Geriatrics

Study Overview

Objective. The objective of this study was to evaluate orders and documentation describing perioperative management of code status in adults.

Design. A retrospective case series of all adult inpatients admitted to hospitals at 1 academic health system in the US.

Setting and participants. This retrospective case series was conducted at 5 hospitals within the University of Pennsylvania Health System. Cases included all adult inpatients admitted to hospitals between March 2017 and September 2018 who had a Do-Not-Resuscitate (DNR) order placed in their medical record during admission and subsequently underwent a surgical procedure that required anesthesia care.

Main outcome measures. Medical records of included cases were manually reviewed by the authors to verify whether a DNR order was in place at the time surgical intervention was discussed with a patient. Clinical notes and DNR orders of eligible cases were reviewed to identify documentation and outcome of goals of care discussions that were conducted within 48 hours prior to the surgical procedure. Collected data included patient demographics (age, sex, race); case characteristics (American Society of Anesthesiologists [ASA] physical status score, anesthesia type [general vs others such as regional], emergency status [emergent vs elective surgery], procedures by service [surgical including hip fracture repair, gastrostomy or jejunostomy, or exploratory laparotomy vs medical including endoscopy, bronchoscopy, or transesophageal echocardiogram]); and hospital policy for perioperative management of DNR orders (written policy encouraging discussion vs written policy plus additional initiatives, including procedure-specific DNR form). The primary outcome was the presence of a preoperative order or note documenting code status discussion or change. Data were analyzed using χ² and Fisher exact tests and the threshold for statistical significance was P < .05.

Main results. Of the 27 665 inpatient procedures identified across 5 hospitals, 444 (1.6%) cases met the inclusion criteria. Patients from these cases aged 75 (SD 13) years (95% CI, 72-77 years); 247 (56%, 95% CI, 55%-57%) were women; and 300 (68%, 95% CI, 65%-71%) were White. A total of 426 patients (96%, 95% CI, 90%-100%) had an ASA physical status score of 3 or higher and 237 (53%, 95% CI, 51%-56%) received general anesthesia. The most common procedures performed were endoscopy (148 [33%]), hip fracture repair (43 [10%]), and gastrostomy or jejunostomy (28 [6%]). Reevaluation of code status was documented in 126 cases (28%, 95% CI, 25%-31%); code status orders were changed in 20 of 126 cases (16%, 95% CI, 7%-24%); and a note was filed without a corresponding order for 106 of 126 cases (84%, 95% CI, 75%-95%). In the majority of cases (109 of 126 [87%], 95% CI, 78%-95%) in which documented discussion occurred, DNR orders were suspended. Of 126 cases in which a discussion was documented, participants of these discussions included surgeons 10% of the time (13 cases, 95% CI, 8%-13%), members of the anesthesia team 51% of the time (64 cases, 95% CI, 49%-53%), and medicine or palliative care clinicians 39% of the time (49 cases, 95% CI, 37%-41%).

The rate of documented preoperative code status discussion was higher in patients with higher ASA physical status score (35% in patients with an ASA physical status score ≥ 4 [55 of 155] vs 25% in those with an ASA physical status score ≤ 3 [71 of 289]; P = .02). The rates of documented preoperative code status discussion were similar by anesthesia type (29% for general anesthesia [69 of 237 cases] vs 28% [57 of 207 cases] for other modalities; P = .70). The hospitals involved in this study all had a written policy encouraging rediscussion of code status before surgery. However, only 1 hospital reported added measures (eg, provision of a procedure-specific DNR form) to increase documentation of preoperative code status discussions. In this specific hospital, documentation of preoperative code status discussions was higher compared to other hospitals (67% [37 of 55 cases] vs 23% [89 of 389 cases]; P < .01).

Conclusion. In a retrospective case series conducted at 5 hospitals within 1 academic health system in the US, fewer than 1 in 5 patients with preexisting DNR orders had a documented discussion of code status prior to undergoing surgery. Additional strategies including the development of institutional protocols that facilitate perioperative management of advance directives, identification of local champions, and patient education, should be explored as means to improve preoperative code status reevaulation per guideline recommendations.

It is not unusual that patients with a DNR order may require and undergo surgical interventions to treat reversible conditions, prevent progression of underlying disease, or mitigate distressing symptoms such as pain. For instance, intubation, mechanical ventilation, and administration of vasoactive drugs are resuscitative measures that may be needed to safely anesthetize and sedate a patient. As such, the American College of Surgeons¹ has provided a statement on advance directives by patients with an existing DNR order to guide management. Specifically, the statement indicates that the best approach for these patients is a policy of “required reconsideration” of the existing DNR order. Required reconsideration means that “the patient or designated surrogate and the physicians who will be responsible for the patient’s care should, when possible, discuss the new intraoperative and perioperative risks associated with the surgical procedure, the patient’s treatment goals, and an approach for potentially life-threatening problems consistent with the patient’s values and preferences.” Moreover, the required reconsideration discussion needs to occur as early as it is practical once a decision is made to have surgery because the discussion “may result in the patient agreeing to suspend the DNR order during surgery and the perioperative period, retaining the original DNR order, or modifying the DNR order.” Given that surgical patients with DNR orders have significant comorbidities, many sustain postoperative complications, and nearly 1 in 4 die within 30 days of surgery, preoperative advance care planning (ACP) and code status discussions are particularly essential to delivering high quality surgical care.²

In the current study, Hadler et al³ conducted a retrospective analysis to evaluate orders and documentation describing perioperative management of code status in patients with existing DNR order at an academic health system in the US. The authors reported that fewer than 20% of patients with existing DNR orders had a documented discussion of code status prior to undergoing surgery. These findings add to the notion that compliance with such guidance on required reconsideration discussion is suboptimal in perioperative care in the US.^4,5 A recently published study focused on patients aged more than 60 years undergoing high-risk oncologic or vascular surgeries similarly showed that the frequency of ACP discussions or advance directive documentations among older patients was low.⁶ This growing body of evidence is highly clinically relevant in that preoperative discussion on code status is highly relevant to the care of older adults, a population group that accounts for the majority of surgeries and is most vulnerable to poor surgical outcomes. Additionally, it highlights a disconnect between the shared recognition by surgeons and patients that ACP discussion is important in perioperative care and its low implementation rates.

Unsurprisingly, Hadler et al³ reported that added measures such as the provision of a procedure-specific DNR form led to an increase in the documentation of preoperative code status discussions in 1 of the hospitals studied. The authors suggested that strategies such as the development of institutional protocols aimed to facilitate perioperative advance directive discussions, identify local champions, and educate patients may be ways to improve preoperative code status reevaulation. The idea that institutional value and culture are key factors impacting surgeon behavior and may influence the practice of ACP discussion is not new. Thus, creative and adaptable strategies, resources, and trainings that are required by medical institutions and hospitals to support preoperative ACP discussions with patients undergoing surgeries need to be identified, validated, and implemented to optimize perioperative care in vulnerable patients.

Applications for Clinical Practice

The findings from the current study indicate that less than 20% of patients with preexisting DNR orders have a documented discussion of code status prior to undergoing surgery. Physicians and health care institutions need to identify barriers to, and implement strategies that, facilitate and optimize preoperative ACP discussions in order to provide patient-centered care in vulnerable surgical patients.

Financial disclosures: None.

Study Overview

Objective. The objective of this study was to evaluate orders and documentation describing perioperative management of code status in adults.

Design. A retrospective case series of all adult inpatients admitted to hospitals at 1 academic health system in the US.

Setting and participants. This retrospective case series was conducted at 5 hospitals within the University of Pennsylvania Health System. Cases included all adult inpatients admitted to hospitals between March 2017 and September 2018 who had a Do-Not-Resuscitate (DNR) order placed in their medical record during admission and subsequently underwent a surgical procedure that required anesthesia care.

Main outcome measures. Medical records of included cases were manually reviewed by the authors to verify whether a DNR order was in place at the time surgical intervention was discussed with a patient. Clinical notes and DNR orders of eligible cases were reviewed to identify documentation and outcome of goals of care discussions that were conducted within 48 hours prior to the surgical procedure. Collected data included patient demographics (age, sex, race); case characteristics (American Society of Anesthesiologists [ASA] physical status score, anesthesia type [general vs others such as regional], emergency status [emergent vs elective surgery], procedures by service [surgical including hip fracture repair, gastrostomy or jejunostomy, or exploratory laparotomy vs medical including endoscopy, bronchoscopy, or transesophageal echocardiogram]); and hospital policy for perioperative management of DNR orders (written policy encouraging discussion vs written policy plus additional initiatives, including procedure-specific DNR form). The primary outcome was the presence of a preoperative order or note documenting code status discussion or change. Data were analyzed using χ² and Fisher exact tests and the threshold for statistical significance was P < .05.

Main results. Of the 27 665 inpatient procedures identified across 5 hospitals, 444 (1.6%) cases met the inclusion criteria. Patients from these cases aged 75 (SD 13) years (95% CI, 72-77 years); 247 (56%, 95% CI, 55%-57%) were women; and 300 (68%, 95% CI, 65%-71%) were White. A total of 426 patients (96%, 95% CI, 90%-100%) had an ASA physical status score of 3 or higher and 237 (53%, 95% CI, 51%-56%) received general anesthesia. The most common procedures performed were endoscopy (148 [33%]), hip fracture repair (43 [10%]), and gastrostomy or jejunostomy (28 [6%]). Reevaluation of code status was documented in 126 cases (28%, 95% CI, 25%-31%); code status orders were changed in 20 of 126 cases (16%, 95% CI, 7%-24%); and a note was filed without a corresponding order for 106 of 126 cases (84%, 95% CI, 75%-95%). In the majority of cases (109 of 126 [87%], 95% CI, 78%-95%) in which documented discussion occurred, DNR orders were suspended. Of 126 cases in which a discussion was documented, participants of these discussions included surgeons 10% of the time (13 cases, 95% CI, 8%-13%), members of the anesthesia team 51% of the time (64 cases, 95% CI, 49%-53%), and medicine or palliative care clinicians 39% of the time (49 cases, 95% CI, 37%-41%).

The rate of documented preoperative code status discussion was higher in patients with higher ASA physical status score (35% in patients with an ASA physical status score ≥ 4 [55 of 155] vs 25% in those with an ASA physical status score ≤ 3 [71 of 289]; P = .02). The rates of documented preoperative code status discussion were similar by anesthesia type (29% for general anesthesia [69 of 237 cases] vs 28% [57 of 207 cases] for other modalities; P = .70). The hospitals involved in this study all had a written policy encouraging rediscussion of code status before surgery. However, only 1 hospital reported added measures (eg, provision of a procedure-specific DNR form) to increase documentation of preoperative code status discussions. In this specific hospital, documentation of preoperative code status discussions was higher compared to other hospitals (67% [37 of 55 cases] vs 23% [89 of 389 cases]; P < .01).

Conclusion. In a retrospective case series conducted at 5 hospitals within 1 academic health system in the US, fewer than 1 in 5 patients with preexisting DNR orders had a documented discussion of code status prior to undergoing surgery. Additional strategies including the development of institutional protocols that facilitate perioperative management of advance directives, identification of local champions, and patient education, should be explored as means to improve preoperative code status reevaulation per guideline recommendations.

It is not unusual that patients with a DNR order may require and undergo surgical interventions to treat reversible conditions, prevent progression of underlying disease, or mitigate distressing symptoms such as pain. For instance, intubation, mechanical ventilation, and administration of vasoactive drugs are resuscitative measures that may be needed to safely anesthetize and sedate a patient. As such, the American College of Surgeons¹ has provided a statement on advance directives by patients with an existing DNR order to guide management. Specifically, the statement indicates that the best approach for these patients is a policy of “required reconsideration” of the existing DNR order. Required reconsideration means that “the patient or designated surrogate and the physicians who will be responsible for the patient’s care should, when possible, discuss the new intraoperative and perioperative risks associated with the surgical procedure, the patient’s treatment goals, and an approach for potentially life-threatening problems consistent with the patient’s values and preferences.” Moreover, the required reconsideration discussion needs to occur as early as it is practical once a decision is made to have surgery because the discussion “may result in the patient agreeing to suspend the DNR order during surgery and the perioperative period, retaining the original DNR order, or modifying the DNR order.” Given that surgical patients with DNR orders have significant comorbidities, many sustain postoperative complications, and nearly 1 in 4 die within 30 days of surgery, preoperative advance care planning (ACP) and code status discussions are particularly essential to delivering high quality surgical care.²

In the current study, Hadler et al³ conducted a retrospective analysis to evaluate orders and documentation describing perioperative management of code status in patients with existing DNR order at an academic health system in the US. The authors reported that fewer than 20% of patients with existing DNR orders had a documented discussion of code status prior to undergoing surgery. These findings add to the notion that compliance with such guidance on required reconsideration discussion is suboptimal in perioperative care in the US.^4,5 A recently published study focused on patients aged more than 60 years undergoing high-risk oncologic or vascular surgeries similarly showed that the frequency of ACP discussions or advance directive documentations among older patients was low.⁶ This growing body of evidence is highly clinically relevant in that preoperative discussion on code status is highly relevant to the care of older adults, a population group that accounts for the majority of surgeries and is most vulnerable to poor surgical outcomes. Additionally, it highlights a disconnect between the shared recognition by surgeons and patients that ACP discussion is important in perioperative care and its low implementation rates.

Unsurprisingly, Hadler et al³ reported that added measures such as the provision of a procedure-specific DNR form led to an increase in the documentation of preoperative code status discussions in 1 of the hospitals studied. The authors suggested that strategies such as the development of institutional protocols aimed to facilitate perioperative advance directive discussions, identify local champions, and educate patients may be ways to improve preoperative code status reevaulation. The idea that institutional value and culture are key factors impacting surgeon behavior and may influence the practice of ACP discussion is not new. Thus, creative and adaptable strategies, resources, and trainings that are required by medical institutions and hospitals to support preoperative ACP discussions with patients undergoing surgeries need to be identified, validated, and implemented to optimize perioperative care in vulnerable patients.

Applications for Clinical Practice

The findings from the current study indicate that less than 20% of patients with preexisting DNR orders have a documented discussion of code status prior to undergoing surgery. Physicians and health care institutions need to identify barriers to, and implement strategies that, facilitate and optimize preoperative ACP discussions in order to provide patient-centered care in vulnerable surgical patients.

Financial disclosures: None.

Study Overview

Objective. The objective of this study was to evaluate orders and documentation describing perioperative management of code status in adults.

Design. A retrospective case series of all adult inpatients admitted to hospitals at 1 academic health system in the US.

Setting and participants. This retrospective case series was conducted at 5 hospitals within the University of Pennsylvania Health System. Cases included all adult inpatients admitted to hospitals between March 2017 and September 2018 who had a Do-Not-Resuscitate (DNR) order placed in their medical record during admission and subsequently underwent a surgical procedure that required anesthesia care.

