate the relative efficacy of olaparib compared with capecitabine, as pointed out by the authors, and whether we consider the use of capecitabine and/or olaparib in triple-negative patients with residual invasive disease after neoadjuvant chemotherapy is not clear at this time.

Nevertheless, the magnitude of benefit seen in this trial certainly provide clinically relevant and potentially practice changing results. It will be imperative to follow these results as the survival data matures and ensure no further long-term toxicity, particularly secondary myeloid malignancies, develop. These results should be discussed with each patient and informed decisions regarding the use of adjuvant olaparib should be considered for this patient population. Lastly, these results highlight the importance of germline testing for patients with breast cancer in accordance with national guideline recommendations. Moreover, these results certainly call into question whether it is time to consider expansion of our current germline testing guidelines to detect all potential patients who may benefit from this therapy.

Application for Clinical Practice

Adjuvant olaparib in high-risk patients with germline BRCA1 or BRCA2 mutations improves invasive and distant disease-free survival and should be considered in patients who meet the enrollment criteria of the current study. Furthermore, this highlights the importance of appropriate germline genetic testing in patients with breast cancer.

Financial disclosures: None.

Study Overview

Objective. To assess the efficacy and safety of olaparib as an adjuvant treatment in patients with BRCA1 or BRCA2 germline mutations who are at a high-risk for relapse.

Design. A randomized, double-blind, placebo-controlled, multicenter phase III study. The published results are from the prespecified interim analysis.

Intervention. Patients were randomized in 1:1 ratio to either receive 300 mg of olaparib orally twice daily or to receive a matching placebo. Randomization was stratified by hormone receptor status (estrogen receptor and/or progesterone receptor positive/HER2-negative vs triple negative), prior neoadjuvant vs adjuvant chemotherapy, and prior platinum use for breast cancer. Treatment was continued for 52 weeks.

Setting and participants. A total of 1836 patients were randomized in a 1:1 fashion to receive olaparib or a placebo. Eligible patients had a germline BRCA1 or BRCA1 pathogenic or likely pathogenic variant. Patients had high-risk, HER2-negative primary breast cancers and all had received definitive local therapy and neoadjuvant or adjuvant chemotherapy. Patients were enrolled between 2 to 12 weeks after completion of all local therapy. Platinum chemotherapy was allowed. Patients received adjuvant endocrine therapy for hormone receptor positive disease as well as adjuvant bisphosphonates per institutional guidelines. Patients with triple negative disease who received adjuvant chemotherapy were required to be lymph node positive or have at least 2 cm invasive disease. Patients who received neoadjuvant chemotherapy were required to have residual invasive disease to be eligible. For hormone receptor positive patients receiving adjuvant chemotherapy to be eligible they had to have at least 4 pathologically confirmed lymph nodes involved. Hormone receptor positive patients who had neoadjuvant chemotherapy were required to have had residual invasive disease.

Main outcome measures. The primary endpoint for the study was invasive disease-free survival which was defined as time from randomization to date of recurrence or death from any cause. The secondary endpoints included overall survival (OS), distant disease-free survival, safety, and tolerability of olaparib.

Main results. At the time of data cutoff, 284 events had occurred with a median follow-up of 2.5 years in the intention to treat population. A total of 81% of patients had triple negative breast cancer. Most patients (94% in the olaparib group and 92% in the placebo group) received both taxane and anthracycline based chemotherapy regimens. Platinum based chemotherapy was used in 26% of patients in each group. The groups were otherwise well balanced. Germline mutations in BRCA1 were present in 72% of patients and BRCA2 in 27% of patients. These were balanced between groups.

At the time of this analysis, adjuvant olaparib reduced the risk of invasive disease-free survival by 42% compared with placebo (P < .001). At 3 years, invasive disease-free survival was 85.9% in the olaparib group and 77.1% in the placebo group (difference, 8.8 percentage points; 95% CI, 4.5-13.0; hazard ratio [HR], 0.58; 99.5% CI, 0.41-0.82; P < .001). The 3-year distant disease-free survival was 87.5% in the olaparib group and 80.4% in the placebo group (HR 0.57; 99.5% CI, 0.39-0.83; P < .001). Results also showed that olaparib was associated with fewer deaths than placebo (59 and 86, respectively) (HR, 0.68; 99% CI, 0.44-1.05; P = .02); however, there was no significant difference between treatment arms at the time of this interim analysis. Subgroup analysis showed a consistent benefit across all groups with no difference noted regarding BRCA mutation, hormone receptor status or use of neoadjuvant vs adjuvant chemotherapy.

The side effects were consistent with the safety profile of olaparib. Adverse events of grade 3 or higher more common with olaparib included anemia (8.7%), leukopenia (3%), and fatigue (1.8%). Early discontinuation of trial regimen due to adverse events of disease recurrence occurred in 25.9% in the olaparib group and 20.7% in the placebo group. Blood transfusions were required in 5.8% of patients in the olaparib group. Myelodysplasia or acute myleoid leukemia was observed in 2 patients in the olaparib group and 3 patients in the placebo group. Adverse events leading to death occurred in 1 patient in the olaparib group and 2 patients in the placebo group.

Conclusion. Among patients with high-risk, HER2-negative early breast cancer and germline BRCA1 or BRCA2 pathogenic or likely pathogenic variants, adjuvant olaparib after completion of local treatment and neoadjuvant or adjuvant chemotherapy was associated with significantly longer invasive disease-free and distant disease-free survival compared with placebo.

Commentary

The results from the current OlympiA trial provide the first evidence that adjuvant therapy with poly adenosine diphosphate-ribose polymerase (PARP) inhibitors can improve outcomes in high-risk, HER2-negative breast cancer in patients with pathogenic BRCA1 and BRCA2 mutations. The OS, while favoring olaparib, is not yet mature at the time of this analysis. Nevertheless, these results represent an important step forward in improving outcomes in this patient population. The efficacy and safety of PARP inhibitors in BRCA-mutated breast cancer has previously been shown in patients with advanced disease leading to FDA approval of both olaparib and talazoparib in this setting.^1,2 With the current results, PARP inhibitors will certainly play an important role in the adjuvant setting in patients with deleterious BRCA1 or BRCA2 mutations at high risk for relapse. Importantly, the side effect profile appears acceptable with no unexpected events and a very low rate of secondary myeloid malignancies.

Subgroup analysis appears to indicate a benefit across all groups including hormone receptor–positive disease and triple negative breast cancer. Interestingly, approximately 25% of patients in both cohorts received platinum-based chemotherapy. The efficacy of adjuvant olaparib did not appear to be impacted by prior use of platinum-containing chemotherapy regimens. It is important to consider that postneoadjuvant capecitabine, per the results of the CREATE-X trial, in triple-negative patients was not permitted in the current study. Although, this has been widely adopted in clinical practice.³ The CREATE-X trial did not specify the benefit of adjuvant capecitabine in the BRCA-mutated cohort, thus, it is not clear how this subgroup fares with this approach. Thus, one cannot extrapolate the relative efficacy of olaparib compared with capecitabine, as pointed out by the authors, and whether we consider the use of capecitabine and/or olaparib in triple-negative patients with residual invasive disease after neoadjuvant chemotherapy is not clear at this time.

Nevertheless, the magnitude of benefit seen in this trial certainly provide clinically relevant and potentially practice changing results. It will be imperative to follow these results as the survival data matures and ensure no further long-term toxicity, particularly secondary myeloid malignancies, develop. These results should be discussed with each patient and informed decisions regarding the use of adjuvant olaparib should be considered for this patient population. Lastly, these results highlight the importance of germline testing for patients with breast cancer in accordance with national guideline recommendations. Moreover, these results certainly call into question whether it is time to consider expansion of our current germline testing guidelines to detect all potential patients who may benefit from this therapy.

Application for Clinical Practice

Adjuvant olaparib in high-risk patients with germline BRCA1 or BRCA2 mutations improves invasive and distant disease-free survival and should be considered in patients who meet the enrollment criteria of the current study. Furthermore, this highlights the importance of appropriate germline genetic testing in patients with breast cancer.

Financial disclosures: None.

Study Overview

Objective. To evaluate the efficacy and safety of the combination of nivolumab plus cabozantinib as compared with sunitinib monotherapy in the treatment of previously untreated advanced renal cell carcinoma (RCC).

Design. Multicenter, international, open-label, randomized, phase 3 trial.

Intervention. Patients were randomized in a 1:1 fashion to 1 of 2 treatment arms:

• Arm A: Nivolumab intravenously 240 mg every 2 weeks plus cabozantinib orally 40 mg once daily.
• Arm B: Sunitinib orally 50 mg daily for 4 weeks, followed by 2 weeks off therapy (6-week cycle).

Randomization was stratified by the International Metastatic RCC Database Consortium prognostic risk score (low-, intermediate-, and high-risk). Treatment was continued until disease progression or development of unacceptable toxic side effects with a maximum of 2-year duration of Nivolumab therapy.

Settings and participants. Adults with previously untreated advanced RCC with a clear cell component were eligible for enrollment. Subjects were excluded if they had active central nervous system metastases or active autoimmune disease.

Main outcome measures. The primary outcome of this study was progression-free survival (PFS) as assessed by an independent review committee. Secondary endpoints included overall survival, objective response rate, safety, and PFS as assessed by investigators. All subgroup analyses were prespecified. Efficacy was assessed in the intention-to-treat population, including all patients who underwent randomization.

Main results. A total of 651 patients underwent randomization: 323 to the nivolumab plus cabozantinib group, and 328 to the sunitinib group. Baseline demographics were balanced. The median follow-up period for overall survival (OS) was 18.1 months. The primary reason for treatment discontinuation in any group was disease progression. PFS as indicated by an independent review committee was significantly longer in the nivolumab plus cabozantinib group compared to the sunitinib group (median 16.6 months vs 8.2 months; hazard ratio [HR] 0.51, P < .001). The median OS was not reached for any group. Overall survival was longer in the nivolumab plus cabozantinib group compared to the sunitinib group (HR 0.60, 95% CI: 0.40-0.89; P = .001). The objective response rate was 55.7% with the nivolumab plus cabozantinib group versus 27.1% with sunitinib (P < .001). The complete response rate was 8% in the nivolumab plus cabozantinib group compared to 4.6% in the sunitinib group. The median time to response was 2.8 months with nivolumab plus cabozantinib and 4.2 months in the sunitinib group, while the median duration of response was 20.2 months and 11.5 months, respectively.

Nearly all patients (about 99% in each group) had an adverse event (AE). Hypertension was the most common side effect, with grade 3 or higher seen in 12.5% in the nivolumab plus cabzantinib group and 13.1% in the sunitinib group. Other grade 3 or higher side effects occurring in at least 10% of patients in any group were hyponatremia, diarrhea, palmar-plantar erythrodysesthesia, hypothyroidism, and fatigue. AEs of any cause leading to discontinuation of the therapy occurred in 19.7% in the nivolumab plus cabzantinib group vs 16.9% of the sunitinib group. One death was considered to be treatment-related (small intestinal perforation) in the nivolumab plus cabozantinib group vs 2 treatment-related deaths with sunitinib (pneumonia and respiratory distress). In the nivolumab plus cabozantinib group, 57% of the patients had a dose reduction of cabozantinib and 52% had a reduction in sunitinib dosage.

Using the Functional Assessment of Cancer Therapy-Kidney Symptoms Index, patients in the nivolumab plus cabozantinib group reported better health-related quality of life and less disease-related symptoms compared to the sunitinib group.

Commentary

The treatment landscape for frontline therapy for patients with advanced RCC has rapidly expanded over the last several years and has revolutionized cancer care. Ushered in by the results from the CheckMate 214 study highlighting the efficacy of dual checkpoint inhibition with nivolumab and ipilimumab in intermediate and poor risk patients, several subsequent trials have demonstrated improved outcomes with combination therapy with immune checkpoint inhibitors and tyrosine-kinase inhibitors (TKI). To date, data from Keynote-426 (pembrolizumab plus axitinib vs sunitinib), Javelin Renal 101 (avelumab plus axitinib vs sunitinib) and the CLEAR trial (lenvatinib plus pembrolizumab vs levatinib plus everolimus vs sunitinib) have demonstrated superiority of immune checkpoint inhibitor/TKI combinations over sunitinb in the first-line setting.^1-5

The current phase 3, CheckMate 9ER trial adds yet another dynamic option for patients with advanced clear cell RCC. While cross-trial comparisons are fraught with important caveats, the median PFS of almost 16.6 months and complete response rate of 8% the nivolumab plus cabozantinib group compares favorably with other combinations. Data from the CLEAR study with the combination of lenvatinib and pembrolizumab showed a complete response rate approaching 16%. Importantly, the current study highlights improved quality of life with the combination of cabozantinib and nivolumab compared to sunitinib alone adding to the efficacy and benefits of this combination treatment.

The selection of first line therapy for patients with advanced RCC should be always guided by individual patient characteristics, and any single immune checkpoint inhibitor/TKI combination is not “superior” to any other. Perhaps more importantly is developing an understanding of the overlapping toxicity profiles of checkpoint inhibitors and TKIs. Again, this trial results are consistent with prior studies in terms of the adverse event profile which were not trivial, and almost all patients (99%) experienced AEs. It is important for oncologists to understand the management of the toxicities with these combinations and dose reductions as appropriate. It is worth noting that 19% of patients with nivolumab plus cabozantinib received glucocorticoids for management of immune-related AEs.

While long-term follow-up data will be needed to further understand the durability of response to this combination, nivolumab-cabozantinib represents an exciting new option for patients with advanced clear cell RCC. As we continue to see improvement in outcomes in clear cell histology, further work must focus on optimization of therapy in non-clear cell RCC as this is a population that is not represented in these data sets. Furthermore, future efforts should begin to explore triplet combinations and biomarker driven patient selection for upfront therapy in ordercontinue to improve outcomes in patients with advanced RCC.

Applications for Clinical Practice

The combination of nivolumab plus cabozantinib adds to the growing list of highly active checkpoint inhibitor/TKI combinations for first-line treatment of advanced RCC. With significant higher response rates, improved outcomes, and improvement in the quality of life, this combination will add another standard treatment option for patients with previously untreated advanced RCC.

Study Overview

Objective. To evaluate the efficacy and safety of the combination of nivolumab plus cabozantinib as compared with sunitinib monotherapy in the treatment of previously untreated advanced renal cell carcinoma (RCC).

Design. Multicenter, international, open-label, randomized, phase 3 trial.

Intervention. Patients were randomized in a 1:1 fashion to 1 of 2 treatment arms:

• Arm A: Nivolumab intravenously 240 mg every 2 weeks plus cabozantinib orally 40 mg once daily.
• Arm B: Sunitinib orally 50 mg daily for 4 weeks, followed by 2 weeks off therapy (6-week cycle).

Randomization was stratified by the International Metastatic RCC Database Consortium prognostic risk score (low-, intermediate-, and high-risk). Treatment was continued until disease progression or development of unacceptable toxic side effects with a maximum of 2-year duration of Nivolumab therapy.

Settings and participants. Adults with previously untreated advanced RCC with a clear cell component were eligible for enrollment. Subjects were excluded if they had active central nervous system metastases or active autoimmune disease.

Main outcome measures. The primary outcome of this study was progression-free survival (PFS) as assessed by an independent review committee. Secondary endpoints included overall survival, objective response rate, safety, and PFS as assessed by investigators. All subgroup analyses were prespecified. Efficacy was assessed in the intention-to-treat population, including all patients who underwent randomization.

Main results. A total of 651 patients underwent randomization: 323 to the nivolumab plus cabozantinib group, and 328 to the sunitinib group. Baseline demographics were balanced. The median follow-up period for overall survival (OS) was 18.1 months. The primary reason for treatment discontinuation in any group was disease progression. PFS as indicated by an independent review committee was significantly longer in the nivolumab plus cabozantinib group compared to the sunitinib group (median 16.6 months vs 8.2 months; hazard ratio [HR] 0.51, P < .001). The median OS was not reached for any group. Overall survival was longer in the nivolumab plus cabozantinib group compared to the sunitinib group (HR 0.60, 95% CI: 0.40-0.89; P = .001). The objective response rate was 55.7% with the nivolumab plus cabozantinib group versus 27.1% with sunitinib (P < .001). The complete response rate was 8% in the nivolumab plus cabozantinib group compared to 4.6% in the sunitinib group. The median time to response was 2.8 months with nivolumab plus cabozantinib and 4.2 months in the sunitinib group, while the median duration of response was 20.2 months and 11.5 months, respectively.

Nearly all patients (about 99% in each group) had an adverse event (AE). Hypertension was the most common side effect, with grade 3 or higher seen in 12.5% in the nivolumab plus cabzantinib group and 13.1% in the sunitinib group. Other grade 3 or higher side effects occurring in at least 10% of patients in any group were hyponatremia, diarrhea, palmar-plantar erythrodysesthesia, hypothyroidism, and fatigue. AEs of any cause leading to discontinuation of the therapy occurred in 19.7% in the nivolumab plus cabzantinib group vs 16.9% of the sunitinib group. One death was considered to be treatment-related (small intestinal perforation) in the nivolumab plus cabozantinib group vs 2 treatment-related deaths with sunitinib (pneumonia and respiratory distress). In the nivolumab plus cabozantinib group, 57% of the patients had a dose reduction of cabozantinib and 52% had a reduction in sunitinib dosage.

Using the Functional Assessment of Cancer Therapy-Kidney Symptoms Index, patients in the nivolumab plus cabozantinib group reported better health-related quality of life and less disease-related symptoms compared to the sunitinib group.

Commentary

The treatment landscape for frontline therapy for patients with advanced RCC has rapidly expanded over the last several years and has revolutionized cancer care. Ushered in by the results from the CheckMate 214 study highlighting the efficacy of dual checkpoint inhibition with nivolumab and ipilimumab in intermediate and poor risk patients, several subsequent trials have demonstrated improved outcomes with combination therapy with immune checkpoint inhibitors and tyrosine-kinase inhibitors (TKI). To date, data from Keynote-426 (pembrolizumab plus axitinib vs sunitinib), Javelin Renal 101 (avelumab plus axitinib vs sunitinib) and the CLEAR trial (lenvatinib plus pembrolizumab vs levatinib plus everolimus vs sunitinib) have demonstrated superiority of immune checkpoint inhibitor/TKI combinations over sunitinb in the first-line setting.^1-5

The current phase 3, CheckMate 9ER trial adds yet another dynamic option for patients with advanced clear cell RCC. While cross-trial comparisons are fraught with important caveats, the median PFS of almost 16.6 months and complete response rate of 8% the nivolumab plus cabozantinib group compares favorably with other combinations. Data from the CLEAR study with the combination of lenvatinib and pembrolizumab showed a complete response rate approaching 16%. Importantly, the current study highlights improved quality of life with the combination of cabozantinib and nivolumab compared to sunitinib alone adding to the efficacy and benefits of this combination treatment.