Main outcome measures. Medical records of included cases were manually reviewed by the authors to verify whether a DNR order was in place at the time surgical intervention was discussed with a patient. Clinical notes and DNR orders of eligible cases were reviewed to identify documentation and outcome of goals of care discussions that were conducted within 48 hours prior to the surgical procedure. Collected data included patient demographics (age, sex, race); case characteristics (American Society of Anesthesiologists [ASA] physical status score, anesthesia type [general vs others such as regional], emergency status [emergent vs elective surgery], procedures by service [surgical including hip fracture repair, gastrostomy or jejunostomy, or exploratory laparotomy vs medical including endoscopy, bronchoscopy, or transesophageal echocardiogram]); and hospital policy for perioperative management of DNR orders (written policy encouraging discussion vs written policy plus additional initiatives, including procedure-specific DNR form). The primary outcome was the presence of a preoperative order or note documenting code status discussion or change. Data were analyzed using χ² and Fisher exact tests and the threshold for statistical significance was P < .05.

Main results. Of the 27 665 inpatient procedures identified across 5 hospitals, 444 (1.6%) cases met the inclusion criteria. Patients from these cases aged 75 (SD 13) years (95% CI, 72-77 years); 247 (56%, 95% CI, 55%-57%) were women; and 300 (68%, 95% CI, 65%-71%) were White. A total of 426 patients (96%, 95% CI, 90%-100%) had an ASA physical status score of 3 or higher and 237 (53%, 95% CI, 51%-56%) received general anesthesia. The most common procedures performed were endoscopy (148 [33%]), hip fracture repair (43 [10%]), and gastrostomy or jejunostomy (28 [6%]). Reevaluation of code status was documented in 126 cases (28%, 95% CI, 25%-31%); code status orders were changed in 20 of 126 cases (16%, 95% CI, 7%-24%); and a note was filed without a corresponding order for 106 of 126 cases (84%, 95% CI, 75%-95%). In the majority of cases (109 of 126 [87%], 95% CI, 78%-95%) in which documented discussion occurred, DNR orders were suspended. Of 126 cases in which a discussion was documented, participants of these discussions included surgeons 10% of the time (13 cases, 95% CI, 8%-13%), members of the anesthesia team 51% of the time (64 cases, 95% CI, 49%-53%), and medicine or palliative care clinicians 39% of the time (49 cases, 95% CI, 37%-41%).

The rate of documented preoperative code status discussion was higher in patients with higher ASA physical status score (35% in patients with an ASA physical status score ≥ 4 [55 of 155] vs 25% in those with an ASA physical status score ≤ 3 [71 of 289]; P = .02). The rates of documented preoperative code status discussion were similar by anesthesia type (29% for general anesthesia [69 of 237 cases] vs 28% [57 of 207 cases] for other modalities; P = .70). The hospitals involved in this study all had a written policy encouraging rediscussion of code status before surgery. However, only 1 hospital reported added measures (eg, provision of a procedure-specific DNR form) to increase documentation of preoperative code status discussions. In this specific hospital, documentation of preoperative code status discussions was higher compared to other hospitals (67% [37 of 55 cases] vs 23% [89 of 389 cases]; P < .01).

Conclusion. In a retrospective case series conducted at 5 hospitals within 1 academic health system in the US, fewer than 1 in 5 patients with preexisting DNR orders had a documented discussion of code status prior to undergoing surgery. Additional strategies including the development of institutional protocols that facilitate perioperative management of advance directives, identification of local champions, and patient education, should be explored as means to improve preoperative code status reevaulation per guideline recommendations.

It is not unusual that patients with a DNR order may require and undergo surgical interventions to treat reversible conditions, prevent progression of underlying disease, or mitigate distressing symptoms such as pain. For instance, intubation, mechanical ventilation, and administration of vasoactive drugs are resuscitative measures that may be needed to safely anesthetize and sedate a patient. As such, the American College of Surgeons¹ has provided a statement on advance directives by patients with an existing DNR order to guide management. Specifically, the statement indicates that the best approach for these patients is a policy of “required reconsideration” of the existing DNR order. Required reconsideration means that “the patient or designated surrogate and the physicians who will be responsible for the patient’s care should, when possible, discuss the new intraoperative and perioperative risks associated with the surgical procedure, the patient’s treatment goals, and an approach for potentially life-threatening problems consistent with the patient’s values and preferences.” Moreover, the required reconsideration discussion needs to occur as early as it is practical once a decision is made to have surgery because the discussion “may result in the patient agreeing to suspend the DNR order during surgery and the perioperative period, retaining the original DNR order, or modifying the DNR order.” Given that surgical patients with DNR orders have significant comorbidities, many sustain postoperative complications, and nearly 1 in 4 die within 30 days of surgery, preoperative advance care planning (ACP) and code status discussions are particularly essential to delivering high quality surgical care.²

In the current study, Hadler et al³ conducted a retrospective analysis to evaluate orders and documentation describing perioperative management of code status in patients with existing DNR order at an academic health system in the US. The authors reported that fewer than 20% of patients with existing DNR orders had a documented discussion of code status prior to undergoing surgery. These findings add to the notion that compliance with such guidance on required reconsideration discussion is suboptimal in perioperative care in the US.^4,5 A recently published study focused on patients aged more than 60 years undergoing high-risk oncologic or vascular surgeries similarly showed that the frequency of ACP discussions or advance directive documentations among older patients was low.⁶ This growing body of evidence is highly clinically relevant in that preoperative discussion on code status is highly relevant to the care of older adults, a population group that accounts for the majority of surgeries and is most vulnerable to poor surgical outcomes. Additionally, it highlights a disconnect between the shared recognition by surgeons and patients that ACP discussion is important in perioperative care and its low implementation rates.

Unsurprisingly, Hadler et al³ reported that added measures such as the provision of a procedure-specific DNR form led to an increase in the documentation of preoperative code status discussions in 1 of the hospitals studied. The authors suggested that strategies such as the development of institutional protocols aimed to facilitate perioperative advance directive discussions, identify local champions, and educate patients may be ways to improve preoperative code status reevaulation. The idea that institutional value and culture are key factors impacting surgeon behavior and may influence the practice of ACP discussion is not new. Thus, creative and adaptable strategies, resources, and trainings that are required by medical institutions and hospitals to support preoperative ACP discussions with patients undergoing surgeries need to be identified, validated, and implemented to optimize perioperative care in vulnerable patients.

Applications for Clinical Practice

The findings from the current study indicate that less than 20% of patients with preexisting DNR orders have a documented discussion of code status prior to undergoing surgery. Physicians and health care institutions need to identify barriers to, and implement strategies that, facilitate and optimize preoperative ACP discussions in order to provide patient-centered care in vulnerable surgical patients.

Financial disclosures: None.

From the Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA (Drs. Ching, Darwish, Li, Wong, Simpson, and Funk), the Department of Anesthesia, Cedars-Sinai Medical Center, Los Angeles, CA (Keith Siegel), and the Department of Psychiatry, Cedars-Sinai Medical Center, Los Angeles, CA (Dr. Bamgbose).

Objectives: To reduce the incidence and duration of delirium among patients in a hospital ward through standardized delirium screening tools and nonpharmacologic interventions. To advance nursing-focused education on delirium-prevention strategies. To measure the efficacy of the interventions with the aim of reproducing best practices.

Background: Delirium is associated with poor patient outcomes but may be preventable in a significant percentage of hospitalized patients.

Methods: Following nursing-focused education to prevent delirium, we prospectively evaluated patient care outcomes in a consecutive series of patients who were admitted to a hospital medical-surgical ward within a 25-week period. All patients who had at least 1 Confusion Assessment Method (CAM) documented by a nurse during hospitalization met our inclusion criteria (N = 353). Standards for Quality Improvement Reporting Excellence guidelines were adhered to.

Results: There were 187 patients in the control group, and 166 in the postintervention group. Compared to the control group, the postintervention group had a significant decrease in the incidence of delirium during hospitalization (14.4% vs 4.2%) and a significant decrease in the mean percentage of tested nursing shifts with 1 or more positive CAM (4.9% vs 1.1%). Significant differences in secondary outcomes between the control and postintervention groups included median length of stay (6 days vs 4 days), mean length of stay (8.5 days vs 5.9 days), and use of an indwelling urinary catheter (9.1% vs 2.4%).

Conclusion: A multimodal strategy involving nursing-focused training and nonpharmacologic interventions to address hospital delirium is associated with improved patient care outcomes and nursing confidence. Nurses play an integral role in the early recognition and prevention of hospital delirium, which directly translates to reducing burdens in both patient functionality and health care costs.

Delirium is a disorder characterized by inattention and acute changes in cognition. It is defined by the American Psychiatric Association’s fifth edition of the Diagnostic and Statistical Manual of Mental Disorders as a disturbance in attention, awareness, and cognition over hours to a few days that is not better explained by a preexisting, established, or other evolving neurocognitive disorder.¹ Delirium is common yet often under-recognized among hospitalized patients, particularly in the elderly. The incidence of delirium in elderly patients on admission is estimated to be 11% to 25%, and an additional 29% to 31% of elderly patients will develop delirium during the hospitalization.² Delirium costs the health care system an estimated $38 billion to $152 billion per year.³ It is associated with negative outcomes, such as increased new placements to nursing homes, increased mortality, increased risk of dementia, and further cognitive deterioration among patients with dementia.^4-6

Despite its prevalence, delirium may be preventable in a significant percentage of hospitalized patients. Targeted intervention strategies, such as frequent reorientation, maximizing sleep, early mobilization, restricting use of psychoactive medications, and addressing hearing or vision impairment, have been demonstrated to significantly reduce the incidence of hospital delirium.^7,8 To achieve these goals, we explored the use of a multimodal strategy centered on nursing education. We integrated consistent, standardized delirium screening and nonpharmacologic interventions as part of a preventative protocol to reduce the incidence of delirium in the hospital ward.

Methods

We evaluated a consecutive series of patients who were admitted to a designated hospital medical-surgical ward within a 25-week period between October 2019 and April 2020. All patients during this period who had at least 1 Confusion Assessment Method (CAM) documented by a nurse during hospitalization met our inclusion criteria. Patients who did not have a CAM documented were excluded from the analysis. Delirium was defined according to the CAM diagnostic algorithm.⁹

Core nursing staff regularly assigned to the ward completed a multimodal training program designed to improve recognition, documentation, and prevention of hospital delirium. Prior to the training, the nurses completed a 5-point Likert scale survey assessing their level of confidence with recognizing delirium risk factors, preventing delirium, addressing delirium, utilizing the CAM tool, and educating others about delirium. Nurses completed the same survey after the study period ended.

The training curriculum for nurses began with an online module reviewing the epidemiology and risk factors for delirium. Nurses then participated in a series of in-service training sessions led by a team of physicians, during which the CAM and nonpharmacologic delirium prevention measures were reviewed then practiced first-hand. Nursing staff attended an in-person lecture reviewing the current body of literature on delirium risk factors and effective nursing interventions. After formal training was completed, nurses were instructed to document CAM screens for each patient under their care at least once every 12-hour shift for the remainder of the study. An order set, reflected in Table 1, was made available to physicians and floor nurses to assist with implementing the educational components.

Patients admitted to the hospital unit from the start of the training program (week 1) until the order set was made available (week 15) constituted our control group. The postintervention study group consisted of patients admitted for 10 weeks after the completion of the interventions (weeks 16-25). A timeline of the study events is shown in Figure 1.

Patient demographics and hospital-stay metrics determined a priori were attained via the Cedars-Sinai Enterprise Information Services core. Age, sex, medical history, and incidence of surgery with anesthesia during hospitalization were recorded. The Charlson Comorbidity Index was calculated from patients’ listed diagnoses following discharge. Primary outcomes included incidence of patients with delirium during hospitalization, percentage of tested shifts with positive CAM screens, length of hospital stay, and survival. Secondary outcomes included measures associated with delirium, including the use of chemical restraints, physical restraints, sitters, indwelling urinary catheters, and new psychiatry and neurology consults. Chemical restraints were defined as administration of a new antipsychotic medication or benzodiazepine for the specific indication of hyperactive delirium or agitation.            

Statistical analysis was conducted by a statistician, using R version 3.6.3.10P values of < .05 were considered significant. Categorical variables were analyzed using Fisher’s exact test. Continuous variables were analyzed with Welch’s t-test or, for highly skewed continuous variables, with Wilcoxon rank-sum test or Mood’s median test. All patient data were anonymized and stored securely in accordance with institutional guidelines.

Our project was deemed to represent nonhuman subject research and therefore did not require Institutional Review Board (IRB) approval upon review by our institution’s IRB committee and Office of Research Compliance and Quality Improvement. Standards for Quality Improvement Reporting Excellence (SQUIRE 2.0) guidelines were adhered to (Supplementary File can be found at mdedge.com/jcomjournal).

Results

We evaluated 353 patients who met our inclusion criteria: 187 in the control group, and 166 in the postintervention group. Ten patients were readmitted to the ward after their initial discharge; only the initial admission encounters were included in our analysis. Median age, sex, median Charlson Comorbidity Index, and incidence of surgery with anesthesia during hospitalization were comparable between the control and postintervention groups and are summarized in Table 2.

In the control group, 1572 CAMs were performed, with 74 positive CAMs recorded among 27 patients with delirium. In the postintervention group, 1298 CAMs were performed, with 12 positive CAMs recorded among 7 patients with delirium (Figure 2). Primary and secondary outcomes, as well as CAM compliance measures, are summarized in Table 3.

Compared to the control group, the postintervention group had a significant decrease in the incidence of delirium during hospitalization (14.4% vs 4.2%, P = .002) and a significant decrease in the mean percentage of tested nursing shifts with 1 or more positive CAM (4.9% vs 1.1%, P = .002). Significant differences in secondary outcomes between the control and postintervention groups included median length of stay (6 days vs 4 days, P = .004), mean length of stay (8.5 days vs 5.9 days, P = .003), and use of an indwelling urinary catheter (9.1% vs 2.4%, P = .012). There was a trend towards decreased incidence of chemical restraints and psychiatry consults, which did not reach statistical significance. Differences in mortality during hospitalization, physical restraint use, and sitter use could not be assessed due to low incidence.

Results of nursing surveys completed before and after the training program are listed in Table 4. After training, nurses had a greater level of confidence with recognizing delirium risk factors, preventing delirium, addressing delirium, utilizing the CAM tool, and educating others about delirium.

Discussion

Our study utilized a standardized delirium assessment tool to compare patient cohorts before and after nurse-targeted training interventions on delirium recognition and prevention. Our interventions emphasized nonpharmacologic intervention strategies, which are recommended as first-line in the management of patients with delirium.¹¹ Patients were not excluded from the analysis based on preexisting medical conditions or recent surgery with anesthesia, to allow for conditions that are representative of community hospitals. We also did not use an inclusion criterion based on age; however, the majority of our patients were greater than 70 years old, representing those at highest risk for delirium.² Significant outcomes among patients in the postintervention group include decreased incidence of delirium, lower average length of stay, decreased indwelling urinary catheter use, and increased compliance with delirium screening by nursing staff.