The selection of first line therapy for patients with advanced RCC should be always guided by individual patient characteristics, and any single immune checkpoint inhibitor/TKI combination is not “superior” to any other. Perhaps more importantly is developing an understanding of the overlapping toxicity profiles of checkpoint inhibitors and TKIs. Again, this trial results are consistent with prior studies in terms of the adverse event profile which were not trivial, and almost all patients (99%) experienced AEs. It is important for oncologists to understand the management of the toxicities with these combinations and dose reductions as appropriate. It is worth noting that 19% of patients with nivolumab plus cabozantinib received glucocorticoids for management of immune-related AEs.

While long-term follow-up data will be needed to further understand the durability of response to this combination, nivolumab-cabozantinib represents an exciting new option for patients with advanced clear cell RCC. As we continue to see improvement in outcomes in clear cell histology, further work must focus on optimization of therapy in non-clear cell RCC as this is a population that is not represented in these data sets. Furthermore, future efforts should begin to explore triplet combinations and biomarker driven patient selection for upfront therapy in ordercontinue to improve outcomes in patients with advanced RCC.

Applications for Clinical Practice

The combination of nivolumab plus cabozantinib adds to the growing list of highly active checkpoint inhibitor/TKI combinations for first-line treatment of advanced RCC. With significant higher response rates, improved outcomes, and improvement in the quality of life, this combination will add another standard treatment option for patients with previously untreated advanced RCC.

Study Overview

Objective. To evaluate the efficacy and safety of the combination of nivolumab plus cabozantinib as compared with sunitinib monotherapy in the treatment of previously untreated advanced renal cell carcinoma (RCC).

Design. Multicenter, international, open-label, randomized, phase 3 trial.

Intervention. Patients were randomized in a 1:1 fashion to 1 of 2 treatment arms:

• Arm A: Nivolumab intravenously 240 mg every 2 weeks plus cabozantinib orally 40 mg once daily.
• Arm B: Sunitinib orally 50 mg daily for 4 weeks, followed by 2 weeks off therapy (6-week cycle).

Randomization was stratified by the International Metastatic RCC Database Consortium prognostic risk score (low-, intermediate-, and high-risk). Treatment was continued until disease progression or development of unacceptable toxic side effects with a maximum of 2-year duration of Nivolumab therapy.

Settings and participants. Adults with previously untreated advanced RCC with a clear cell component were eligible for enrollment. Subjects were excluded if they had active central nervous system metastases or active autoimmune disease.

Main outcome measures. The primary outcome of this study was progression-free survival (PFS) as assessed by an independent review committee. Secondary endpoints included overall survival, objective response rate, safety, and PFS as assessed by investigators. All subgroup analyses were prespecified. Efficacy was assessed in the intention-to-treat population, including all patients who underwent randomization.

Main results. A total of 651 patients underwent randomization: 323 to the nivolumab plus cabozantinib group, and 328 to the sunitinib group. Baseline demographics were balanced. The median follow-up period for overall survival (OS) was 18.1 months. The primary reason for treatment discontinuation in any group was disease progression. PFS as indicated by an independent review committee was significantly longer in the nivolumab plus cabozantinib group compared to the sunitinib group (median 16.6 months vs 8.2 months; hazard ratio [HR] 0.51, P < .001). The median OS was not reached for any group. Overall survival was longer in the nivolumab plus cabozantinib group compared to the sunitinib group (HR 0.60, 95% CI: 0.40-0.89; P = .001). The objective response rate was 55.7% with the nivolumab plus cabozantinib group versus 27.1% with sunitinib (P < .001). The complete response rate was 8% in the nivolumab plus cabozantinib group compared to 4.6% in the sunitinib group. The median time to response was 2.8 months with nivolumab plus cabozantinib and 4.2 months in the sunitinib group, while the median duration of response was 20.2 months and 11.5 months, respectively.

Nearly all patients (about 99% in each group) had an adverse event (AE). Hypertension was the most common side effect, with grade 3 or higher seen in 12.5% in the nivolumab plus cabzantinib group and 13.1% in the sunitinib group. Other grade 3 or higher side effects occurring in at least 10% of patients in any group were hyponatremia, diarrhea, palmar-plantar erythrodysesthesia, hypothyroidism, and fatigue. AEs of any cause leading to discontinuation of the therapy occurred in 19.7% in the nivolumab plus cabzantinib group vs 16.9% of the sunitinib group. One death was considered to be treatment-related (small intestinal perforation) in the nivolumab plus cabozantinib group vs 2 treatment-related deaths with sunitinib (pneumonia and respiratory distress). In the nivolumab plus cabozantinib group, 57% of the patients had a dose reduction of cabozantinib and 52% had a reduction in sunitinib dosage.

Using the Functional Assessment of Cancer Therapy-Kidney Symptoms Index, patients in the nivolumab plus cabozantinib group reported better health-related quality of life and less disease-related symptoms compared to the sunitinib group.

Commentary

The treatment landscape for frontline therapy for patients with advanced RCC has rapidly expanded over the last several years and has revolutionized cancer care. Ushered in by the results from the CheckMate 214 study highlighting the efficacy of dual checkpoint inhibition with nivolumab and ipilimumab in intermediate and poor risk patients, several subsequent trials have demonstrated improved outcomes with combination therapy with immune checkpoint inhibitors and tyrosine-kinase inhibitors (TKI). To date, data from Keynote-426 (pembrolizumab plus axitinib vs sunitinib), Javelin Renal 101 (avelumab plus axitinib vs sunitinib) and the CLEAR trial (lenvatinib plus pembrolizumab vs levatinib plus everolimus vs sunitinib) have demonstrated superiority of immune checkpoint inhibitor/TKI combinations over sunitinb in the first-line setting.^1-5

The current phase 3, CheckMate 9ER trial adds yet another dynamic option for patients with advanced clear cell RCC. While cross-trial comparisons are fraught with important caveats, the median PFS of almost 16.6 months and complete response rate of 8% the nivolumab plus cabozantinib group compares favorably with other combinations. Data from the CLEAR study with the combination of lenvatinib and pembrolizumab showed a complete response rate approaching 16%. Importantly, the current study highlights improved quality of life with the combination of cabozantinib and nivolumab compared to sunitinib alone adding to the efficacy and benefits of this combination treatment.

The selection of first line therapy for patients with advanced RCC should be always guided by individual patient characteristics, and any single immune checkpoint inhibitor/TKI combination is not “superior” to any other. Perhaps more importantly is developing an understanding of the overlapping toxicity profiles of checkpoint inhibitors and TKIs. Again, this trial results are consistent with prior studies in terms of the adverse event profile which were not trivial, and almost all patients (99%) experienced AEs. It is important for oncologists to understand the management of the toxicities with these combinations and dose reductions as appropriate. It is worth noting that 19% of patients with nivolumab plus cabozantinib received glucocorticoids for management of immune-related AEs.

While long-term follow-up data will be needed to further understand the durability of response to this combination, nivolumab-cabozantinib represents an exciting new option for patients with advanced clear cell RCC. As we continue to see improvement in outcomes in clear cell histology, further work must focus on optimization of therapy in non-clear cell RCC as this is a population that is not represented in these data sets. Furthermore, future efforts should begin to explore triplet combinations and biomarker driven patient selection for upfront therapy in ordercontinue to improve outcomes in patients with advanced RCC.

Applications for Clinical Practice

The combination of nivolumab plus cabozantinib adds to the growing list of highly active checkpoint inhibitor/TKI combinations for first-line treatment of advanced RCC. With significant higher response rates, improved outcomes, and improvement in the quality of life, this combination will add another standard treatment option for patients with previously untreated advanced RCC.

Study Overview

Objective: To assess whether ticagrelor was superior to clopidogrel in reducing periprocedural myocardial necrosis in stable coronary patients undergoing elective percutaneous coronary intervention (PCI).

Design: Multicenter, open-label, and prospective randomized control trial. Setting and participants: A total of 1910 patients with indication for PCI and at least 1 high risk characteristic were randomized to either ticagrelor or clopidogrel.

Main outcome measures: The primary outcome was the composite of PCI-related type 4a or 4b myocardial infarction or major myocardial injury. The primary safety outcome was major bleeding, evaluated within 48 hours of PCI.

Main results: At 48 hours, the primary outcome was observed in 334 of 941 patients (35%) in the ticagrelor group and 341 of 942 patients (36%) in the clopidogrel group (odds ratio [OR], 0.97; 95% confidence interval [CI], 0.80-1.17; P = .75). The primary safety outcome did not differ between groups. Minor bleeding events at 30 days were more frequently observed with ticagrelor (11%) than clopidogrel (8%) (1.54; 95% CI 1.12-2.11; P = .007).