While the study’s focus was primarily on delirium prevention rather than treatment, these strategies may also have conferred the benefit of reversing delirium symptoms. In addition to measuring incidence of delirium, our primary outcome of percentage of tested shifts with 1 or more positive CAM was intended to assess the overall duration in which patients had delirium during their hospitalization. The reduction in shifts with positive CAMs observed in the postintervention group is notable, given that a significant percentage of patients with hospital delirium have the potential for symptom reversibility.¹²

Multiple studies have shown that admitted patients who develop delirium experience prolonged hospital stays, often up to 5 to 10 days longer.^12-14 The decreased incidence and duration of delirium in our postintervention group is a reasonable explanation for the observed decrease in average length of stay. Our study is in line with previously documented initiatives that show that nonpharmacologic interventions can effectively address downstream health and fiscal sequelae of hospital delirium. For example, a volunteer-based initiative named the Hospital Elder Life Program, from which elements in our order set were modeled after, demonstrated significant reductions in delirium incidence, length of stay, and health care costs.^14-16 Other initiatives that focused on educational training for nurses to assess and prevent delirium have also demonstrated similar positive results.^17-19 Our study provides a model for effective nursing-focused education that can be reproduced in the hospital setting.

Unlike some other studies, which identified delirium based only on physician assessments, our initiative utilized the CAM performed by floor nurses to identify delirium. While this method may have affected the sensitivity and specificity of the CAMs, it also conferred the advantage of recognizing, documenting, and intervening on delirium in real time, given that bedside nurses are often the first to encounter delirium. Furthermore, nurses were instructed to notify a physician if a patient had a new positive CAM, as reflected in Table 1.

Our study demonstrated an increase in the overall compliance with the CAM screening during the postintervention period, which is significant given the under-recognition of delirium by health care professionals.²⁰ We attribute this increase to greater realized importance and a higher level of confidence from nursing staff in recognizing and addressing delirium, as supported by survey data. While the increased screening of patients should be considered a positive outcome, it also poses the possibility that the observed decrease in delirium incidence in the postintervention group was in fact due to more CAMs performed on patients without delirium. Likewise, nurses may have become more adept at recognizing true delirium, as opposed to delirium mimics, in the latter period of the study.

Perhaps the greatest limitation of our study is the variability in performing and recording CAMs, as some patients had multiple CAMs recorded while others did not have any CAMs recorded. This may have been affected in part by the increase in COVID-19 cases in our hospital towards the latter half of the study, which resulted in changes in nursing assignments as well as patient comorbidities in ways that cannot be easily quantified. Given the limited size of our patient cohorts, certain outcomes, such as the use of sitters, physical restraints, and in-hospital mortality, were unable to be assessed for changes statistically. Causative relationships between our interventions and associated outcome measures are necessarily limited in a binary comparison between control and postintervention groups.

Within these limitations, our study demonstrates promising results in core dimensions of patient care. We anticipate further quality improvement initiatives involving greater numbers of nursing staff and patients to better quantify the impact of nonpharmacologic nursing-centered interventions for preventing hospital delirium.

Conclusion

A multimodal strategy involving nursing-focused training and nonpharmacologic interventions to address hospital delirium is associated with improved patient care outcomes and nursing confidence. Nurses play an integral role in the early recognition and prevention of hospital delirium, which directly translates to reducing burdens in both patient functionality and health care costs. Education and tools to equip nurses to perform standardized delirium screening and interventions should be prioritized.

Acknowledgment: The authors thanks Olena Svetlov, NP, Oscar Abarca, Jose Chavez, and Jenita Gutierrez.

Corresponding author: Jason Ching, MD, Department of Neurology, Cedars-Sinai Medical Center, 8700 Beverly Blvd, Los Angeles, CA 90048; [email protected].

Financial disclosures: None.

Funding: This research was supported by NIH National Center for Advancing Translational Science (NCATS) UCLA CTSI Grant Number UL1TR001881.

From the Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA (Drs. Ching, Darwish, Li, Wong, Simpson, and Funk), the Department of Anesthesia, Cedars-Sinai Medical Center, Los Angeles, CA (Keith Siegel), and the Department of Psychiatry, Cedars-Sinai Medical Center, Los Angeles, CA (Dr. Bamgbose).

Objectives: To reduce the incidence and duration of delirium among patients in a hospital ward through standardized delirium screening tools and nonpharmacologic interventions. To advance nursing-focused education on delirium-prevention strategies. To measure the efficacy of the interventions with the aim of reproducing best practices.

Background: Delirium is associated with poor patient outcomes but may be preventable in a significant percentage of hospitalized patients.

Methods: Following nursing-focused education to prevent delirium, we prospectively evaluated patient care outcomes in a consecutive series of patients who were admitted to a hospital medical-surgical ward within a 25-week period. All patients who had at least 1 Confusion Assessment Method (CAM) documented by a nurse during hospitalization met our inclusion criteria (N = 353). Standards for Quality Improvement Reporting Excellence guidelines were adhered to.

Results: There were 187 patients in the control group, and 166 in the postintervention group. Compared to the control group, the postintervention group had a significant decrease in the incidence of delirium during hospitalization (14.4% vs 4.2%) and a significant decrease in the mean percentage of tested nursing shifts with 1 or more positive CAM (4.9% vs 1.1%). Significant differences in secondary outcomes between the control and postintervention groups included median length of stay (6 days vs 4 days), mean length of stay (8.5 days vs 5.9 days), and use of an indwelling urinary catheter (9.1% vs 2.4%).

Conclusion: A multimodal strategy involving nursing-focused training and nonpharmacologic interventions to address hospital delirium is associated with improved patient care outcomes and nursing confidence. Nurses play an integral role in the early recognition and prevention of hospital delirium, which directly translates to reducing burdens in both patient functionality and health care costs.

Delirium is a disorder characterized by inattention and acute changes in cognition. It is defined by the American Psychiatric Association’s fifth edition of the Diagnostic and Statistical Manual of Mental Disorders as a disturbance in attention, awareness, and cognition over hours to a few days that is not better explained by a preexisting, established, or other evolving neurocognitive disorder.¹ Delirium is common yet often under-recognized among hospitalized patients, particularly in the elderly. The incidence of delirium in elderly patients on admission is estimated to be 11% to 25%, and an additional 29% to 31% of elderly patients will develop delirium during the hospitalization.² Delirium costs the health care system an estimated $38 billion to $152 billion per year.³ It is associated with negative outcomes, such as increased new placements to nursing homes, increased mortality, increased risk of dementia, and further cognitive deterioration among patients with dementia.^4-6

Despite its prevalence, delirium may be preventable in a significant percentage of hospitalized patients. Targeted intervention strategies, such as frequent reorientation, maximizing sleep, early mobilization, restricting use of psychoactive medications, and addressing hearing or vision impairment, have been demonstrated to significantly reduce the incidence of hospital delirium.^7,8 To achieve these goals, we explored the use of a multimodal strategy centered on nursing education. We integrated consistent, standardized delirium screening and nonpharmacologic interventions as part of a preventative protocol to reduce the incidence of delirium in the hospital ward.

Methods

We evaluated a consecutive series of patients who were admitted to a designated hospital medical-surgical ward within a 25-week period between October 2019 and April 2020. All patients during this period who had at least 1 Confusion Assessment Method (CAM) documented by a nurse during hospitalization met our inclusion criteria. Patients who did not have a CAM documented were excluded from the analysis. Delirium was defined according to the CAM diagnostic algorithm.⁹

Core nursing staff regularly assigned to the ward completed a multimodal training program designed to improve recognition, documentation, and prevention of hospital delirium. Prior to the training, the nurses completed a 5-point Likert scale survey assessing their level of confidence with recognizing delirium risk factors, preventing delirium, addressing delirium, utilizing the CAM tool, and educating others about delirium. Nurses completed the same survey after the study period ended.

The training curriculum for nurses began with an online module reviewing the epidemiology and risk factors for delirium. Nurses then participated in a series of in-service training sessions led by a team of physicians, during which the CAM and nonpharmacologic delirium prevention measures were reviewed then practiced first-hand. Nursing staff attended an in-person lecture reviewing the current body of literature on delirium risk factors and effective nursing interventions. After formal training was completed, nurses were instructed to document CAM screens for each patient under their care at least once every 12-hour shift for the remainder of the study. An order set, reflected in Table 1, was made available to physicians and floor nurses to assist with implementing the educational components.

Patients admitted to the hospital unit from the start of the training program (week 1) until the order set was made available (week 15) constituted our control group. The postintervention study group consisted of patients admitted for 10 weeks after the completion of the interventions (weeks 16-25). A timeline of the study events is shown in Figure 1.

Patient demographics and hospital-stay metrics determined a priori were attained via the Cedars-Sinai Enterprise Information Services core. Age, sex, medical history, and incidence of surgery with anesthesia during hospitalization were recorded. The Charlson Comorbidity Index was calculated from patients’ listed diagnoses following discharge. Primary outcomes included incidence of patients with delirium during hospitalization, percentage of tested shifts with positive CAM screens, length of hospital stay, and survival. Secondary outcomes included measures associated with delirium, including the use of chemical restraints, physical restraints, sitters, indwelling urinary catheters, and new psychiatry and neurology consults. Chemical restraints were defined as administration of a new antipsychotic medication or benzodiazepine for the specific indication of hyperactive delirium or agitation.            

Statistical analysis was conducted by a statistician, using R version 3.6.3.10P values of < .05 were considered significant. Categorical variables were analyzed using Fisher’s exact test. Continuous variables were analyzed with Welch’s t-test or, for highly skewed continuous variables, with Wilcoxon rank-sum test or Mood’s median test. All patient data were anonymized and stored securely in accordance with institutional guidelines.

Our project was deemed to represent nonhuman subject research and therefore did not require Institutional Review Board (IRB) approval upon review by our institution’s IRB committee and Office of Research Compliance and Quality Improvement. Standards for Quality Improvement Reporting Excellence (SQUIRE 2.0) guidelines were adhered to (Supplementary File can be found at mdedge.com/jcomjournal).

Results

We evaluated 353 patients who met our inclusion criteria: 187 in the control group, and 166 in the postintervention group. Ten patients were readmitted to the ward after their initial discharge; only the initial admission encounters were included in our analysis. Median age, sex, median Charlson Comorbidity Index, and incidence of surgery with anesthesia during hospitalization were comparable between the control and postintervention groups and are summarized in Table 2.

In the control group, 1572 CAMs were performed, with 74 positive CAMs recorded among 27 patients with delirium. In the postintervention group, 1298 CAMs were performed, with 12 positive CAMs recorded among 7 patients with delirium (Figure 2). Primary and secondary outcomes, as well as CAM compliance measures, are summarized in Table 3.

Compared to the control group, the postintervention group had a significant decrease in the incidence of delirium during hospitalization (14.4% vs 4.2%, P = .002) and a significant decrease in the mean percentage of tested nursing shifts with 1 or more positive CAM (4.9% vs 1.1%, P = .002). Significant differences in secondary outcomes between the control and postintervention groups included median length of stay (6 days vs 4 days, P = .004), mean length of stay (8.5 days vs 5.9 days, P = .003), and use of an indwelling urinary catheter (9.1% vs 2.4%, P = .012). There was a trend towards decreased incidence of chemical restraints and psychiatry consults, which did not reach statistical significance. Differences in mortality during hospitalization, physical restraint use, and sitter use could not be assessed due to low incidence.

Results of nursing surveys completed before and after the training program are listed in Table 4. After training, nurses had a greater level of confidence with recognizing delirium risk factors, preventing delirium, addressing delirium, utilizing the CAM tool, and educating others about delirium.

Discussion

Our study utilized a standardized delirium assessment tool to compare patient cohorts before and after nurse-targeted training interventions on delirium recognition and prevention. Our interventions emphasized nonpharmacologic intervention strategies, which are recommended as first-line in the management of patients with delirium.¹¹ Patients were not excluded from the analysis based on preexisting medical conditions or recent surgery with anesthesia, to allow for conditions that are representative of community hospitals. We also did not use an inclusion criterion based on age; however, the majority of our patients were greater than 70 years old, representing those at highest risk for delirium.² Significant outcomes among patients in the postintervention group include decreased incidence of delirium, lower average length of stay, decreased indwelling urinary catheter use, and increased compliance with delirium screening by nursing staff.

While the study’s focus was primarily on delirium prevention rather than treatment, these strategies may also have conferred the benefit of reversing delirium symptoms. In addition to measuring incidence of delirium, our primary outcome of percentage of tested shifts with 1 or more positive CAM was intended to assess the overall duration in which patients had delirium during their hospitalization. The reduction in shifts with positive CAMs observed in the postintervention group is notable, given that a significant percentage of patients with hospital delirium have the potential for symptom reversibility.¹²

Multiple studies have shown that admitted patients who develop delirium experience prolonged hospital stays, often up to 5 to 10 days longer.^12-14 The decreased incidence and duration of delirium in our postintervention group is a reasonable explanation for the observed decrease in average length of stay. Our study is in line with previously documented initiatives that show that nonpharmacologic interventions can effectively address downstream health and fiscal sequelae of hospital delirium. For example, a volunteer-based initiative named the Hospital Elder Life Program, from which elements in our order set were modeled after, demonstrated significant reductions in delirium incidence, length of stay, and health care costs.^14-16 Other initiatives that focused on educational training for nurses to assess and prevent delirium have also demonstrated similar positive results.^17-19 Our study provides a model for effective nursing-focused education that can be reproduced in the hospital setting.

Unlike some other studies, which identified delirium based only on physician assessments, our initiative utilized the CAM performed by floor nurses to identify delirium. While this method may have affected the sensitivity and specificity of the CAMs, it also conferred the advantage of recognizing, documenting, and intervening on delirium in real time, given that bedside nurses are often the first to encounter delirium. Furthermore, nurses were instructed to notify a physician if a patient had a new positive CAM, as reflected in Table 1.

Our study demonstrated an increase in the overall compliance with the CAM screening during the postintervention period, which is significant given the under-recognition of delirium by health care professionals.²⁰ We attribute this increase to greater realized importance and a higher level of confidence from nursing staff in recognizing and addressing delirium, as supported by survey data. While the increased screening of patients should be considered a positive outcome, it also poses the possibility that the observed decrease in delirium incidence in the postintervention group was in fact due to more CAMs performed on patients without delirium. Likewise, nurses may have become more adept at recognizing true delirium, as opposed to delirium mimics, in the latter period of the study.

Perhaps the greatest limitation of our study is the variability in performing and recording CAMs, as some patients had multiple CAMs recorded while others did not have any CAMs recorded. This may have been affected in part by the increase in COVID-19 cases in our hospital towards the latter half of the study, which resulted in changes in nursing assignments as well as patient comorbidities in ways that cannot be easily quantified. Given the limited size of our patient cohorts, certain outcomes, such as the use of sitters, physical restraints, and in-hospital mortality, were unable to be assessed for changes statistically. Causative relationships between our interventions and associated outcome measures are necessarily limited in a binary comparison between control and postintervention groups.

Within these limitations, our study demonstrates promising results in core dimensions of patient care. We anticipate further quality improvement initiatives involving greater numbers of nursing staff and patients to better quantify the impact of nonpharmacologic nursing-centered interventions for preventing hospital delirium.

Conclusion

A multimodal strategy involving nursing-focused training and nonpharmacologic interventions to address hospital delirium is associated with improved patient care outcomes and nursing confidence. Nurses play an integral role in the early recognition and prevention of hospital delirium, which directly translates to reducing burdens in both patient functionality and health care costs. Education and tools to equip nurses to perform standardized delirium screening and interventions should be prioritized.

Acknowledgment: The authors thanks Olena Svetlov, NP, Oscar Abarca, Jose Chavez, and Jenita Gutierrez.

Corresponding author: Jason Ching, MD, Department of Neurology, Cedars-Sinai Medical Center, 8700 Beverly Blvd, Los Angeles, CA 90048; [email protected].

Financial disclosures: None.

Funding: This research was supported by NIH National Center for Advancing Translational Science (NCATS) UCLA CTSI Grant Number UL1TR001881.

From the Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA (Drs. Ching, Darwish, Li, Wong, Simpson, and Funk), the Department of Anesthesia, Cedars-Sinai Medical Center, Los Angeles, CA (Keith Siegel), and the Department of Psychiatry, Cedars-Sinai Medical Center, Los Angeles, CA (Dr. Bamgbose).

Objectives: To reduce the incidence and duration of delirium among patients in a hospital ward through standardized delirium screening tools and nonpharmacologic interventions. To advance nursing-focused education on delirium-prevention strategies. To measure the efficacy of the interventions with the aim of reproducing best practices.

Background: Delirium is associated with poor patient outcomes but may be preventable in a significant percentage of hospitalized patients.

Methods: Following nursing-focused education to prevent delirium, we prospectively evaluated patient care outcomes in a consecutive series of patients who were admitted to a hospital medical-surgical ward within a 25-week period. All patients who had at least 1 Confusion Assessment Method (CAM) documented by a nurse during hospitalization met our inclusion criteria (N = 353). Standards for Quality Improvement Reporting Excellence guidelines were adhered to.

Results: There were 187 patients in the control group, and 166 in the postintervention group. Compared to the control group, the postintervention group had a significant decrease in the incidence of delirium during hospitalization (14.4% vs 4.2%) and a significant decrease in the mean percentage of tested nursing shifts with 1 or more positive CAM (4.9% vs 1.1%). Significant differences in secondary outcomes between the control and postintervention groups included median length of stay (6 days vs 4 days), mean length of stay (8.5 days vs 5.9 days), and use of an indwelling urinary catheter (9.1% vs 2.4%).

Conclusion: A multimodal strategy involving nursing-focused training and nonpharmacologic interventions to address hospital delirium is associated with improved patient care outcomes and nursing confidence. Nurses play an integral role in the early recognition and prevention of hospital delirium, which directly translates to reducing burdens in both patient functionality and health care costs.

Delirium is a disorder characterized by inattention and acute changes in cognition. It is defined by the American Psychiatric Association’s fifth edition of the Diagnostic and Statistical Manual of Mental Disorders as a disturbance in attention, awareness, and cognition over hours to a few days that is not better explained by a preexisting, established, or other evolving neurocognitive disorder.¹ Delirium is common yet often under-recognized among hospitalized patients, particularly in the elderly. The incidence of delirium in elderly patients on admission is estimated to be 11% to 25%, and an additional 29% to 31% of elderly patients will develop delirium during the hospitalization.² Delirium costs the health care system an estimated $38 billion to $152 billion per year.³ It is associated with negative outcomes, such as increased new placements to nursing homes, increased mortality, increased risk of dementia, and further cognitive deterioration among patients with dementia.^4-6

Despite its prevalence, delirium may be preventable in a significant percentage of hospitalized patients. Targeted intervention strategies, such as frequent reorientation, maximizing sleep, early mobilization, restricting use of psychoactive medications, and addressing hearing or vision impairment, have been demonstrated to significantly reduce the incidence of hospital delirium.^7,8 To achieve these goals, we explored the use of a multimodal strategy centered on nursing education. We integrated consistent, standardized delirium screening and nonpharmacologic interventions as part of a preventative protocol to reduce the incidence of delirium in the hospital ward.

Methods

We evaluated a consecutive series of patients who were admitted to a designated hospital medical-surgical ward within a 25-week period between October 2019 and April 2020. All patients during this period who had at least 1 Confusion Assessment Method (CAM) documented by a nurse during hospitalization met our inclusion criteria. Patients who did not have a CAM documented were excluded from the analysis. Delirium was defined according to the CAM diagnostic algorithm.⁹

Core nursing staff regularly assigned to the ward completed a multimodal training program designed to improve recognition, documentation, and prevention of hospital delirium. Prior to the training, the nurses completed a 5-point Likert scale survey assessing their level of confidence with recognizing delirium risk factors, preventing delirium, addressing delirium, utilizing the CAM tool, and educating others about delirium. Nurses completed the same survey after the study period ended.

The training curriculum for nurses began with an online module reviewing the epidemiology and risk factors for delirium. Nurses then participated in a series of in-service training sessions led by a team of physicians, during which the CAM and nonpharmacologic delirium prevention measures were reviewed then practiced first-hand. Nursing staff attended an in-person lecture reviewing the current body of literature on delirium risk factors and effective nursing interventions. After formal training was completed, nurses were instructed to document CAM screens for each patient under their care at least once every 12-hour shift for the remainder of the study. An order set, reflected in Table 1, was made available to physicians and floor nurses to assist with implementing the educational components.

Patients admitted to the hospital unit from the start of the training program (week 1) until the order set was made available (week 15) constituted our control group. The postintervention study group consisted of patients admitted for 10 weeks after the completion of the interventions (weeks 16-25). A timeline of the study events is shown in Figure 1.

Patient demographics and hospital-stay metrics determined a priori were attained via the Cedars-Sinai Enterprise Information Services core. Age, sex, medical history, and incidence of surgery with anesthesia during hospitalization were recorded. The Charlson Comorbidity Index was calculated from patients’ listed diagnoses following discharge. Primary outcomes included incidence of patients with delirium during hospitalization, percentage of tested shifts with positive CAM screens, length of hospital stay, and survival. Secondary outcomes included measures associated with delirium, including the use of chemical restraints, physical restraints, sitters, indwelling urinary catheters, and new psychiatry and neurology consults. Chemical restraints were defined as administration of a new antipsychotic medication or benzodiazepine for the specific indication of hyperactive delirium or agitation.            

Statistical analysis was conducted by a statistician, using R version 3.6.3.10P values of < .05 were considered significant. Categorical variables were analyzed using Fisher’s exact test. Continuous variables were analyzed with Welch’s t-test or, for highly skewed continuous variables, with Wilcoxon rank-sum test or Mood’s median test. All patient data were anonymized and stored securely in accordance with institutional guidelines.

Our project was deemed to represent nonhuman subject research and therefore did not require Institutional Review Board (IRB) approval upon review by our institution’s IRB committee and Office of Research Compliance and Quality Improvement. Standards for Quality Improvement Reporting Excellence (SQUIRE 2.0) guidelines were adhered to (Supplementary File can be found at mdedge.com/jcomjournal).

Results

We evaluated 353 patients who met our inclusion criteria: 187 in the control group, and 166 in the postintervention group. Ten patients were readmitted to the ward after their initial discharge; only the initial admission encounters were included in our analysis. Median age, sex, median Charlson Comorbidity Index, and incidence of surgery with anesthesia during hospitalization were comparable between the control and postintervention groups and are summarized in Table 2.

In the control group, 1572 CAMs were performed, with 74 positive CAMs recorded among 27 patients with delirium. In the postintervention group, 1298 CAMs were performed, with 12 positive CAMs recorded among 7 patients with delirium (Figure 2). Primary and secondary outcomes, as well as CAM compliance measures, are summarized in Table 3.

Compared to the control group, the postintervention group had a significant decrease in the incidence of delirium during hospitalization (14.4% vs 4.2%, P = .002) and a significant decrease in the mean percentage of tested nursing shifts with 1 or more positive CAM (4.9% vs 1.1%, P = .002). Significant differences in secondary outcomes between the control and postintervention groups included median length of stay (6 days vs 4 days, P = .004), mean length of stay (8.5 days vs 5.9 days, P = .003), and use of an indwelling urinary catheter (9.1% vs 2.4%, P = .012). There was a trend towards decreased incidence of chemical restraints and psychiatry consults, which did not reach statistical significance. Differences in mortality during hospitalization, physical restraint use, and sitter use could not be assessed due to low incidence.

Results of nursing surveys completed before and after the training program are listed in Table 4. After training, nurses had a greater level of confidence with recognizing delirium risk factors, preventing delirium, addressing delirium, utilizing the CAM tool, and educating others about delirium.

Discussion

Our study utilized a standardized delirium assessment tool to compare patient cohorts before and after nurse-targeted training interventions on delirium recognition and prevention. Our interventions emphasized nonpharmacologic intervention strategies, which are recommended as first-line in the management of patients with delirium.¹¹ Patients were not excluded from the analysis based on preexisting medical conditions or recent surgery with anesthesia, to allow for conditions that are representative of community hospitals. We also did not use an inclusion criterion based on age; however, the majority of our patients were greater than 70 years old, representing those at highest risk for delirium.² Significant outcomes among patients in the postintervention group include decreased incidence of delirium, lower average length of stay, decreased indwelling urinary catheter use, and increased compliance with delirium screening by nursing staff.

While the study’s focus was primarily on delirium prevention rather than treatment, these strategies may also have conferred the benefit of reversing delirium symptoms. In addition to measuring incidence of delirium, our primary outcome of percentage of tested shifts with 1 or more positive CAM was intended to assess the overall duration in which patients had delirium during their hospitalization. The reduction in shifts with positive CAMs observed in the postintervention group is notable, given that a significant percentage of patients with hospital delirium have the potential for symptom reversibility.¹²

Multiple studies have shown that admitted patients who develop delirium experience prolonged hospital stays, often up to 5 to 10 days longer.^12-14 The decreased incidence and duration of delirium in our postintervention group is a reasonable explanation for the observed decrease in average length of stay. Our study is in line with previously documented initiatives that show that nonpharmacologic interventions can effectively address downstream health and fiscal sequelae of hospital delirium. For example, a volunteer-based initiative named the Hospital Elder Life Program, from which elements in our order set were modeled after, demonstrated significant reductions in delirium incidence, length of stay, and health care costs.^14-16 Other initiatives that focused on educational training for nurses to assess and prevent delirium have also demonstrated similar positive results.^17-19 Our study provides a model for effective nursing-focused education that can be reproduced in the hospital setting.

Unlike some other studies, which identified delirium based only on physician assessments, our initiative utilized the CAM performed by floor nurses to identify delirium. While this method may have affected the sensitivity and specificity of the CAMs, it also conferred the advantage of recognizing, documenting, and intervening on delirium in real time, given that bedside nurses are often the first to encounter delirium. Furthermore, nurses were instructed to notify a physician if a patient had a new positive CAM, as reflected in Table 1.

Our study demonstrated an increase in the overall compliance with the CAM screening during the postintervention period, which is significant given the under-recognition of delirium by health care professionals.²⁰ We attribute this increase to greater realized importance and a higher level of confidence from nursing staff in recognizing and addressing delirium, as supported by survey data. While the increased screening of patients should be considered a positive outcome, it also poses the possibility that the observed decrease in delirium incidence in the postintervention group was in fact due to more CAMs performed on patients without delirium. Likewise, nurses may have become more adept at recognizing true delirium, as opposed to delirium mimics, in the latter period of the study.

Perhaps the greatest limitation of our study is the variability in performing and recording CAMs, as some patients had multiple CAMs recorded while others did not have any CAMs recorded. This may have been affected in part by the increase in COVID-19 cases in our hospital towards the latter half of the study, which resulted in changes in nursing assignments as well as patient comorbidities in ways that cannot be easily quantified. Given the limited size of our patient cohorts, certain outcomes, such as the use of sitters, physical restraints, and in-hospital mortality, were unable to be assessed for changes statistically. Causative relationships between our interventions and associated outcome measures are necessarily limited in a binary comparison between control and postintervention groups.

Within these limitations, our study demonstrates promising results in core dimensions of patient care. We anticipate further quality improvement initiatives involving greater numbers of nursing staff and patients to better quantify the impact of nonpharmacologic nursing-centered interventions for preventing hospital delirium.

Conclusion

A multimodal strategy involving nursing-focused training and nonpharmacologic interventions to address hospital delirium is associated with improved patient care outcomes and nursing confidence. Nurses play an integral role in the early recognition and prevention of hospital delirium, which directly translates to reducing burdens in both patient functionality and health care costs. Education and tools to equip nurses to perform standardized delirium screening and interventions should be prioritized.

Acknowledgment: The authors thanks Olena Svetlov, NP, Oscar Abarca, Jose Chavez, and Jenita Gutierrez.

Corresponding author: Jason Ching, MD, Department of Neurology, Cedars-Sinai Medical Center, 8700 Beverly Blvd, Los Angeles, CA 90048; [email protected].

Financial disclosures: None.

Funding: This research was supported by NIH National Center for Advancing Translational Science (NCATS) UCLA CTSI Grant Number UL1TR001881.

When you have to help a parent choose a nursing home or you need nursing home care yourself, you can consult a health care professional, talk to friends, or look at the Nursing Home Compare website of the Centers for Medicare and Medicaid Services (CMS). The CMS website includes star ratings for each nursing home, both overall and on health inspections, staffing and certain quality measures.

But what you might not know is what financial incentives a particular nursing home might have to provide high-quality care, depending on what kind of entity owns the facility.

A study published Nov. 19 in JAMA Health Forum throws light on at least one aspect of the ownership question: What happens when a private equity (PE) firm acquires a nursing home? According to the study, you can expect a somewhat lower level of quality in a PE-owned nursing home than in other for-profit facilities.

The researchers compared CMS data on 302 nursing homes owned by 79 PE firms to data on 9,562 for-profit facilities not owned by such companies from 2013 to 2017. Among fee-for-service Medicare patients in long-term care, private equity acquisitions of nursing homes were associated with an 11.1% increase in ambulatory-care-sensitive (ACS) visits to the emergency department (ED) and an 8.7% increase in ACS hospitalizations per quarter, compared to the changes that occurred in the non-PE-owned facilities, they found.

What’s more, Medicare costs per beneficiary increased 3.9% more – or about $1,000 a year – in the PE-owned nursing homes than they did in the other cohort during the study period.

And when the acquired nursing homes were compared to the nursing homes prior to their acquisition by PE firms, there were no statistically significant differences in unadjusted outcomes, the researchers found. That means the two cohorts were broadly comparable.

The researchers adjusted the numbers in their study for various characteristics of the facilities and their residents. For example, the PE-acquired nursing homes were likely to have a higher percentage of patients covered by Medicare and a lower percentage covered by Medicaid than their non-PE counterparts.

The mean percentages of Black residents, female residents, and residents aged 85 or older were 12.4%, 65.4%, and 36.2%, respectively, for the PE-owned nursing homes and 15.7%, 67.8%, and 39%, respectively, for the non–PE-owned facilities.
 

Less than optimal outcomes

On average, the residents of non–PE-owned nursing homes had better outcomes than did the patients in the PE-owned facilities. But that doesn’t mean that the average for-profit nursing home had terrific outcomes.

For all the nursing homes in the study, the mean quarterly rate of ACS emergency department visits was 14.1%, and the mean quarterly rate of ACS hospitalizations was 17.3%.

“These events should be largely, although not completely, preventable with appropriate care,” the researchers pointed out.