Conclusion: Among patients undergoing elective PCI, ticagrelor was not superior to clopidogrel in reducing periprocedural myocardial necrosis. Ticagrelor did not cause increase in major bleeding compared to clopidogrel but did increase the rate of minor bleeding at 30 days.

Commentary

Standard treatment after PCI includes dual antiplatelet therapy combining adenosine diphosphate (ADP) receptor antagonist and aspirin. The newer generation thienopyridine prasugrel and the reversible direct acting oral antagonist of the ADP receptor ticagrelor, provides consistent and greater antiplatelet effect compared to clopidogrel, and are superior in reducing ischemic events when compared to clopidogrel in patients presenting with acute coronary syndrome (ACS).^1,2 Therefore, current guidelines recommend ticagrelor and prasugrel in preference to clopidogrel in patients presenting with ACS.^3,4 However, whether these findings of improved outcomes with newer agents compared to clopidogrel extends to patients with stable ischemic heart disease presenting for elective PCI is unknown.

In this context, Silvain et al investigated this clinical question and compared ticagrelor and clopidogrel by performing a well-designed multicenter randomized control trial in patients presenting with elective PCI. At 48 hours and at 30 days the composite of PCI-related type 4 myocardial infarction or major myocardial injury defined by the third universal definition⁵ was similar between the ticagrelor and clopidogrel groups. Although the incidence of major bleeding was not significantly different between the 2 groups, minor bleeding at 30 days was higher in the ticagrelor group (11%) than clopidogrel (8%) (1.54; 95% CI, 1.12-2.11, P = .007).

The strengths of this current study include the randomized design and the large number of patients enrolled with adequate power to evaluate for superiority of ticagrelor compared to clopidogrel. This was a multicenter trial in Europe with 49 participating centers from France and Czech, and the interventional technique used by the operators reflects contemporary technique with 95% use of radial or ulnar access.

There are a few important points to consider in this study. First, the primary outcome was biomarker assessed myocardial necrosis and myocardial injury, and the study was not powered to assess the hard outcomes such as death and myocardial infarction. Although there have been previous reports describing the relationship between the postprocedural myocardial necrosis with worse outcomes, the definition of myocardial necrosis post-PCI and its relationship with hard outcomes remains controversial. Second, half of the patients enrolled were on chronic clopidogrel therapy which suggests that patients with inadequate platelet inhibition with clopidogrel may be under-represented in this cohort. Third, this was an open-label study and the knowledge of agent used could have affected the study results. Finally, whether the population included represents a true high-risk population is questionable. Some of the prespecified high-risk features necessary to enter the study was relatively light, such as presence of diabetes mellitus or body mass index > 30 kg/m² compared to other criteria such as bifurcation stenting or left main stenting.

Currently, when treating patients with stable ischemic heart disease with higher risk anatomy, some operators may use ticagrelor over clopidogrel by extrapolating the study results from the ACS population. However, the results from the current study do not support the uniform use of ticagrelor in stable patients and suggests that the use of clopidogrel continues to be the standard of care. This is especially relevant considering the cost difference for the 2 agents studied. Whether there is a subgroup that benefits from ticagrelor use, such as patients with unprotected left main stenting or bifurcation stenting with 2 stent strategies, requires further investigation.

Applications for Clinical Practice

In patients presenting with stable ischemic heart disease undergoing elective PCI, ticagrelor did not lower composite of periprocedural myocardial infarction and myocardial injury at 48 hours. Clopidogrel continues to be a first line treatment after elective PCI.

Study Overview

Objective: To assess whether ticagrelor was superior to clopidogrel in reducing periprocedural myocardial necrosis in stable coronary patients undergoing elective percutaneous coronary intervention (PCI).

Design: Multicenter, open-label, and prospective randomized control trial. Setting and participants: A total of 1910 patients with indication for PCI and at least 1 high risk characteristic were randomized to either ticagrelor or clopidogrel.

Main outcome measures: The primary outcome was the composite of PCI-related type 4a or 4b myocardial infarction or major myocardial injury. The primary safety outcome was major bleeding, evaluated within 48 hours of PCI.

Main results: At 48 hours, the primary outcome was observed in 334 of 941 patients (35%) in the ticagrelor group and 341 of 942 patients (36%) in the clopidogrel group (odds ratio [OR], 0.97; 95% confidence interval [CI], 0.80-1.17; P = .75). The primary safety outcome did not differ between groups. Minor bleeding events at 30 days were more frequently observed with ticagrelor (11%) than clopidogrel (8%) (1.54; 95% CI 1.12-2.11; P = .007).

Conclusion: Among patients undergoing elective PCI, ticagrelor was not superior to clopidogrel in reducing periprocedural myocardial necrosis. Ticagrelor did not cause increase in major bleeding compared to clopidogrel but did increase the rate of minor bleeding at 30 days.

Commentary

Standard treatment after PCI includes dual antiplatelet therapy combining adenosine diphosphate (ADP) receptor antagonist and aspirin. The newer generation thienopyridine prasugrel and the reversible direct acting oral antagonist of the ADP receptor ticagrelor, provides consistent and greater antiplatelet effect compared to clopidogrel, and are superior in reducing ischemic events when compared to clopidogrel in patients presenting with acute coronary syndrome (ACS).^1,2 Therefore, current guidelines recommend ticagrelor and prasugrel in preference to clopidogrel in patients presenting with ACS.^3,4 However, whether these findings of improved outcomes with newer agents compared to clopidogrel extends to patients with stable ischemic heart disease presenting for elective PCI is unknown.

In this context, Silvain et al investigated this clinical question and compared ticagrelor and clopidogrel by performing a well-designed multicenter randomized control trial in patients presenting with elective PCI. At 48 hours and at 30 days the composite of PCI-related type 4 myocardial infarction or major myocardial injury defined by the third universal definition⁵ was similar between the ticagrelor and clopidogrel groups. Although the incidence of major bleeding was not significantly different between the 2 groups, minor bleeding at 30 days was higher in the ticagrelor group (11%) than clopidogrel (8%) (1.54; 95% CI, 1.12-2.11, P = .007).

The strengths of this current study include the randomized design and the large number of patients enrolled with adequate power to evaluate for superiority of ticagrelor compared to clopidogrel. This was a multicenter trial in Europe with 49 participating centers from France and Czech, and the interventional technique used by the operators reflects contemporary technique with 95% use of radial or ulnar access.

There are a few important points to consider in this study. First, the primary outcome was biomarker assessed myocardial necrosis and myocardial injury, and the study was not powered to assess the hard outcomes such as death and myocardial infarction. Although there have been previous reports describing the relationship between the postprocedural myocardial necrosis with worse outcomes, the definition of myocardial necrosis post-PCI and its relationship with hard outcomes remains controversial. Second, half of the patients enrolled were on chronic clopidogrel therapy which suggests that patients with inadequate platelet inhibition with clopidogrel may be under-represented in this cohort. Third, this was an open-label study and the knowledge of agent used could have affected the study results. Finally, whether the population included represents a true high-risk population is questionable. Some of the prespecified high-risk features necessary to enter the study was relatively light, such as presence of diabetes mellitus or body mass index > 30 kg/m² compared to other criteria such as bifurcation stenting or left main stenting.

Currently, when treating patients with stable ischemic heart disease with higher risk anatomy, some operators may use ticagrelor over clopidogrel by extrapolating the study results from the ACS population. However, the results from the current study do not support the uniform use of ticagrelor in stable patients and suggests that the use of clopidogrel continues to be the standard of care. This is especially relevant considering the cost difference for the 2 agents studied. Whether there is a subgroup that benefits from ticagrelor use, such as patients with unprotected left main stenting or bifurcation stenting with 2 stent strategies, requires further investigation.

Applications for Clinical Practice

In patients presenting with stable ischemic heart disease undergoing elective PCI, ticagrelor did not lower composite of periprocedural myocardial infarction and myocardial injury at 48 hours. Clopidogrel continues to be a first line treatment after elective PCI.

Study Overview

Objective: To assess whether ticagrelor was superior to clopidogrel in reducing periprocedural myocardial necrosis in stable coronary patients undergoing elective percutaneous coronary intervention (PCI).

Design: Multicenter, open-label, and prospective randomized control trial. Setting and participants: A total of 1910 patients with indication for PCI and at least 1 high risk characteristic were randomized to either ticagrelor or clopidogrel.

Main outcome measures: The primary outcome was the composite of PCI-related type 4a or 4b myocardial infarction or major myocardial injury. The primary safety outcome was major bleeding, evaluated within 48 hours of PCI.

Main results: At 48 hours, the primary outcome was observed in 334 of 941 patients (35%) in the ticagrelor group and 341 of 942 patients (36%) in the clopidogrel group (odds ratio [OR], 0.97; 95% confidence interval [CI], 0.80-1.17; P = .75). The primary safety outcome did not differ between groups. Minor bleeding events at 30 days were more frequently observed with ticagrelor (11%) than clopidogrel (8%) (1.54; 95% CI 1.12-2.11; P = .007).

Conclusion: Among patients undergoing elective PCI, ticagrelor was not superior to clopidogrel in reducing periprocedural myocardial necrosis. Ticagrelor did not cause increase in major bleeding compared to clopidogrel but did increase the rate of minor bleeding at 30 days.