To date, PE firms have invested about $750 billion in U.S. health care, with nursing homes being a major target of these companies, which currently own 5% of skilled nursing facilities, per the study. PE companies seek annual returns of 20% or more, the paper says, and thus feel pressure to generate high short-term profits. That could lead to reduced staffing, services, supplies, or equipment in their facilities.

Some nursing homes purchased by PE firms may be responsible for the debt incurred in their own leveraged buyouts, the researchers noted. There is also concern that PE firms may focus their properties disproportionately on short-term post-acute care, which is reimbursed at a higher rate than long-term care, the study says.

For all these reasons, some health policy makers are concerned about the long-term impact of private-equity nursing home acquisitions, according to the study.

A version of this article first appeared on WebMD.com.

When you have to help a parent choose a nursing home or you need nursing home care yourself, you can consult a health care professional, talk to friends, or look at the Nursing Home Compare website of the Centers for Medicare and Medicaid Services (CMS). The CMS website includes star ratings for each nursing home, both overall and on health inspections, staffing and certain quality measures.

But what you might not know is what financial incentives a particular nursing home might have to provide high-quality care, depending on what kind of entity owns the facility.

A study published Nov. 19 in JAMA Health Forum throws light on at least one aspect of the ownership question: What happens when a private equity (PE) firm acquires a nursing home? According to the study, you can expect a somewhat lower level of quality in a PE-owned nursing home than in other for-profit facilities.

The researchers compared CMS data on 302 nursing homes owned by 79 PE firms to data on 9,562 for-profit facilities not owned by such companies from 2013 to 2017. Among fee-for-service Medicare patients in long-term care, private equity acquisitions of nursing homes were associated with an 11.1% increase in ambulatory-care-sensitive (ACS) visits to the emergency department (ED) and an 8.7% increase in ACS hospitalizations per quarter, compared to the changes that occurred in the non-PE-owned facilities, they found.

What’s more, Medicare costs per beneficiary increased 3.9% more – or about $1,000 a year – in the PE-owned nursing homes than they did in the other cohort during the study period.

And when the acquired nursing homes were compared to the nursing homes prior to their acquisition by PE firms, there were no statistically significant differences in unadjusted outcomes, the researchers found. That means the two cohorts were broadly comparable.

The researchers adjusted the numbers in their study for various characteristics of the facilities and their residents. For example, the PE-acquired nursing homes were likely to have a higher percentage of patients covered by Medicare and a lower percentage covered by Medicaid than their non-PE counterparts.

The mean percentages of Black residents, female residents, and residents aged 85 or older were 12.4%, 65.4%, and 36.2%, respectively, for the PE-owned nursing homes and 15.7%, 67.8%, and 39%, respectively, for the non–PE-owned facilities.
 

Less than optimal outcomes

On average, the residents of non–PE-owned nursing homes had better outcomes than did the patients in the PE-owned facilities. But that doesn’t mean that the average for-profit nursing home had terrific outcomes.

For all the nursing homes in the study, the mean quarterly rate of ACS emergency department visits was 14.1%, and the mean quarterly rate of ACS hospitalizations was 17.3%.

“These events should be largely, although not completely, preventable with appropriate care,” the researchers pointed out.

To date, PE firms have invested about $750 billion in U.S. health care, with nursing homes being a major target of these companies, which currently own 5% of skilled nursing facilities, per the study. PE companies seek annual returns of 20% or more, the paper says, and thus feel pressure to generate high short-term profits. That could lead to reduced staffing, services, supplies, or equipment in their facilities.

Some nursing homes purchased by PE firms may be responsible for the debt incurred in their own leveraged buyouts, the researchers noted. There is also concern that PE firms may focus their properties disproportionately on short-term post-acute care, which is reimbursed at a higher rate than long-term care, the study says.

For all these reasons, some health policy makers are concerned about the long-term impact of private-equity nursing home acquisitions, according to the study.

A version of this article first appeared on WebMD.com.

When you have to help a parent choose a nursing home or you need nursing home care yourself, you can consult a health care professional, talk to friends, or look at the Nursing Home Compare website of the Centers for Medicare and Medicaid Services (CMS). The CMS website includes star ratings for each nursing home, both overall and on health inspections, staffing and certain quality measures.

But what you might not know is what financial incentives a particular nursing home might have to provide high-quality care, depending on what kind of entity owns the facility.

A study published Nov. 19 in JAMA Health Forum throws light on at least one aspect of the ownership question: What happens when a private equity (PE) firm acquires a nursing home? According to the study, you can expect a somewhat lower level of quality in a PE-owned nursing home than in other for-profit facilities.

The researchers compared CMS data on 302 nursing homes owned by 79 PE firms to data on 9,562 for-profit facilities not owned by such companies from 2013 to 2017. Among fee-for-service Medicare patients in long-term care, private equity acquisitions of nursing homes were associated with an 11.1% increase in ambulatory-care-sensitive (ACS) visits to the emergency department (ED) and an 8.7% increase in ACS hospitalizations per quarter, compared to the changes that occurred in the non-PE-owned facilities, they found.

What’s more, Medicare costs per beneficiary increased 3.9% more – or about $1,000 a year – in the PE-owned nursing homes than they did in the other cohort during the study period.

And when the acquired nursing homes were compared to the nursing homes prior to their acquisition by PE firms, there were no statistically significant differences in unadjusted outcomes, the researchers found. That means the two cohorts were broadly comparable.

The researchers adjusted the numbers in their study for various characteristics of the facilities and their residents. For example, the PE-acquired nursing homes were likely to have a higher percentage of patients covered by Medicare and a lower percentage covered by Medicaid than their non-PE counterparts.

The mean percentages of Black residents, female residents, and residents aged 85 or older were 12.4%, 65.4%, and 36.2%, respectively, for the PE-owned nursing homes and 15.7%, 67.8%, and 39%, respectively, for the non–PE-owned facilities.
 

Less than optimal outcomes

On average, the residents of non–PE-owned nursing homes had better outcomes than did the patients in the PE-owned facilities. But that doesn’t mean that the average for-profit nursing home had terrific outcomes.

For all the nursing homes in the study, the mean quarterly rate of ACS emergency department visits was 14.1%, and the mean quarterly rate of ACS hospitalizations was 17.3%.

“These events should be largely, although not completely, preventable with appropriate care,” the researchers pointed out.

To date, PE firms have invested about $750 billion in U.S. health care, with nursing homes being a major target of these companies, which currently own 5% of skilled nursing facilities, per the study. PE companies seek annual returns of 20% or more, the paper says, and thus feel pressure to generate high short-term profits. That could lead to reduced staffing, services, supplies, or equipment in their facilities.

Some nursing homes purchased by PE firms may be responsible for the debt incurred in their own leveraged buyouts, the researchers noted. There is also concern that PE firms may focus their properties disproportionately on short-term post-acute care, which is reimbursed at a higher rate than long-term care, the study says.

For all these reasons, some health policy makers are concerned about the long-term impact of private-equity nursing home acquisitions, according to the study.

A version of this article first appeared on WebMD.com.

A 64 year-old man with type 2 diabetes complains of recurrent flushing for the past 6 months. He has had no other symptoms. His only abnormalities on physical exam are a blood pressure of 160/100 and mild peripheral edema.

His current medications include: Famotidine 20 mg b.i.d., Pseudoephedrine/guaifenesin SR b.i.d., Metformin 1,000 mg twice a day, Nifedipine 60 mg XL once a day, and Atorvastatin 20 mg once a day.

His laboratory work up includes: blood urea nitrogen: 20, creatinine: 1.3, sodium: 140, Chloride: 104, potassium: 3.9, glucose: 205, white blood cell count: 6,000, hematocrit: 41, 24-hour urine 5-hydroxyindoleacetic acid (5HIAA) test: 12 mg/day (normal 2-8 mg/day), free catecholamines: 80 mg/24 hours (normal less than 100 mg/24 hours).
 

What is the most likely diagnosis?

A. Drug effect

B. Pheochromocytoma

C. Carcinoid syndrome

D. Mastocytosis

E. Medullary thyroid cancer

The most likely diagnosis is a drug effect. His flushing is likely caused by nifedipine.

Flushing is one of the most common side effects of this drug.¹ This patient had lab testing done for carcinoid (urine 5HIAA), presumably because he had flushing. This lab test result was a false positive, likely because of guaifenesin ingestion, which can cause false-positive 5HIAA results.²

Carcinoid syndrome is very rare (estimates from less than 1 patient/100,000), and the vast majority of patients who have it present with metastatic disease at presentation. Drug side effects are common, and usually are much more likely than rare diseases.
 

Four principles for assisting with making a diagnosis

This case points out the following four principles that I will touch on to help us make diagnoses in challenging cases.

1. Trigger symptoms: These are symptoms that make us think of a rare disease. In this case, the symptom is flushing, which may make you think of carcinoid syndrome.

Another good example of a trigger symptom is night sweats, where you may think of tuberculosis or lymphoma. These symptoms almost always have a much more common and likely cause, which in this case is a common drug side effect.

Trigger symptoms are great to pay attention to, but do not jump to working up the rare diagnosis without more evidence that it is a plausible diagnosis. Working up rare diseases without a reasonable pretest probability will lead to significant false-positive results.

2. Distinguishing features: These are findings, or combinations of findings, that make rarer diseases more likely. For example, flushing, although seen in many patients with carcinoid syndrome, is much more commonly caused by rosacea, medications, or estrogen/testosterone deficiency.

If a patient presents with flushing plus diarrhea, carcinoid syndrome becomes more likely in differentials. An example of a specific distinguishing feature is transient visual obstructions in patients with idiopathic intracranial hypertension (IIH or pseudotumor cerebri).

Sudden transient visual loss is not a symptom we see often, but headaches and obesity are problems we see every day. A patient with headaches and obesity is very likely to have IIH if they have transient visual obstructions along with headaches and obesity.

3. Intentional physical exams: Do the physical exam focusing on what findings will change your diagnostic probabilities. For example, in this case, if you are considering carcinoid, do a careful abdominal exam, with close attention to the liver, as 75% of patients with carcinoid syndrome have liver metastases.

If you are thinking about IIH, a fundoscopic exam is mandatory, as papilledema is a key feature of this diagnosis.

Read about the rare diagnosis you are considering, this will help with targeting your exam.

4. Remember the unusual presentation of a common disease is more common than the common presentation of a rare disease: Good examples of this are sleep apnea and gastroesophageal reflux disease causing night sweats more commonly than finding lymphomas or active tuberculosis (in the United States) as the cause.³

Pearl: Trigger symptoms help us think of rare diseases, but distinguishing features are most helpful in including or excluding the diagnosis.

Dr. Paauw is professor of medicine in the division of general internal medicine at the University of Washington, Seattle, and serves as third-year medical student clerkship director at the University of Washington. He is a member of the editorial advisory board of Internal Medicine News. Dr. Paauw has no conflicts to disclose. Contact him at [email protected].

References

1. Gueret P et al. Drugs. 1990;39 Suppl 2:67-72.

2. Corcuff J et al. Endocr Connect. 2017;6:R87.

3. Smith CS and Paauw DS. J Am Board Fam Pract. 2000;13:424-9.

A 64 year-old man with type 2 diabetes complains of recurrent flushing for the past 6 months. He has had no other symptoms. His only abnormalities on physical exam are a blood pressure of 160/100 and mild peripheral edema.

His current medications include: Famotidine 20 mg b.i.d., Pseudoephedrine/guaifenesin SR b.i.d., Metformin 1,000 mg twice a day, Nifedipine 60 mg XL once a day, and Atorvastatin 20 mg once a day.

His laboratory work up includes: blood urea nitrogen: 20, creatinine: 1.3, sodium: 140, Chloride: 104, potassium: 3.9, glucose: 205, white blood cell count: 6,000, hematocrit: 41, 24-hour urine 5-hydroxyindoleacetic acid (5HIAA) test: 12 mg/day (normal 2-8 mg/day), free catecholamines: 80 mg/24 hours (normal less than 100 mg/24 hours).
 

What is the most likely diagnosis?

A. Drug effect

B. Pheochromocytoma

C. Carcinoid syndrome

D. Mastocytosis

E. Medullary thyroid cancer

The most likely diagnosis is a drug effect. His flushing is likely caused by nifedipine.

Flushing is one of the most common side effects of this drug.¹ This patient had lab testing done for carcinoid (urine 5HIAA), presumably because he had flushing. This lab test result was a false positive, likely because of guaifenesin ingestion, which can cause false-positive 5HIAA results.²

Carcinoid syndrome is very rare (estimates from less than 1 patient/100,000), and the vast majority of patients who have it present with metastatic disease at presentation. Drug side effects are common, and usually are much more likely than rare diseases.
 

Four principles for assisting with making a diagnosis

This case points out the following four principles that I will touch on to help us make diagnoses in challenging cases.

1. Trigger symptoms: These are symptoms that make us think of a rare disease. In this case, the symptom is flushing, which may make you think of carcinoid syndrome.

Another good example of a trigger symptom is night sweats, where you may think of tuberculosis or lymphoma. These symptoms almost always have a much more common and likely cause, which in this case is a common drug side effect.

Trigger symptoms are great to pay attention to, but do not jump to working up the rare diagnosis without more evidence that it is a plausible diagnosis. Working up rare diseases without a reasonable pretest probability will lead to significant false-positive results.

2. Distinguishing features: These are findings, or combinations of findings, that make rarer diseases more likely. For example, flushing, although seen in many patients with carcinoid syndrome, is much more commonly caused by rosacea, medications, or estrogen/testosterone deficiency.

If a patient presents with flushing plus diarrhea, carcinoid syndrome becomes more likely in differentials. An example of a specific distinguishing feature is transient visual obstructions in patients with idiopathic intracranial hypertension (IIH or pseudotumor cerebri).

Sudden transient visual loss is not a symptom we see often, but headaches and obesity are problems we see every day. A patient with headaches and obesity is very likely to have IIH if they have transient visual obstructions along with headaches and obesity.

3. Intentional physical exams: Do the physical exam focusing on what findings will change your diagnostic probabilities. For example, in this case, if you are considering carcinoid, do a careful abdominal exam, with close attention to the liver, as 75% of patients with carcinoid syndrome have liver metastases.

If you are thinking about IIH, a fundoscopic exam is mandatory, as papilledema is a key feature of this diagnosis.

Read about the rare diagnosis you are considering, this will help with targeting your exam.

4. Remember the unusual presentation of a common disease is more common than the common presentation of a rare disease: Good examples of this are sleep apnea and gastroesophageal reflux disease causing night sweats more commonly than finding lymphomas or active tuberculosis (in the United States) as the cause.³

Pearl: Trigger symptoms help us think of rare diseases, but distinguishing features are most helpful in including or excluding the diagnosis.

Dr. Paauw is professor of medicine in the division of general internal medicine at the University of Washington, Seattle, and serves as third-year medical student clerkship director at the University of Washington. He is a member of the editorial advisory board of Internal Medicine News. Dr. Paauw has no conflicts to disclose. Contact him at [email protected].

References

1. Gueret P et al. Drugs. 1990;39 Suppl 2:67-72.

2. Corcuff J et al. Endocr Connect. 2017;6:R87.

3. Smith CS and Paauw DS. J Am Board Fam Pract. 2000;13:424-9.

A 64 year-old man with type 2 diabetes complains of recurrent flushing for the past 6 months. He has had no other symptoms. His only abnormalities on physical exam are a blood pressure of 160/100 and mild peripheral edema.

His current medications include: Famotidine 20 mg b.i.d., Pseudoephedrine/guaifenesin SR b.i.d., Metformin 1,000 mg twice a day, Nifedipine 60 mg XL once a day, and Atorvastatin 20 mg once a day.

His laboratory work up includes: blood urea nitrogen: 20, creatinine: 1.3, sodium: 140, Chloride: 104, potassium: 3.9, glucose: 205, white blood cell count: 6,000, hematocrit: 41, 24-hour urine 5-hydroxyindoleacetic acid (5HIAA) test: 12 mg/day (normal 2-8 mg/day), free catecholamines: 80 mg/24 hours (normal less than 100 mg/24 hours).
 

What is the most likely diagnosis?

A. Drug effect

B. Pheochromocytoma

C. Carcinoid syndrome

D. Mastocytosis

E. Medullary thyroid cancer

The most likely diagnosis is a drug effect. His flushing is likely caused by nifedipine.

Flushing is one of the most common side effects of this drug.¹ This patient had lab testing done for carcinoid (urine 5HIAA), presumably because he had flushing. This lab test result was a false positive, likely because of guaifenesin ingestion, which can cause false-positive 5HIAA results.²

Carcinoid syndrome is very rare (estimates from less than 1 patient/100,000), and the vast majority of patients who have it present with metastatic disease at presentation. Drug side effects are common, and usually are much more likely than rare diseases.
 

Four principles for assisting with making a diagnosis

This case points out the following four principles that I will touch on to help us make diagnoses in challenging cases.

1. Trigger symptoms: These are symptoms that make us think of a rare disease. In this case, the symptom is flushing, which may make you think of carcinoid syndrome.

Another good example of a trigger symptom is night sweats, where you may think of tuberculosis or lymphoma. These symptoms almost always have a much more common and likely cause, which in this case is a common drug side effect.

Trigger symptoms are great to pay attention to, but do not jump to working up the rare diagnosis without more evidence that it is a plausible diagnosis. Working up rare diseases without a reasonable pretest probability will lead to significant false-positive results.

2. Distinguishing features: These are findings, or combinations of findings, that make rarer diseases more likely. For example, flushing, although seen in many patients with carcinoid syndrome, is much more commonly caused by rosacea, medications, or estrogen/testosterone deficiency.

If a patient presents with flushing plus diarrhea, carcinoid syndrome becomes more likely in differentials. An example of a specific distinguishing feature is transient visual obstructions in patients with idiopathic intracranial hypertension (IIH or pseudotumor cerebri).

Sudden transient visual loss is not a symptom we see often, but headaches and obesity are problems we see every day. A patient with headaches and obesity is very likely to have IIH if they have transient visual obstructions along with headaches and obesity.

3. Intentional physical exams: Do the physical exam focusing on what findings will change your diagnostic probabilities. For example, in this case, if you are considering carcinoid, do a careful abdominal exam, with close attention to the liver, as 75% of patients with carcinoid syndrome have liver metastases.

If you are thinking about IIH, a fundoscopic exam is mandatory, as papilledema is a key feature of this diagnosis.

Read about the rare diagnosis you are considering, this will help with targeting your exam.

4. Remember the unusual presentation of a common disease is more common than the common presentation of a rare disease: Good examples of this are sleep apnea and gastroesophageal reflux disease causing night sweats more commonly than finding lymphomas or active tuberculosis (in the United States) as the cause.³

Pearl: Trigger symptoms help us think of rare diseases, but distinguishing features are most helpful in including or excluding the diagnosis.

Dr. Paauw is professor of medicine in the division of general internal medicine at the University of Washington, Seattle, and serves as third-year medical student clerkship director at the University of Washington. He is a member of the editorial advisory board of Internal Medicine News. Dr. Paauw has no conflicts to disclose. Contact him at [email protected].

References

1. Gueret P et al. Drugs. 1990;39 Suppl 2:67-72.

2. Corcuff J et al. Endocr Connect. 2017;6:R87.

3. Smith CS and Paauw DS. J Am Board Fam Pract. 2000;13:424-9.

Taking a daily multivitamin for 3 years is associated with a 60% slowing of cognitive aging, with the effects especially pronounced in patients with cardiovascular (CVD) disease, new research suggests.

©Graça Victoria/iStockphoto.com

In addition to testing the effect of a daily multivitamin on cognition, the COSMOS-Mind study examined the effect of cocoa flavanols, but showed no beneficial effect.

The findings “may have important public health implications, particularly for brain health, given the accessibility of multivitamins and minerals, and their low cost and safety,” said study investigator Laura D. Baker, PhD, professor, gerontology and geriatric medicine, Wake Forest University, Winston-Salem, N.C.

The findings were presented at the 14th Clinical Trials on Alzheimer’s Disease (CTAD) conference.

 

Placebo-controlled study

The study is a substudy of a large parent trial that compared the effects of cocoa extract (500 mg/day cocoa flavanols) and a standard multivitamin-mineral (MVM) to placebo on cardiovascular and cancer outcomes in more than 21,000 older participants.

COSMOS-Mind included 2,262 adults aged 65 and over without dementia who underwent cognitive testing at baseline and annually for 3 years. The mean age at baseline was 73 years, and 40.4% were men. Most participants (88.7%) were non-Hispanic White and almost half (49.2%) had some post-college education.

All study groups were balanced with respect to demographics, CVD history, diabetes, depression, smoking status, alcohol intake, chocolate intake, and prior multivitamin use. Baseline cognitive scores were similar between study groups. Researchers had complete data on 77% of study participants.

The primary endpoint was the effect of cocoa extract (CE) vs. placebo on Global Cognitive Function composite score. The secondary outcome was the effect of MVM vs. placebo on global cognitive function.

Additional outcomes included the impact of supplements on executive function and memory and the treatment effects for prespecified subgroups, including subjects with a history of CVD.

Using a graph of change over time, Dr. Baker showed there was no effect of cocoa on global cognitive function (effect: 0.03; 95% confidence interval, –0.02 to 0.08; P = .28). “We see the to-be-expected practice effects, but there’s no separation between the active and placebo groups,” she said.

It was a different story for MVM. Here, there was the same practice effect, but the graph showed the lines separated for global cognitive function composite score (effect: 0.07; 95% CI, 0.02-0.12; P = .007).

“We see a positive effect of multivitamins for the active group relative to placebo, peaking at 2 years and then remaining stable over time,” said Dr. Baker.

There were similar findings with MVM for the memory composite score, and the executive function composite score. “We have significance in all three, where the two lines do separate over and above the practice effects,” said Dr. Baker.
 

New evidence

Investigators found a baseline history of CVD, including transient ischemic attack, heart failure, coronary artery bypass graft, percutaneous transluminal coronary angioplasty, and stent, but not myocardial infarction or stroke as these were excluded in the parent trial because they affected the response to multivitamins.

As expected, those with CVD had lower cognitive scores at baseline. “But after an initial bump due to practice effect, at year 1, the cardiovascular disease history folks continue to benefit from multivitamins, whereas those who got placebo multivitamins continue to decline over time,” said Dr. Baker.

Based on information from a baseline scatter plot of cognitive function scores by age, the study’s modeling estimated the multivitamin treatment effect had a positive benefit of .028 standard deviations (SD) per year.

“Daily multivitamin-mineral supplementation appears to slow cognitive aging by 60% or by 1.8 years,” Dr. Baker added.

To date, the effect of MVM supplementation on cognition has been tested in only one large randomized clinical trial – the Physicians Health Study II. That study did not show an effect, but included only older male physicians – and cognitive testing began 2.5 years after randomization, said Dr. Baker.

“Our study provides new evidence that daily multivitamin supplementation may benefit cognitive function in older women and men, and the multivitamin effects may be more pronounced in participants with cardiovascular disease,” she noted.

For effects of multivitamins on Alzheimer’s disease prevalence and progression, “stay tuned,” Dr. Baker concluded.

Following the presentation, session cochair Suzanne Schindler, MD, PhD, instructor in the department of neurology at Washington University, St. Louis, said she and her colleagues “always check vitamin B₁₂ levels” in patients with memory and cognitive difficulties and wondered if study subjects with a low level or deficiency of vitamin B₁₂ benefited from the intervention.

“We are asking ourselves that as well,” said Dr. Baker.

“Some of this is a work in progress,” Dr. Baker added. “We still need to look at that more in-depth to understand whether it might be a mechanism for improvement. I think the results are still out on that topic.”

The study received support from the National Institute on Aging. Pfizer Consumer Healthcare (now GSK Consumer Healthcare) provided study pills and packaging. Dr. Baker has disclosed no relevant financial relationships.
 

A version of this article first appeared on Medscape.com.

Taking a daily multivitamin for 3 years is associated with a 60% slowing of cognitive aging, with the effects especially pronounced in patients with cardiovascular (CVD) disease, new research suggests.

©Graça Victoria/iStockphoto.com

In addition to testing the effect of a daily multivitamin on cognition, the COSMOS-Mind study examined the effect of cocoa flavanols, but showed no beneficial effect.

The findings “may have important public health implications, particularly for brain health, given the accessibility of multivitamins and minerals, and their low cost and safety,” said study investigator Laura D. Baker, PhD, professor, gerontology and geriatric medicine, Wake Forest University, Winston-Salem, N.C.

The findings were presented at the 14th Clinical Trials on Alzheimer’s Disease (CTAD) conference.

 

Placebo-controlled study

The study is a substudy of a large parent trial that compared the effects of cocoa extract (500 mg/day cocoa flavanols) and a standard multivitamin-mineral (MVM) to placebo on cardiovascular and cancer outcomes in more than 21,000 older participants.

COSMOS-Mind included 2,262 adults aged 65 and over without dementia who underwent cognitive testing at baseline and annually for 3 years. The mean age at baseline was 73 years, and 40.4% were men. Most participants (88.7%) were non-Hispanic White and almost half (49.2%) had some post-college education.

All study groups were balanced with respect to demographics, CVD history, diabetes, depression, smoking status, alcohol intake, chocolate intake, and prior multivitamin use. Baseline cognitive scores were similar between study groups. Researchers had complete data on 77% of study participants.

The primary endpoint was the effect of cocoa extract (CE) vs. placebo on Global Cognitive Function composite score. The secondary outcome was the effect of MVM vs. placebo on global cognitive function.

Additional outcomes included the impact of supplements on executive function and memory and the treatment effects for prespecified subgroups, including subjects with a history of CVD.

Using a graph of change over time, Dr. Baker showed there was no effect of cocoa on global cognitive function (effect: 0.03; 95% confidence interval, –0.02 to 0.08; P = .28). “We see the to-be-expected practice effects, but there’s no separation between the active and placebo groups,” she said.

It was a different story for MVM. Here, there was the same practice effect, but the graph showed the lines separated for global cognitive function composite score (effect: 0.07; 95% CI, 0.02-0.12; P = .007).

“We see a positive effect of multivitamins for the active group relative to placebo, peaking at 2 years and then remaining stable over time,” said Dr. Baker.

There were similar findings with MVM for the memory composite score, and the executive function composite score. “We have significance in all three, where the two lines do separate over and above the practice effects,” said Dr. Baker.
 

New evidence

Investigators found a baseline history of CVD, including transient ischemic attack, heart failure, coronary artery bypass graft, percutaneous transluminal coronary angioplasty, and stent, but not myocardial infarction or stroke as these were excluded in the parent trial because they affected the response to multivitamins.

As expected, those with CVD had lower cognitive scores at baseline. “But after an initial bump due to practice effect, at year 1, the cardiovascular disease history folks continue to benefit from multivitamins, whereas those who got placebo multivitamins continue to decline over time,” said Dr. Baker.

Based on information from a baseline scatter plot of cognitive function scores by age, the study’s modeling estimated the multivitamin treatment effect had a positive benefit of .028 standard deviations (SD) per year.

“Daily multivitamin-mineral supplementation appears to slow cognitive aging by 60% or by 1.8 years,” Dr. Baker added.

To date, the effect of MVM supplementation on cognition has been tested in only one large randomized clinical trial – the Physicians Health Study II. That study did not show an effect, but included only older male physicians – and cognitive testing began 2.5 years after randomization, said Dr. Baker.

“Our study provides new evidence that daily multivitamin supplementation may benefit cognitive function in older women and men, and the multivitamin effects may be more pronounced in participants with cardiovascular disease,” she noted.

For effects of multivitamins on Alzheimer’s disease prevalence and progression, “stay tuned,” Dr. Baker concluded.

Following the presentation, session cochair Suzanne Schindler, MD, PhD, instructor in the department of neurology at Washington University, St. Louis, said she and her colleagues “always check vitamin B₁₂ levels” in patients with memory and cognitive difficulties and wondered if study subjects with a low level or deficiency of vitamin B₁₂ benefited from the intervention.

“We are asking ourselves that as well,” said Dr. Baker.

“Some of this is a work in progress,” Dr. Baker added. “We still need to look at that more in-depth to understand whether it might be a mechanism for improvement. I think the results are still out on that topic.”

The study received support from the National Institute on Aging. Pfizer Consumer Healthcare (now GSK Consumer Healthcare) provided study pills and packaging. Dr. Baker has disclosed no relevant financial relationships.
 

A version of this article first appeared on Medscape.com.

Taking a daily multivitamin for 3 years is associated with a 60% slowing of cognitive aging, with the effects especially pronounced in patients with cardiovascular (CVD) disease, new research suggests.

©Graça Victoria/iStockphoto.com

In addition to testing the effect of a daily multivitamin on cognition, the COSMOS-Mind study examined the effect of cocoa flavanols, but showed no beneficial effect.

The findings “may have important public health implications, particularly for brain health, given the accessibility of multivitamins and minerals, and their low cost and safety,” said study investigator Laura D. Baker, PhD, professor, gerontology and geriatric medicine, Wake Forest University, Winston-Salem, N.C.

The findings were presented at the 14th Clinical Trials on Alzheimer’s Disease (CTAD) conference.

 

Placebo-controlled study

The study is a substudy of a large parent trial that compared the effects of cocoa extract (500 mg/day cocoa flavanols) and a standard multivitamin-mineral (MVM) to placebo on cardiovascular and cancer outcomes in more than 21,000 older participants.

COSMOS-Mind included 2,262 adults aged 65 and over without dementia who underwent cognitive testing at baseline and annually for 3 years. The mean age at baseline was 73 years, and 40.4% were men. Most participants (88.7%) were non-Hispanic White and almost half (49.2%) had some post-college education.

All study groups were balanced with respect to demographics, CVD history, diabetes, depression, smoking status, alcohol intake, chocolate intake, and prior multivitamin use. Baseline cognitive scores were similar between study groups. Researchers had complete data on 77% of study participants.

The primary endpoint was the effect of cocoa extract (CE) vs. placebo on Global Cognitive Function composite score. The secondary outcome was the effect of MVM vs. placebo on global cognitive function.