Commentary

Standard treatment after PCI includes dual antiplatelet therapy combining adenosine diphosphate (ADP) receptor antagonist and aspirin. The newer generation thienopyridine prasugrel and the reversible direct acting oral antagonist of the ADP receptor ticagrelor, provides consistent and greater antiplatelet effect compared to clopidogrel, and are superior in reducing ischemic events when compared to clopidogrel in patients presenting with acute coronary syndrome (ACS).^1,2 Therefore, current guidelines recommend ticagrelor and prasugrel in preference to clopidogrel in patients presenting with ACS.^3,4 However, whether these findings of improved outcomes with newer agents compared to clopidogrel extends to patients with stable ischemic heart disease presenting for elective PCI is unknown.

In this context, Silvain et al investigated this clinical question and compared ticagrelor and clopidogrel by performing a well-designed multicenter randomized control trial in patients presenting with elective PCI. At 48 hours and at 30 days the composite of PCI-related type 4 myocardial infarction or major myocardial injury defined by the third universal definition⁵ was similar between the ticagrelor and clopidogrel groups. Although the incidence of major bleeding was not significantly different between the 2 groups, minor bleeding at 30 days was higher in the ticagrelor group (11%) than clopidogrel (8%) (1.54; 95% CI, 1.12-2.11, P = .007).

The strengths of this current study include the randomized design and the large number of patients enrolled with adequate power to evaluate for superiority of ticagrelor compared to clopidogrel. This was a multicenter trial in Europe with 49 participating centers from France and Czech, and the interventional technique used by the operators reflects contemporary technique with 95% use of radial or ulnar access.

There are a few important points to consider in this study. First, the primary outcome was biomarker assessed myocardial necrosis and myocardial injury, and the study was not powered to assess the hard outcomes such as death and myocardial infarction. Although there have been previous reports describing the relationship between the postprocedural myocardial necrosis with worse outcomes, the definition of myocardial necrosis post-PCI and its relationship with hard outcomes remains controversial. Second, half of the patients enrolled were on chronic clopidogrel therapy which suggests that patients with inadequate platelet inhibition with clopidogrel may be under-represented in this cohort. Third, this was an open-label study and the knowledge of agent used could have affected the study results. Finally, whether the population included represents a true high-risk population is questionable. Some of the prespecified high-risk features necessary to enter the study was relatively light, such as presence of diabetes mellitus or body mass index > 30 kg/m² compared to other criteria such as bifurcation stenting or left main stenting.

Currently, when treating patients with stable ischemic heart disease with higher risk anatomy, some operators may use ticagrelor over clopidogrel by extrapolating the study results from the ACS population. However, the results from the current study do not support the uniform use of ticagrelor in stable patients and suggests that the use of clopidogrel continues to be the standard of care. This is especially relevant considering the cost difference for the 2 agents studied. Whether there is a subgroup that benefits from ticagrelor use, such as patients with unprotected left main stenting or bifurcation stenting with 2 stent strategies, requires further investigation.

Applications for Clinical Practice

In patients presenting with stable ischemic heart disease undergoing elective PCI, ticagrelor did not lower composite of periprocedural myocardial infarction and myocardial injury at 48 hours. Clopidogrel continues to be a first line treatment after elective PCI.

From Stamford Hospital, Stamford, CT.

Objective: This single-center, quasi-experimental study of adult patients admitted or transferred to a medical step-down unit with alcohol withdrawal diagnoses sought to determine if symptom–triggered therapy (STT) is more effective than combined fixed-scheduled (FS) and STT in severe alcohol withdrawal.

Methods: In the preintervention group (72 episodes), patients were treated with FS and STT based on physician preference. In the postintervention group (69 episodes), providers were required to utilize only the STT protocol.

Results: Implementation of the intervention was associated with a significant reduction in average (per patient) cumulative benzodiazepine dose, from 250 mg to 96 mg (P < .001) and a decrease in average length of stay from 8.0 days to 5.1 days (P < .001). Secondary safety measures included a reduction in the proportion of patients who experienced delirium tremens from 47.5% to 22.5% (P < .001), and a reduction in intubation rates from 13.8% to 1.3% (P = .003).

Conclusion: The STT protocol proved to be more effective and safer in treating severe alcohol withdrawal patients than usual care employing STT with FS. We believe the successful implementation of a STT protocol in high-acuity patients requires frequent monitoring to assess withdrawal severity combined with appropriate and timely dosing of benzodiazepines.

Keywords: alcohol withdrawal delirium; alcohol withdrawal syndrome; treatment protocol; benzodiazepine; lorazepam.

Management of severe alcohol withdrawal and delirium tremens (DT) is challenging and requires significant resources, including close monitoring and intensive treatment, frequently in an intensive care unit (ICU).¹ Early diagnosis and therapeutic intervention are important to limit potential complications associated with DT.² Benzodiazepines are first-line therapeutic agents, but the definition of optimal use and dosing regimens has been limited, due to a lack of randomized controlled trials. In lower acuity patients admitted to a detoxification unit, systematic symptom–triggered benzodiazepine therapy (STT) has been established to be more effective than fixed-schedule (FS) dosing.^3-5 Patients treated using STT require lower total benzodiazepine dosing and achieve shorter treatment durations. However, in higher-acuity patients admitted to general medical services, analyses have not shown an advantage of STT over combined FS and STT.⁶

The purpose of this study was to determine whether implementation of STT is more effective than FS dosing combined with episodic STT in the management of hospitalized high-acuity alcohol withdrawal patients. We conducted a preintervention and postintervention quasi-experimental study in the step-down unit (SDU) of a 305-bed community teaching hospital. The study population consisted of adult inpatients 18 years or older admitted or transferred to the 12-bed SDU with alcohol withdrawal, as defined by primary or secondary International Classification of Diseases, Tenth Revision diagnoses. SDU admission criteria included patients with prior DT or those who had received multiple doses of benzodiazepines in the emergency department. In-hospital transfer to the SDU was at the physician’s discretion, if the patient required escalating doses of benzodiazepines or the use of increasing resources, such as those for behavioral emergencies. The majority of patients admitted or transferred to the SDU were assigned to medical house staff teams under hospitalist supervision, and, on occasion, under community physicians. The nurse-to-patient ratio in the SDU was 1:3.

Study groups

The preintervention group consisted of 80 successive treatment episodes involving patients admitted or transferred to the SDU from December 2, 2015, to July 1, 2017. Patients were treated based upon physician preference, consisting of a scheduled dosing regimen with additional doses as needed. The postintervention group included 80 successive treatment episodes involving patients admitted or transferred to the SDU from October 1, 2017, to March 23, 2019. The STT protocol was used in all patients in the postintervention group.

In the preintervention group, fixed, scheduled doses of lorazepam or chlordiazepoxide and as-needed lorazepam were prescribed and adjusted based upon physician judgment. Monitoring of symptom severity was scored using the revised Clinical Institute Withdrawal Assessment for Alcohol scale (CIWA-Ar). Benzodiazepine dosing occurred if the CIWA-Ar score had increased 2 or more points from the last score.

In the postintervention group, the STT protocol included the creation of a standardized physician order set for benzodiazepine “sliding scale” administration. The STT protocol allowed for escalating doses for higher withdrawal scores. Symptom severity was scored using MINDS (Minnesota Detoxification Scale) criteria.¹ Lorazepam as-needed dosing was based upon MINDS scores. A MINDS score less than 10 resulted in no medication, MINDS 10-12 required 2 mg, MINDS 13-16 required 4 mg, MINDS 17-19 required 6 mg, and MINDS 20 required 8 mg and a call to the physician. Transfer to the ICU was recommended if the MINDS score was ≥ 20 for 3 consecutive hours. Monitoring intervals occurred more frequently at 30 minutes unless the MINDS score was less than 10. After 7 days, the MINDS protocol was recommended to be discontinued, as the patient might have had iatrogenic delirium.

The STT protocol was introduced during a didactic session for the hospitalists and a separate session for internal medicine and family residents. Each registered nurse working in the SDU was trained in the use of the STT protocol and MINDS during nursing huddles.

Patients were excluded from evaluation if they were transferred to the SDU after 7 or more days in the hospital, if they had stayed in the hospital more than 30 days, were chronically on benzodiazepine therapy (to avoid confounding withdrawal symptoms), or if they left the hospital against medical advice (AMA). To avoid bias in the results, the patients with early discontinuation of treatment were included in analyses of secondary outcomes, thus resulting in all 80 episodes analyzed.

Measures and data

The primary outcome measure was benzodiazepine dose intensity, expressed in total lorazepam-equivalents. Secondary measures included average length of stay (including general medical, surgical, and ICU days), seizure incidence, DT incidence, sitter use, behavioral emergency responses, rates of leaving AMA, intubation, transfer to the ICU, and death.

Benzodiazepine dosing and length of stay were obtained from the data warehouse of the hospital’s electronic health record (EHR; Meditech). Benzodiazepine dosing was expressed in total lorazepam-equivalents, with conversion as follows: lorazepam orally and intravenously 1 mg = chlordiazepoxide 25 mg = diazepam 5 mg. All other measures were obtained from chart review of the patients’ EMR entries. The Stamford Hospital Institutional Review Board approved this study.

Analysis

Data analyses for this study were performed using SPSS version 25.0 (IBM). Categorical data were reported as frequency (count) and percent within category. Continuous data were reported as mean (SD). Categorical data were analyzed using χ² analysis; continuous data were analyzed using t-tests. A P value of .05 was considered significant for each analysis.

Results

During the preintervention period, 72 episodes (58 patients) met inclusion criteria, and 69 episodes (55 patients) met inclusion criteria during the postintervention period. Ten patients were represented in both groups. Eight preintervention episodes were excluded from the primary analysis because the patient left AMA. Eleven postintervention episodes were excluded: 9 due to patients leaving AMA, 1 due to chronic benzodiazepine usage, and 1 due to transfer to the SDU unit after 7 days. Baseline characteristics and medication use profiles of the preintervention and postintervention groups are summarized in Table 1.

Implementation of the intervention was associated with a significant reduction in average (per patient) cumulative benzodiazepine dose, from 250 mg to 96 mg (P < .001), as shown in Table 2. Average length of stay decreased from 8.0 days to 5.1 days (P < .001). Secondary safety measures were notable for a reduction in DT incidence, from 47.5% to 22.5% (P < .001), and lower rates of intubation, from 13.8% to 1.3% (P = .003). Seven-day readmission rates were 0% preintervention and 1.4% postintervention.

Discussion

We found that hospitalized patients with severe alcohol withdrawal treated with STT required fewer benzodiazepines and had a lower length of stay than patients treated with a conventional combined STT and FS regimen. Implementation of the change from the STT and FS approach to the STT approach in the SDU resulted in concerns that waiting for symptoms to appear could result in more severe withdrawal and prolonged treatment.³ To address this, the intervention included monitoring and dosing every 30 minutes, as compared to monitoring and dosing every 1 hour preintervention. In addition, a sliding-scale approach to match alcohol withdrawal score with dosage was employed in postintervention patients.

Employment of the STT protocol also resulted in decreased complications, including lower rates of DT and transfer to the ICU. This new intervention resulted in significantly decreased time required to control severe symptoms. In the preintervention phase, if a patient’s symptoms escalated despite administration of the as-needed dose of benzodiazepine, there was often a delay in administration of additional doses due to the time needed for nurses to reach a physician and subsequent placement of a new order. In the postintervention phase, the STT protocol allowed nursing staff to give benzodiazepines without delay when needed. We believe this reduced the number of calls by nursing staff to physicians requesting additional medications, and that this improved teamwork when managing these patients.

As part of the intervention, a decision was made to use the MINDS scale rather than the CIWA-Ar scale to assess withdrawal severity. This was because the CIWA-Ar has only been validated in patients with uncomplicated alcohol withdrawal syndrome and has not been researched extensively in patients requiring ICU-level care.¹ MINDS assessment has proven to be reliable and reflects severity of withdrawal. Furthermore, MINDS requires less time to administer—3 to 5 minutes vs 5 to 15 minutes for the CIWA-Ar scale. CIWA-Ar, unlike MINDS, requires subjective input from the patient, which is less reliable for higher acuity patients. Our study is unique in that it focused on high-acuity patients and it showed both a significant reduction in quantity of benzodiazepines prescribed and length of stay. Previous studies on lower acuity patients in detoxification units have confirmed that STT is more effective than a FS approach.^3-5 In patients of higher acuity, STT has not proven to be superior.

A key lesson learned was the need for proper education of nursing staff. Concurrent nursing audits were necessary to ensure that scoring was performed in an accurate and timely manner. In addition, it was challenging to predict which patients might develop DTs versus those requiring a brief inpatient stay. While there was initial concern that an STT protocol could result in underdosing, we found that patients had fewer DT episodes and fewer ICU transfers.

This study had several limitations. These include a relatively small sample size and the data being less recent. As there has been no intervening change to the therapeutic paradigm of DT treatment, the findings remain pertinent to the present time. The study employed a simple pre/post design and was conducted in a single setting. We are not aware of any temporal or local trends likely to influence these results. Admissions and transfers to the SDU for severe alcohol withdrawal were based on physician discretion. However, patient characteristics in both groups were similar (Table 1). We note that the postintervention STT protocol allowed for more frequent benzodiazepine dosing, though benzodiazepine use did decrease. Different alcohol withdrawal scores (MINDS vs. CIWA-Ar) were used for postintervention and preintervention, although previous research has shown that MINDS and CIWA-Ar scores correlate well.⁷ Finally, some patients of higher acuity and complexity were excluded, potentially limiting the generalizability of our results.

Conclusion

Our STT protocol proved to be more effective and safer in treating severe alcohol withdrawal patients than usual care employing STT with FS. We believe the successful implementation of a STT protocol in high-acuity patients also requires frequent monitoring using the MINDS scale, integrated with benzodiazepine sliding-scale dosing to match symptom severity. This bundled approach resulted in a significant reduction of benzodiazepine usage and reduced length of stay. Timely treatment of these patients also reduced the percent of patients developing DTs, and reduced intubation rates and transfers to the ICU. Further studies may be warranted at other sites to confirm the effectiveness of this STT protocol.

Corresponding author: Paul W. Huang, MD, Stamford Hospital, One Hospital Plaza, PO Box 9317, Stamford, CT 06904; [email protected].

Financial disclosures: None.

From Stamford Hospital, Stamford, CT.

Objective: This single-center, quasi-experimental study of adult patients admitted or transferred to a medical step-down unit with alcohol withdrawal diagnoses sought to determine if symptom–triggered therapy (STT) is more effective than combined fixed-scheduled (FS) and STT in severe alcohol withdrawal.

Methods: In the preintervention group (72 episodes), patients were treated with FS and STT based on physician preference. In the postintervention group (69 episodes), providers were required to utilize only the STT protocol.

Results: Implementation of the intervention was associated with a significant reduction in average (per patient) cumulative benzodiazepine dose, from 250 mg to 96 mg (P < .001) and a decrease in average length of stay from 8.0 days to 5.1 days (P < .001). Secondary safety measures included a reduction in the proportion of patients who experienced delirium tremens from 47.5% to 22.5% (P < .001), and a reduction in intubation rates from 13.8% to 1.3% (P = .003).

Conclusion: The STT protocol proved to be more effective and safer in treating severe alcohol withdrawal patients than usual care employing STT with FS. We believe the successful implementation of a STT protocol in high-acuity patients requires frequent monitoring to assess withdrawal severity combined with appropriate and timely dosing of benzodiazepines.

Keywords: alcohol withdrawal delirium; alcohol withdrawal syndrome; treatment protocol; benzodiazepine; lorazepam.

Management of severe alcohol withdrawal and delirium tremens (DT) is challenging and requires significant resources, including close monitoring and intensive treatment, frequently in an intensive care unit (ICU).¹ Early diagnosis and therapeutic intervention are important to limit potential complications associated with DT.² Benzodiazepines are first-line therapeutic agents, but the definition of optimal use and dosing regimens has been limited, due to a lack of randomized controlled trials. In lower acuity patients admitted to a detoxification unit, systematic symptom–triggered benzodiazepine therapy (STT) has been established to be more effective than fixed-schedule (FS) dosing.^3-5 Patients treated using STT require lower total benzodiazepine dosing and achieve shorter treatment durations. However, in higher-acuity patients admitted to general medical services, analyses have not shown an advantage of STT over combined FS and STT.⁶

The purpose of this study was to determine whether implementation of STT is more effective than FS dosing combined with episodic STT in the management of hospitalized high-acuity alcohol withdrawal patients. We conducted a preintervention and postintervention quasi-experimental study in the step-down unit (SDU) of a 305-bed community teaching hospital. The study population consisted of adult inpatients 18 years or older admitted or transferred to the 12-bed SDU with alcohol withdrawal, as defined by primary or secondary International Classification of Diseases, Tenth Revision diagnoses. SDU admission criteria included patients with prior DT or those who had received multiple doses of benzodiazepines in the emergency department. In-hospital transfer to the SDU was at the physician’s discretion, if the patient required escalating doses of benzodiazepines or the use of increasing resources, such as those for behavioral emergencies. The majority of patients admitted or transferred to the SDU were assigned to medical house staff teams under hospitalist supervision, and, on occasion, under community physicians. The nurse-to-patient ratio in the SDU was 1:3.

Study groups

The preintervention group consisted of 80 successive treatment episodes involving patients admitted or transferred to the SDU from December 2, 2015, to July 1, 2017. Patients were treated based upon physician preference, consisting of a scheduled dosing regimen with additional doses as needed. The postintervention group included 80 successive treatment episodes involving patients admitted or transferred to the SDU from October 1, 2017, to March 23, 2019. The STT protocol was used in all patients in the postintervention group.

In the preintervention group, fixed, scheduled doses of lorazepam or chlordiazepoxide and as-needed lorazepam were prescribed and adjusted based upon physician judgment. Monitoring of symptom severity was scored using the revised Clinical Institute Withdrawal Assessment for Alcohol scale (CIWA-Ar). Benzodiazepine dosing occurred if the CIWA-Ar score had increased 2 or more points from the last score.