Additional outcomes included the impact of supplements on executive function and memory and the treatment effects for prespecified subgroups, including subjects with a history of CVD.

Using a graph of change over time, Dr. Baker showed there was no effect of cocoa on global cognitive function (effect: 0.03; 95% confidence interval, –0.02 to 0.08; P = .28). “We see the to-be-expected practice effects, but there’s no separation between the active and placebo groups,” she said.

It was a different story for MVM. Here, there was the same practice effect, but the graph showed the lines separated for global cognitive function composite score (effect: 0.07; 95% CI, 0.02-0.12; P = .007).

“We see a positive effect of multivitamins for the active group relative to placebo, peaking at 2 years and then remaining stable over time,” said Dr. Baker.

There were similar findings with MVM for the memory composite score, and the executive function composite score. “We have significance in all three, where the two lines do separate over and above the practice effects,” said Dr. Baker.
 

New evidence

Investigators found a baseline history of CVD, including transient ischemic attack, heart failure, coronary artery bypass graft, percutaneous transluminal coronary angioplasty, and stent, but not myocardial infarction or stroke as these were excluded in the parent trial because they affected the response to multivitamins.

As expected, those with CVD had lower cognitive scores at baseline. “But after an initial bump due to practice effect, at year 1, the cardiovascular disease history folks continue to benefit from multivitamins, whereas those who got placebo multivitamins continue to decline over time,” said Dr. Baker.

Based on information from a baseline scatter plot of cognitive function scores by age, the study’s modeling estimated the multivitamin treatment effect had a positive benefit of .028 standard deviations (SD) per year.

“Daily multivitamin-mineral supplementation appears to slow cognitive aging by 60% or by 1.8 years,” Dr. Baker added.

To date, the effect of MVM supplementation on cognition has been tested in only one large randomized clinical trial – the Physicians Health Study II. That study did not show an effect, but included only older male physicians – and cognitive testing began 2.5 years after randomization, said Dr. Baker.

“Our study provides new evidence that daily multivitamin supplementation may benefit cognitive function in older women and men, and the multivitamin effects may be more pronounced in participants with cardiovascular disease,” she noted.

For effects of multivitamins on Alzheimer’s disease prevalence and progression, “stay tuned,” Dr. Baker concluded.

Following the presentation, session cochair Suzanne Schindler, MD, PhD, instructor in the department of neurology at Washington University, St. Louis, said she and her colleagues “always check vitamin B₁₂ levels” in patients with memory and cognitive difficulties and wondered if study subjects with a low level or deficiency of vitamin B₁₂ benefited from the intervention.

“We are asking ourselves that as well,” said Dr. Baker.

“Some of this is a work in progress,” Dr. Baker added. “We still need to look at that more in-depth to understand whether it might be a mechanism for improvement. I think the results are still out on that topic.”

The study received support from the National Institute on Aging. Pfizer Consumer Healthcare (now GSK Consumer Healthcare) provided study pills and packaging. Dr. Baker has disclosed no relevant financial relationships.
 

A version of this article first appeared on Medscape.com.

Sleeping too much or too little can lead to cognitive decline over time, but new research suggests there could be a sleep time “sweet spot” that stabilizes cognitive function.

JGI/Tom Grill/Getty Images

In a longitudinal study, investigators found older adults who slept less than 4.5 hours or more than 6.5 hours a night reported significant cognitive decline over time, but cognitive scores for those with sleep duration in between that range remained stable.

“This really suggests that there’s this middle range, a ‘sweet spot,’ where your sleep is really optimal,” lead author Brendan Lucey, MD, MSCI, associate professor of neurology and director of the Washington University Sleep Medicine Center, St. Louis, said in an interview.

The study, published online Oct. 20, 2021, in the journal Brain, is part of a growing body of research that seeks to determine if sleep can be used as a marker of Alzheimer’s disease progression.
 

A complex relationship

Studies suggest a strong relationship between sleep patterns and Alzheimer’s disease, which affects nearly 6 million Americans. The challenge, Dr. Lucey said, is unwinding the complex links between sleep, AD, and cognitive function.

An earlier study by Dr. Lucey and colleagues found that poor sleep quality is associated with early signs of AD, and a report published in September found that elderly people who slept less than 6 hours a night had a greater burden of amyloid-beta, a hallmark sign of AD.

For this new study, researchers monitored sleep-wake activity over 4-6 nights in 100 participants who underwent annual cognitive assessments and clinical studies, including APOE genotyping, as part of a longitudinal study at the Knight Alzheimer Disease Research Center at Washington University.

Participants also provided cerebrospinal fluid (CSF) total tau and amyloid-beta 42 and wore a small EEG device on their forehead while they slept.

The majority of participants had a clinical dementia rating (CDR) score of 0, indicating no cognitive impairment. Twelve individuals had a CDR greater than 0, with most reporting mild cognitive impairment.

As expected, CSF analysis showed greater evidence of AD pathology in those with a baseline CDR greater than 0.

Changes in cognitive function were measured using a Preclinical Alzheimer Cognitive Composite (PACC) score, a composite of results from a neuropsychological testing battery that included the Free and Cued Selective Reminding Test, the Logical Memory Delayed Recall Test from the Wechsler Memory Scale–Revised, the Digit Symbol Substitution Test from the Wechsler Adult Intelligence Scale–Revised, and the Mini-Mental State Examination.

Researchers found an upside-down U-shaped relationship between PACC scores and sleep duration, with dramatic cognitive decline in those who slept less than 4.5 hours or more than 6.5 hours a night (P < .001 for both).

The U-shaped relationship was also found with measures of sleep phases, including time spent in rapid eye movement and in non-REM sleep (P < .001 for both).

The findings persisted even after controlling for confounders that can affect sleep and cognition, such as age, CSF total tau/amyloid-beta ₄₂ ratio, apo E four-allele carrier status, years of education, and sex.

Understanding how sleep changes at different stages of AD could help researchers determine if sleep can be used as a marker of disease progression, Dr. Lucey said. That could lead to interventions to slow that process.

“We’re not at the point yet where we can say that we need to monitor someone’s sleep time and then do an intervention to see if it would improve their risk for cognitive decline,” said Dr. Lucey, who plans to repeat this sleep study with the same cohort to track changes in sleep patterns and cognitive function over time. “But that’s a question I’m very excited to try to answer.”
 

A component of cognitive health

Commenting on the findings for this news organization, Heather Snyder, PhD, vice president of medical and scientific relations for the Alzheimer’s Association, noted that the study adds to a body of evidence linking sleep and cognition, especially how sleep quality can optimize brain function.

“We’ve seen previous research that’s shown poor sleep contributes to dementia risk, as well as research showing sleep duration may play a role in cognition,” she said.

“We also need studies that look at sleep as an intervention for cognitive health,” Dr. Snyder said. “Sleep is an important aspect of our overall health. Clinicians should have conversations with their patients about sleep as part of standard discussions about their health habits and wellness.”

The study was funded by the National Institutes of Health, the American Sleep Medicine Foundation, the Roger and Paula Riney Fund, and the Daniel J. Brennan, MD Fund. Dr. Lucey consults for Merck and Eli Lilly. Dr. Snyder has disclosed no relevant financial relationships.

A version of this article first appeared on Medscape.com.

Sleeping too much or too little can lead to cognitive decline over time, but new research suggests there could be a sleep time “sweet spot” that stabilizes cognitive function.

JGI/Tom Grill/Getty Images

In a longitudinal study, investigators found older adults who slept less than 4.5 hours or more than 6.5 hours a night reported significant cognitive decline over time, but cognitive scores for those with sleep duration in between that range remained stable.

“This really suggests that there’s this middle range, a ‘sweet spot,’ where your sleep is really optimal,” lead author Brendan Lucey, MD, MSCI, associate professor of neurology and director of the Washington University Sleep Medicine Center, St. Louis, said in an interview.

The study, published online Oct. 20, 2021, in the journal Brain, is part of a growing body of research that seeks to determine if sleep can be used as a marker of Alzheimer’s disease progression.
 

A complex relationship

Studies suggest a strong relationship between sleep patterns and Alzheimer’s disease, which affects nearly 6 million Americans. The challenge, Dr. Lucey said, is unwinding the complex links between sleep, AD, and cognitive function.

An earlier study by Dr. Lucey and colleagues found that poor sleep quality is associated with early signs of AD, and a report published in September found that elderly people who slept less than 6 hours a night had a greater burden of amyloid-beta, a hallmark sign of AD.

For this new study, researchers monitored sleep-wake activity over 4-6 nights in 100 participants who underwent annual cognitive assessments and clinical studies, including APOE genotyping, as part of a longitudinal study at the Knight Alzheimer Disease Research Center at Washington University.

Participants also provided cerebrospinal fluid (CSF) total tau and amyloid-beta 42 and wore a small EEG device on their forehead while they slept.

The majority of participants had a clinical dementia rating (CDR) score of 0, indicating no cognitive impairment. Twelve individuals had a CDR greater than 0, with most reporting mild cognitive impairment.

As expected, CSF analysis showed greater evidence of AD pathology in those with a baseline CDR greater than 0.

Changes in cognitive function were measured using a Preclinical Alzheimer Cognitive Composite (PACC) score, a composite of results from a neuropsychological testing battery that included the Free and Cued Selective Reminding Test, the Logical Memory Delayed Recall Test from the Wechsler Memory Scale–Revised, the Digit Symbol Substitution Test from the Wechsler Adult Intelligence Scale–Revised, and the Mini-Mental State Examination.

Researchers found an upside-down U-shaped relationship between PACC scores and sleep duration, with dramatic cognitive decline in those who slept less than 4.5 hours or more than 6.5 hours a night (P < .001 for both).

The U-shaped relationship was also found with measures of sleep phases, including time spent in rapid eye movement and in non-REM sleep (P < .001 for both).

The findings persisted even after controlling for confounders that can affect sleep and cognition, such as age, CSF total tau/amyloid-beta ₄₂ ratio, apo E four-allele carrier status, years of education, and sex.

Understanding how sleep changes at different stages of AD could help researchers determine if sleep can be used as a marker of disease progression, Dr. Lucey said. That could lead to interventions to slow that process.

“We’re not at the point yet where we can say that we need to monitor someone’s sleep time and then do an intervention to see if it would improve their risk for cognitive decline,” said Dr. Lucey, who plans to repeat this sleep study with the same cohort to track changes in sleep patterns and cognitive function over time. “But that’s a question I’m very excited to try to answer.”
 

A component of cognitive health

Commenting on the findings for this news organization, Heather Snyder, PhD, vice president of medical and scientific relations for the Alzheimer’s Association, noted that the study adds to a body of evidence linking sleep and cognition, especially how sleep quality can optimize brain function.

“We’ve seen previous research that’s shown poor sleep contributes to dementia risk, as well as research showing sleep duration may play a role in cognition,” she said.

“We also need studies that look at sleep as an intervention for cognitive health,” Dr. Snyder said. “Sleep is an important aspect of our overall health. Clinicians should have conversations with their patients about sleep as part of standard discussions about their health habits and wellness.”

The study was funded by the National Institutes of Health, the American Sleep Medicine Foundation, the Roger and Paula Riney Fund, and the Daniel J. Brennan, MD Fund. Dr. Lucey consults for Merck and Eli Lilly. Dr. Snyder has disclosed no relevant financial relationships.

A version of this article first appeared on Medscape.com.

Sleeping too much or too little can lead to cognitive decline over time, but new research suggests there could be a sleep time “sweet spot” that stabilizes cognitive function.

JGI/Tom Grill/Getty Images

In a longitudinal study, investigators found older adults who slept less than 4.5 hours or more than 6.5 hours a night reported significant cognitive decline over time, but cognitive scores for those with sleep duration in between that range remained stable.

“This really suggests that there’s this middle range, a ‘sweet spot,’ where your sleep is really optimal,” lead author Brendan Lucey, MD, MSCI, associate professor of neurology and director of the Washington University Sleep Medicine Center, St. Louis, said in an interview.

The study, published online Oct. 20, 2021, in the journal Brain, is part of a growing body of research that seeks to determine if sleep can be used as a marker of Alzheimer’s disease progression.
 

A complex relationship

Studies suggest a strong relationship between sleep patterns and Alzheimer’s disease, which affects nearly 6 million Americans. The challenge, Dr. Lucey said, is unwinding the complex links between sleep, AD, and cognitive function.

An earlier study by Dr. Lucey and colleagues found that poor sleep quality is associated with early signs of AD, and a report published in September found that elderly people who slept less than 6 hours a night had a greater burden of amyloid-beta, a hallmark sign of AD.

For this new study, researchers monitored sleep-wake activity over 4-6 nights in 100 participants who underwent annual cognitive assessments and clinical studies, including APOE genotyping, as part of a longitudinal study at the Knight Alzheimer Disease Research Center at Washington University.

Participants also provided cerebrospinal fluid (CSF) total tau and amyloid-beta 42 and wore a small EEG device on their forehead while they slept.

The majority of participants had a clinical dementia rating (CDR) score of 0, indicating no cognitive impairment. Twelve individuals had a CDR greater than 0, with most reporting mild cognitive impairment.

As expected, CSF analysis showed greater evidence of AD pathology in those with a baseline CDR greater than 0.

Changes in cognitive function were measured using a Preclinical Alzheimer Cognitive Composite (PACC) score, a composite of results from a neuropsychological testing battery that included the Free and Cued Selective Reminding Test, the Logical Memory Delayed Recall Test from the Wechsler Memory Scale–Revised, the Digit Symbol Substitution Test from the Wechsler Adult Intelligence Scale–Revised, and the Mini-Mental State Examination.

Researchers found an upside-down U-shaped relationship between PACC scores and sleep duration, with dramatic cognitive decline in those who slept less than 4.5 hours or more than 6.5 hours a night (P < .001 for both).

The U-shaped relationship was also found with measures of sleep phases, including time spent in rapid eye movement and in non-REM sleep (P < .001 for both).

The findings persisted even after controlling for confounders that can affect sleep and cognition, such as age, CSF total tau/amyloid-beta ₄₂ ratio, apo E four-allele carrier status, years of education, and sex.

Understanding how sleep changes at different stages of AD could help researchers determine if sleep can be used as a marker of disease progression, Dr. Lucey said. That could lead to interventions to slow that process.

“We’re not at the point yet where we can say that we need to monitor someone’s sleep time and then do an intervention to see if it would improve their risk for cognitive decline,” said Dr. Lucey, who plans to repeat this sleep study with the same cohort to track changes in sleep patterns and cognitive function over time. “But that’s a question I’m very excited to try to answer.”
 

A component of cognitive health

Commenting on the findings for this news organization, Heather Snyder, PhD, vice president of medical and scientific relations for the Alzheimer’s Association, noted that the study adds to a body of evidence linking sleep and cognition, especially how sleep quality can optimize brain function.

“We’ve seen previous research that’s shown poor sleep contributes to dementia risk, as well as research showing sleep duration may play a role in cognition,” she said.

“We also need studies that look at sleep as an intervention for cognitive health,” Dr. Snyder said. “Sleep is an important aspect of our overall health. Clinicians should have conversations with their patients about sleep as part of standard discussions about their health habits and wellness.”