In the postintervention group, the STT protocol included the creation of a standardized physician order set for benzodiazepine “sliding scale” administration. The STT protocol allowed for escalating doses for higher withdrawal scores. Symptom severity was scored using MINDS (Minnesota Detoxification Scale) criteria.¹ Lorazepam as-needed dosing was based upon MINDS scores. A MINDS score less than 10 resulted in no medication, MINDS 10-12 required 2 mg, MINDS 13-16 required 4 mg, MINDS 17-19 required 6 mg, and MINDS 20 required 8 mg and a call to the physician. Transfer to the ICU was recommended if the MINDS score was ≥ 20 for 3 consecutive hours. Monitoring intervals occurred more frequently at 30 minutes unless the MINDS score was less than 10. After 7 days, the MINDS protocol was recommended to be discontinued, as the patient might have had iatrogenic delirium.

The STT protocol was introduced during a didactic session for the hospitalists and a separate session for internal medicine and family residents. Each registered nurse working in the SDU was trained in the use of the STT protocol and MINDS during nursing huddles.

Patients were excluded from evaluation if they were transferred to the SDU after 7 or more days in the hospital, if they had stayed in the hospital more than 30 days, were chronically on benzodiazepine therapy (to avoid confounding withdrawal symptoms), or if they left the hospital against medical advice (AMA). To avoid bias in the results, the patients with early discontinuation of treatment were included in analyses of secondary outcomes, thus resulting in all 80 episodes analyzed.

Measures and data

The primary outcome measure was benzodiazepine dose intensity, expressed in total lorazepam-equivalents. Secondary measures included average length of stay (including general medical, surgical, and ICU days), seizure incidence, DT incidence, sitter use, behavioral emergency responses, rates of leaving AMA, intubation, transfer to the ICU, and death.

Benzodiazepine dosing and length of stay were obtained from the data warehouse of the hospital’s electronic health record (EHR; Meditech). Benzodiazepine dosing was expressed in total lorazepam-equivalents, with conversion as follows: lorazepam orally and intravenously 1 mg = chlordiazepoxide 25 mg = diazepam 5 mg. All other measures were obtained from chart review of the patients’ EMR entries. The Stamford Hospital Institutional Review Board approved this study.

Analysis

Data analyses for this study were performed using SPSS version 25.0 (IBM). Categorical data were reported as frequency (count) and percent within category. Continuous data were reported as mean (SD). Categorical data were analyzed using χ² analysis; continuous data were analyzed using t-tests. A P value of .05 was considered significant for each analysis.

Results

During the preintervention period, 72 episodes (58 patients) met inclusion criteria, and 69 episodes (55 patients) met inclusion criteria during the postintervention period. Ten patients were represented in both groups. Eight preintervention episodes were excluded from the primary analysis because the patient left AMA. Eleven postintervention episodes were excluded: 9 due to patients leaving AMA, 1 due to chronic benzodiazepine usage, and 1 due to transfer to the SDU unit after 7 days. Baseline characteristics and medication use profiles of the preintervention and postintervention groups are summarized in Table 1.

Implementation of the intervention was associated with a significant reduction in average (per patient) cumulative benzodiazepine dose, from 250 mg to 96 mg (P < .001), as shown in Table 2. Average length of stay decreased from 8.0 days to 5.1 days (P < .001). Secondary safety measures were notable for a reduction in DT incidence, from 47.5% to 22.5% (P < .001), and lower rates of intubation, from 13.8% to 1.3% (P = .003). Seven-day readmission rates were 0% preintervention and 1.4% postintervention.

Discussion

We found that hospitalized patients with severe alcohol withdrawal treated with STT required fewer benzodiazepines and had a lower length of stay than patients treated with a conventional combined STT and FS regimen. Implementation of the change from the STT and FS approach to the STT approach in the SDU resulted in concerns that waiting for symptoms to appear could result in more severe withdrawal and prolonged treatment.³ To address this, the intervention included monitoring and dosing every 30 minutes, as compared to monitoring and dosing every 1 hour preintervention. In addition, a sliding-scale approach to match alcohol withdrawal score with dosage was employed in postintervention patients.

Employment of the STT protocol also resulted in decreased complications, including lower rates of DT and transfer to the ICU. This new intervention resulted in significantly decreased time required to control severe symptoms. In the preintervention phase, if a patient’s symptoms escalated despite administration of the as-needed dose of benzodiazepine, there was often a delay in administration of additional doses due to the time needed for nurses to reach a physician and subsequent placement of a new order. In the postintervention phase, the STT protocol allowed nursing staff to give benzodiazepines without delay when needed. We believe this reduced the number of calls by nursing staff to physicians requesting additional medications, and that this improved teamwork when managing these patients.

As part of the intervention, a decision was made to use the MINDS scale rather than the CIWA-Ar scale to assess withdrawal severity. This was because the CIWA-Ar has only been validated in patients with uncomplicated alcohol withdrawal syndrome and has not been researched extensively in patients requiring ICU-level care.¹ MINDS assessment has proven to be reliable and reflects severity of withdrawal. Furthermore, MINDS requires less time to administer—3 to 5 minutes vs 5 to 15 minutes for the CIWA-Ar scale. CIWA-Ar, unlike MINDS, requires subjective input from the patient, which is less reliable for higher acuity patients. Our study is unique in that it focused on high-acuity patients and it showed both a significant reduction in quantity of benzodiazepines prescribed and length of stay. Previous studies on lower acuity patients in detoxification units have confirmed that STT is more effective than a FS approach.^3-5 In patients of higher acuity, STT has not proven to be superior.

A key lesson learned was the need for proper education of nursing staff. Concurrent nursing audits were necessary to ensure that scoring was performed in an accurate and timely manner. In addition, it was challenging to predict which patients might develop DTs versus those requiring a brief inpatient stay. While there was initial concern that an STT protocol could result in underdosing, we found that patients had fewer DT episodes and fewer ICU transfers.

This study had several limitations. These include a relatively small sample size and the data being less recent. As there has been no intervening change to the therapeutic paradigm of DT treatment, the findings remain pertinent to the present time. The study employed a simple pre/post design and was conducted in a single setting. We are not aware of any temporal or local trends likely to influence these results. Admissions and transfers to the SDU for severe alcohol withdrawal were based on physician discretion. However, patient characteristics in both groups were similar (Table 1). We note that the postintervention STT protocol allowed for more frequent benzodiazepine dosing, though benzodiazepine use did decrease. Different alcohol withdrawal scores (MINDS vs. CIWA-Ar) were used for postintervention and preintervention, although previous research has shown that MINDS and CIWA-Ar scores correlate well.⁷ Finally, some patients of higher acuity and complexity were excluded, potentially limiting the generalizability of our results.

Conclusion

Our STT protocol proved to be more effective and safer in treating severe alcohol withdrawal patients than usual care employing STT with FS. We believe the successful implementation of a STT protocol in high-acuity patients also requires frequent monitoring using the MINDS scale, integrated with benzodiazepine sliding-scale dosing to match symptom severity. This bundled approach resulted in a significant reduction of benzodiazepine usage and reduced length of stay. Timely treatment of these patients also reduced the percent of patients developing DTs, and reduced intubation rates and transfers to the ICU. Further studies may be warranted at other sites to confirm the effectiveness of this STT protocol.

Corresponding author: Paul W. Huang, MD, Stamford Hospital, One Hospital Plaza, PO Box 9317, Stamford, CT 06904; [email protected].

Financial disclosures: None.

From Stamford Hospital, Stamford, CT.

Objective: This single-center, quasi-experimental study of adult patients admitted or transferred to a medical step-down unit with alcohol withdrawal diagnoses sought to determine if symptom–triggered therapy (STT) is more effective than combined fixed-scheduled (FS) and STT in severe alcohol withdrawal.

Methods: In the preintervention group (72 episodes), patients were treated with FS and STT based on physician preference. In the postintervention group (69 episodes), providers were required to utilize only the STT protocol.

Results: Implementation of the intervention was associated with a significant reduction in average (per patient) cumulative benzodiazepine dose, from 250 mg to 96 mg (P < .001) and a decrease in average length of stay from 8.0 days to 5.1 days (P < .001). Secondary safety measures included a reduction in the proportion of patients who experienced delirium tremens from 47.5% to 22.5% (P < .001), and a reduction in intubation rates from 13.8% to 1.3% (P = .003).

Conclusion: The STT protocol proved to be more effective and safer in treating severe alcohol withdrawal patients than usual care employing STT with FS. We believe the successful implementation of a STT protocol in high-acuity patients requires frequent monitoring to assess withdrawal severity combined with appropriate and timely dosing of benzodiazepines.

Keywords: alcohol withdrawal delirium; alcohol withdrawal syndrome; treatment protocol; benzodiazepine; lorazepam.

Management of severe alcohol withdrawal and delirium tremens (DT) is challenging and requires significant resources, including close monitoring and intensive treatment, frequently in an intensive care unit (ICU).¹ Early diagnosis and therapeutic intervention are important to limit potential complications associated with DT.² Benzodiazepines are first-line therapeutic agents, but the definition of optimal use and dosing regimens has been limited, due to a lack of randomized controlled trials. In lower acuity patients admitted to a detoxification unit, systematic symptom–triggered benzodiazepine therapy (STT) has been established to be more effective than fixed-schedule (FS) dosing.^3-5 Patients treated using STT require lower total benzodiazepine dosing and achieve shorter treatment durations. However, in higher-acuity patients admitted to general medical services, analyses have not shown an advantage of STT over combined FS and STT.⁶

The purpose of this study was to determine whether implementation of STT is more effective than FS dosing combined with episodic STT in the management of hospitalized high-acuity alcohol withdrawal patients. We conducted a preintervention and postintervention quasi-experimental study in the step-down unit (SDU) of a 305-bed community teaching hospital. The study population consisted of adult inpatients 18 years or older admitted or transferred to the 12-bed SDU with alcohol withdrawal, as defined by primary or secondary International Classification of Diseases, Tenth Revision diagnoses. SDU admission criteria included patients with prior DT or those who had received multiple doses of benzodiazepines in the emergency department. In-hospital transfer to the SDU was at the physician’s discretion, if the patient required escalating doses of benzodiazepines or the use of increasing resources, such as those for behavioral emergencies. The majority of patients admitted or transferred to the SDU were assigned to medical house staff teams under hospitalist supervision, and, on occasion, under community physicians. The nurse-to-patient ratio in the SDU was 1:3.

Study groups

The preintervention group consisted of 80 successive treatment episodes involving patients admitted or transferred to the SDU from December 2, 2015, to July 1, 2017. Patients were treated based upon physician preference, consisting of a scheduled dosing regimen with additional doses as needed. The postintervention group included 80 successive treatment episodes involving patients admitted or transferred to the SDU from October 1, 2017, to March 23, 2019. The STT protocol was used in all patients in the postintervention group.

In the preintervention group, fixed, scheduled doses of lorazepam or chlordiazepoxide and as-needed lorazepam were prescribed and adjusted based upon physician judgment. Monitoring of symptom severity was scored using the revised Clinical Institute Withdrawal Assessment for Alcohol scale (CIWA-Ar). Benzodiazepine dosing occurred if the CIWA-Ar score had increased 2 or more points from the last score.

In the postintervention group, the STT protocol included the creation of a standardized physician order set for benzodiazepine “sliding scale” administration. The STT protocol allowed for escalating doses for higher withdrawal scores. Symptom severity was scored using MINDS (Minnesota Detoxification Scale) criteria.¹ Lorazepam as-needed dosing was based upon MINDS scores. A MINDS score less than 10 resulted in no medication, MINDS 10-12 required 2 mg, MINDS 13-16 required 4 mg, MINDS 17-19 required 6 mg, and MINDS 20 required 8 mg and a call to the physician. Transfer to the ICU was recommended if the MINDS score was ≥ 20 for 3 consecutive hours. Monitoring intervals occurred more frequently at 30 minutes unless the MINDS score was less than 10. After 7 days, the MINDS protocol was recommended to be discontinued, as the patient might have had iatrogenic delirium.

The STT protocol was introduced during a didactic session for the hospitalists and a separate session for internal medicine and family residents. Each registered nurse working in the SDU was trained in the use of the STT protocol and MINDS during nursing huddles.

Patients were excluded from evaluation if they were transferred to the SDU after 7 or more days in the hospital, if they had stayed in the hospital more than 30 days, were chronically on benzodiazepine therapy (to avoid confounding withdrawal symptoms), or if they left the hospital against medical advice (AMA). To avoid bias in the results, the patients with early discontinuation of treatment were included in analyses of secondary outcomes, thus resulting in all 80 episodes analyzed.

Measures and data

The primary outcome measure was benzodiazepine dose intensity, expressed in total lorazepam-equivalents. Secondary measures included average length of stay (including general medical, surgical, and ICU days), seizure incidence, DT incidence, sitter use, behavioral emergency responses, rates of leaving AMA, intubation, transfer to the ICU, and death.

Benzodiazepine dosing and length of stay were obtained from the data warehouse of the hospital’s electronic health record (EHR; Meditech). Benzodiazepine dosing was expressed in total lorazepam-equivalents, with conversion as follows: lorazepam orally and intravenously 1 mg = chlordiazepoxide 25 mg = diazepam 5 mg. All other measures were obtained from chart review of the patients’ EMR entries. The Stamford Hospital Institutional Review Board approved this study.

Analysis

Data analyses for this study were performed using SPSS version 25.0 (IBM). Categorical data were reported as frequency (count) and percent within category. Continuous data were reported as mean (SD). Categorical data were analyzed using χ² analysis; continuous data were analyzed using t-tests. A P value of .05 was considered significant for each analysis.

Results

During the preintervention period, 72 episodes (58 patients) met inclusion criteria, and 69 episodes (55 patients) met inclusion criteria during the postintervention period. Ten patients were represented in both groups. Eight preintervention episodes were excluded from the primary analysis because the patient left AMA. Eleven postintervention episodes were excluded: 9 due to patients leaving AMA, 1 due to chronic benzodiazepine usage, and 1 due to transfer to the SDU unit after 7 days. Baseline characteristics and medication use profiles of the preintervention and postintervention groups are summarized in Table 1.

Implementation of the intervention was associated with a significant reduction in average (per patient) cumulative benzodiazepine dose, from 250 mg to 96 mg (P < .001), as shown in Table 2. Average length of stay decreased from 8.0 days to 5.1 days (P < .001). Secondary safety measures were notable for a reduction in DT incidence, from 47.5% to 22.5% (P < .001), and lower rates of intubation, from 13.8% to 1.3% (P = .003). Seven-day readmission rates were 0% preintervention and 1.4% postintervention.

Discussion

We found that hospitalized patients with severe alcohol withdrawal treated with STT required fewer benzodiazepines and had a lower length of stay than patients treated with a conventional combined STT and FS regimen. Implementation of the change from the STT and FS approach to the STT approach in the SDU resulted in concerns that waiting for symptoms to appear could result in more severe withdrawal and prolonged treatment.³ To address this, the intervention included monitoring and dosing every 30 minutes, as compared to monitoring and dosing every 1 hour preintervention. In addition, a sliding-scale approach to match alcohol withdrawal score with dosage was employed in postintervention patients.

Employment of the STT protocol also resulted in decreased complications, including lower rates of DT and transfer to the ICU. This new intervention resulted in significantly decreased time required to control severe symptoms. In the preintervention phase, if a patient’s symptoms escalated despite administration of the as-needed dose of benzodiazepine, there was often a delay in administration of additional doses due to the time needed for nurses to reach a physician and subsequent placement of a new order. In the postintervention phase, the STT protocol allowed nursing staff to give benzodiazepines without delay when needed. We believe this reduced the number of calls by nursing staff to physicians requesting additional medications, and that this improved teamwork when managing these patients.

As part of the intervention, a decision was made to use the MINDS scale rather than the CIWA-Ar scale to assess withdrawal severity. This was because the CIWA-Ar has only been validated in patients with uncomplicated alcohol withdrawal syndrome and has not been researched extensively in patients requiring ICU-level care.¹ MINDS assessment has proven to be reliable and reflects severity of withdrawal. Furthermore, MINDS requires less time to administer—3 to 5 minutes vs 5 to 15 minutes for the CIWA-Ar scale. CIWA-Ar, unlike MINDS, requires subjective input from the patient, which is less reliable for higher acuity patients. Our study is unique in that it focused on high-acuity patients and it showed both a significant reduction in quantity of benzodiazepines prescribed and length of stay. Previous studies on lower acuity patients in detoxification units have confirmed that STT is more effective than a FS approach.^3-5 In patients of higher acuity, STT has not proven to be superior.

A key lesson learned was the need for proper education of nursing staff. Concurrent nursing audits were necessary to ensure that scoring was performed in an accurate and timely manner. In addition, it was challenging to predict which patients might develop DTs versus those requiring a brief inpatient stay. While there was initial concern that an STT protocol could result in underdosing, we found that patients had fewer DT episodes and fewer ICU transfers.

This study had several limitations. These include a relatively small sample size and the data being less recent. As there has been no intervening change to the therapeutic paradigm of DT treatment, the findings remain pertinent to the present time. The study employed a simple pre/post design and was conducted in a single setting. We are not aware of any temporal or local trends likely to influence these results. Admissions and transfers to the SDU for severe alcohol withdrawal were based on physician discretion. However, patient characteristics in both groups were similar (Table 1). We note that the postintervention STT protocol allowed for more frequent benzodiazepine dosing, though benzodiazepine use did decrease. Different alcohol withdrawal scores (MINDS vs. CIWA-Ar) were used for postintervention and preintervention, although previous research has shown that MINDS and CIWA-Ar scores correlate well.⁷ Finally, some patients of higher acuity and complexity were excluded, potentially limiting the generalizability of our results.

Conclusion

Our STT protocol proved to be more effective and safer in treating severe alcohol withdrawal patients than usual care employing STT with FS. We believe the successful implementation of a STT protocol in high-acuity patients also requires frequent monitoring using the MINDS scale, integrated with benzodiazepine sliding-scale dosing to match symptom severity. This bundled approach resulted in a significant reduction of benzodiazepine usage and reduced length of stay. Timely treatment of these patients also reduced the percent of patients developing DTs, and reduced intubation rates and transfers to the ICU. Further studies may be warranted at other sites to confirm the effectiveness of this STT protocol.

Corresponding author: Paul W. Huang, MD, Stamford Hospital, One Hospital Plaza, PO Box 9317, Stamford, CT 06904; [email protected].

Financial disclosures: None.