The study was funded by the National Institutes of Health, the American Sleep Medicine Foundation, the Roger and Paula Riney Fund, and the Daniel J. Brennan, MD Fund. Dr. Lucey consults for Merck and Eli Lilly. Dr. Snyder has disclosed no relevant financial relationships.

A version of this article first appeared on Medscape.com.

The U.S. Food and Drug Administration has given marketing clearance to CognICA, an artificial intelligence–powered integrated cognitive assessment for the early detection of dementia.

Developed by Cognetivity Neurosciences, CognICA is a 5-minute, computerized cognitive assessment that is completed using an iPad. The test offers several advantages over traditional pen-and-paper–based cognitive tests, the company said in a news release.

“These include its high sensitivity to early-stage cognitive impairment, avoidance of cultural or educational bias, and absence of learning effect upon repeat testing,” the company notes.

Because the test runs on a computer, it can support remote, self-administered testing at scale and is geared toward seamless integration with existing electronic health record systems, they add.

According to the latest Alzheimer’s Disease Facts and Figures, published by the Alzheimer’s Association, more than 6 million Americans are now living with Alzheimer’s disease. That number is projected to increase to 12.7 million by 2050.

“We’re excited about the opportunity to revolutionize the way cognitive impairment is assessed and managed in the U.S. and make a positive impact on the health and wellbeing of millions of Americans,” Sina Habibi, PhD, cofounder and CEO of Cognetivity, said in the news release.

The test has already received European regulatory approval as a CE-marked medical device and has been deployed in both primary and specialist clinical care in the U.K.’s National Health Service.

A version of this article first appeared on Medscape.com.

The U.S. Food and Drug Administration has given marketing clearance to CognICA, an artificial intelligence–powered integrated cognitive assessment for the early detection of dementia.

Developed by Cognetivity Neurosciences, CognICA is a 5-minute, computerized cognitive assessment that is completed using an iPad. The test offers several advantages over traditional pen-and-paper–based cognitive tests, the company said in a news release.

“These include its high sensitivity to early-stage cognitive impairment, avoidance of cultural or educational bias, and absence of learning effect upon repeat testing,” the company notes.

Because the test runs on a computer, it can support remote, self-administered testing at scale and is geared toward seamless integration with existing electronic health record systems, they add.

According to the latest Alzheimer’s Disease Facts and Figures, published by the Alzheimer’s Association, more than 6 million Americans are now living with Alzheimer’s disease. That number is projected to increase to 12.7 million by 2050.

“We’re excited about the opportunity to revolutionize the way cognitive impairment is assessed and managed in the U.S. and make a positive impact on the health and wellbeing of millions of Americans,” Sina Habibi, PhD, cofounder and CEO of Cognetivity, said in the news release.

The test has already received European regulatory approval as a CE-marked medical device and has been deployed in both primary and specialist clinical care in the U.K.’s National Health Service.

A version of this article first appeared on Medscape.com.

The U.S. Food and Drug Administration has given marketing clearance to CognICA, an artificial intelligence–powered integrated cognitive assessment for the early detection of dementia.

Developed by Cognetivity Neurosciences, CognICA is a 5-minute, computerized cognitive assessment that is completed using an iPad. The test offers several advantages over traditional pen-and-paper–based cognitive tests, the company said in a news release.

“These include its high sensitivity to early-stage cognitive impairment, avoidance of cultural or educational bias, and absence of learning effect upon repeat testing,” the company notes.

Because the test runs on a computer, it can support remote, self-administered testing at scale and is geared toward seamless integration with existing electronic health record systems, they add.

According to the latest Alzheimer’s Disease Facts and Figures, published by the Alzheimer’s Association, more than 6 million Americans are now living with Alzheimer’s disease. That number is projected to increase to 12.7 million by 2050.

“We’re excited about the opportunity to revolutionize the way cognitive impairment is assessed and managed in the U.S. and make a positive impact on the health and wellbeing of millions of Americans,” Sina Habibi, PhD, cofounder and CEO of Cognetivity, said in the news release.

The test has already received European regulatory approval as a CE-marked medical device and has been deployed in both primary and specialist clinical care in the U.K.’s National Health Service.

A version of this article first appeared on Medscape.com.

Dementia remains a major cause of disability in older adults. In addition, it places a strain on family members and other caregivers taking care of these patients.

It is estimated that by the year 2060, 13.9 million Americans over the age of 65 will be diagnosed with dementia. Few good treatments are currently available.

Earlier this year, the American Psychological Association (APA) Task Force issued clinical guidelines “for the Evaluation of Dementia and Age-Related Cognitive Change.” While these 16 guidelines are aimed at psychologists, primary care doctors are often the first ones to evaluate a patient who may have dementia. As a family physician, I find having these guidelines especially helpful.
 

Neuropsychiatric testing and defining severity and type

This new guidance places emphasis on neuropsychiatric testing and defining the severity and type of dementia present.

Over the past 2 decades, diagnoses of mild neurocognitive disorders have increased, and this, in part, is due to diagnosing these problems earlier and with greater precision. It is also important to know that biomarkers are being increasingly researched, and it is imperative that we stay current with this research.

Cognitive decline may also occur with the coexistence of other mental health disorders, such as depression, so it is important that we screen for these as well. This is often difficult given the behavioral changes that can arise in dementia, but, as primary care doctors, we must differentiate these to treat our patients appropriately.
 

Informed consent

Informed consent can become an issue with patients with dementia. It must be assessed whether the patient has the capacity to make an informed decision and can competently communicate that decision.

The diagnosis of dementia alone does not preclude a patient from giving informed consent. A patient’s mental capacity must be determined, and if they are not capable of making an informed decision, the person legally responsible for giving informed consent on behalf of the patient must be identified.

Patients with dementia often have other medical comorbidities and take several medications. It is imperative to keep accurate medical records and medication lists. Sometimes, patients with dementia cannot provide this information. If that is the case, every attempt should be made to obtain records from every possible source.
 

Cultural competence

The guidelines also stress that there may be cultural differences when applying neuropsychiatric tests. It is our duty to maintain cultural competence and understand these differences. We all need to work to ensure we control our biases, and it is suggested that we review relevant evidence-based literature.

While ageism is common in our society, it shouldn’t be in our practices. For these reasons, outreach in at-risk populations is very important.
 

Pertinent data

The guidelines also suggest obtaining all possible information in our evaluation, especially when the patient is unable to give it to us.

Often, as primary care physicians, we refer these patients to other providers, and we should be providing all pertinent data to those we are referring these patients to. If all information is not available at the time of evaluation, follow-up visits should be scheduled.

If possible, family members should be present at the time of visit. They often provide valuable information regarding the extent and progression of the decline. Also, they know how the patient is functioning in the home setting and how much assistance they need with activities of daily living.
 

Caretaker support

Another important factor to consider is caretaker burnout. Caretakers are often under a lot of stress and have high rates of depression. It is important to provide them with education and support, as well as resources that may be available to them. For some, accepting the diagnosis that their loved one has dementia may be a struggle.

As doctors treating dementia patients, we need to know the resources that are available to assist dementia patients and their families. There are many local organizations that can help.

Also, research into dementia is ongoing and we need to stay current. The diagnosis of dementia should be made as early as possible using appropriate screening tools. The sooner the diagnosis is made, the quicker interventions can be started and the family members, as well as the patient, can come to accept the diagnosis.

As the population ages, we can expect the demands of dementia to rise as well. Primary care doctors are in a unique position to diagnose dementia once it starts to appear.
 

Dr. Girgis practices family medicine in South River, N.J., and is a clinical assistant professor of family medicine at Robert Wood Johnson Medical School, New Brunswick, N.J. You can contact her at [email protected].

Dementia remains a major cause of disability in older adults. In addition, it places a strain on family members and other caregivers taking care of these patients.

It is estimated that by the year 2060, 13.9 million Americans over the age of 65 will be diagnosed with dementia. Few good treatments are currently available.

Earlier this year, the American Psychological Association (APA) Task Force issued clinical guidelines “for the Evaluation of Dementia and Age-Related Cognitive Change.” While these 16 guidelines are aimed at psychologists, primary care doctors are often the first ones to evaluate a patient who may have dementia. As a family physician, I find having these guidelines especially helpful.
 

Neuropsychiatric testing and defining severity and type

This new guidance places emphasis on neuropsychiatric testing and defining the severity and type of dementia present.

Over the past 2 decades, diagnoses of mild neurocognitive disorders have increased, and this, in part, is due to diagnosing these problems earlier and with greater precision. It is also important to know that biomarkers are being increasingly researched, and it is imperative that we stay current with this research.

Cognitive decline may also occur with the coexistence of other mental health disorders, such as depression, so it is important that we screen for these as well. This is often difficult given the behavioral changes that can arise in dementia, but, as primary care doctors, we must differentiate these to treat our patients appropriately.
 

Informed consent

Informed consent can become an issue with patients with dementia. It must be assessed whether the patient has the capacity to make an informed decision and can competently communicate that decision.

The diagnosis of dementia alone does not preclude a patient from giving informed consent. A patient’s mental capacity must be determined, and if they are not capable of making an informed decision, the person legally responsible for giving informed consent on behalf of the patient must be identified.

Patients with dementia often have other medical comorbidities and take several medications. It is imperative to keep accurate medical records and medication lists. Sometimes, patients with dementia cannot provide this information. If that is the case, every attempt should be made to obtain records from every possible source.
 

Cultural competence

The guidelines also stress that there may be cultural differences when applying neuropsychiatric tests. It is our duty to maintain cultural competence and understand these differences. We all need to work to ensure we control our biases, and it is suggested that we review relevant evidence-based literature.

While ageism is common in our society, it shouldn’t be in our practices. For these reasons, outreach in at-risk populations is very important.
 

Pertinent data

The guidelines also suggest obtaining all possible information in our evaluation, especially when the patient is unable to give it to us.

Often, as primary care physicians, we refer these patients to other providers, and we should be providing all pertinent data to those we are referring these patients to. If all information is not available at the time of evaluation, follow-up visits should be scheduled.

If possible, family members should be present at the time of visit. They often provide valuable information regarding the extent and progression of the decline. Also, they know how the patient is functioning in the home setting and how much assistance they need with activities of daily living.
 

Caretaker support

Another important factor to consider is caretaker burnout. Caretakers are often under a lot of stress and have high rates of depression. It is important to provide them with education and support, as well as resources that may be available to them. For some, accepting the diagnosis that their loved one has dementia may be a struggle.

As doctors treating dementia patients, we need to know the resources that are available to assist dementia patients and their families. There are many local organizations that can help.

Also, research into dementia is ongoing and we need to stay current. The diagnosis of dementia should be made as early as possible using appropriate screening tools. The sooner the diagnosis is made, the quicker interventions can be started and the family members, as well as the patient, can come to accept the diagnosis.

As the population ages, we can expect the demands of dementia to rise as well. Primary care doctors are in a unique position to diagnose dementia once it starts to appear.
 

Dr. Girgis practices family medicine in South River, N.J., and is a clinical assistant professor of family medicine at Robert Wood Johnson Medical School, New Brunswick, N.J. You can contact her at [email protected].

Dementia remains a major cause of disability in older adults. In addition, it places a strain on family members and other caregivers taking care of these patients.

It is estimated that by the year 2060, 13.9 million Americans over the age of 65 will be diagnosed with dementia. Few good treatments are currently available.

Earlier this year, the American Psychological Association (APA) Task Force issued clinical guidelines “for the Evaluation of Dementia and Age-Related Cognitive Change.” While these 16 guidelines are aimed at psychologists, primary care doctors are often the first ones to evaluate a patient who may have dementia. As a family physician, I find having these guidelines especially helpful.
 

Neuropsychiatric testing and defining severity and type

This new guidance places emphasis on neuropsychiatric testing and defining the severity and type of dementia present.

Over the past 2 decades, diagnoses of mild neurocognitive disorders have increased, and this, in part, is due to diagnosing these problems earlier and with greater precision. It is also important to know that biomarkers are being increasingly researched, and it is imperative that we stay current with this research.

Cognitive decline may also occur with the coexistence of other mental health disorders, such as depression, so it is important that we screen for these as well. This is often difficult given the behavioral changes that can arise in dementia, but, as primary care doctors, we must differentiate these to treat our patients appropriately.
 

Informed consent

Informed consent can become an issue with patients with dementia. It must be assessed whether the patient has the capacity to make an informed decision and can competently communicate that decision.

The diagnosis of dementia alone does not preclude a patient from giving informed consent. A patient’s mental capacity must be determined, and if they are not capable of making an informed decision, the person legally responsible for giving informed consent on behalf of the patient must be identified.

Patients with dementia often have other medical comorbidities and take several medications. It is imperative to keep accurate medical records and medication lists. Sometimes, patients with dementia cannot provide this information. If that is the case, every attempt should be made to obtain records from every possible source.
 

Cultural competence

The guidelines also stress that there may be cultural differences when applying neuropsychiatric tests. It is our duty to maintain cultural competence and understand these differences. We all need to work to ensure we control our biases, and it is suggested that we review relevant evidence-based literature.

While ageism is common in our society, it shouldn’t be in our practices. For these reasons, outreach in at-risk populations is very important.
 

Pertinent data

The guidelines also suggest obtaining all possible information in our evaluation, especially when the patient is unable to give it to us.

Often, as primary care physicians, we refer these patients to other providers, and we should be providing all pertinent data to those we are referring these patients to. If all information is not available at the time of evaluation, follow-up visits should be scheduled.

If possible, family members should be present at the time of visit. They often provide valuable information regarding the extent and progression of the decline. Also, they know how the patient is functioning in the home setting and how much assistance they need with activities of daily living.
 

Caretaker support

Another important factor to consider is caretaker burnout. Caretakers are often under a lot of stress and have high rates of depression. It is important to provide them with education and support, as well as resources that may be available to them. For some, accepting the diagnosis that their loved one has dementia may be a struggle.

As doctors treating dementia patients, we need to know the resources that are available to assist dementia patients and their families. There are many local organizations that can help.

Also, research into dementia is ongoing and we need to stay current. The diagnosis of dementia should be made as early as possible using appropriate screening tools. The sooner the diagnosis is made, the quicker interventions can be started and the family members, as well as the patient, can come to accept the diagnosis.

As the population ages, we can expect the demands of dementia to rise as well. Primary care doctors are in a unique position to diagnose dementia once it starts to appear.
 

Dr. Girgis practices family medicine in South River, N.J., and is a clinical assistant professor of family medicine at Robert Wood Johnson Medical School, New Brunswick, N.J. You can contact her at [email protected].

This month’s cover story, “A 4-pronged approach to foster healthy aging in older adults,” by Wilson and colleagues (page 376) provides a wealth of information about aspects of healthy aging that we should consider when we see our older patients. After reading this manuscript, I was a bit overwhelmed by the amount of information presented and, more so, by the thought of attempting to incorporate into my practice all of the possible screenings and interventions available to help older adults improve and maintain their health.

There is no debate about the importance of issues such as diet, exercise and mobility, mental health and cognition, vision and hearing, and strong social connections for maintaining health as we age. The difficulty comes in deciding how to spend our limited time with older patients during office encounters. Most older adults have several chronic diseases that need our attention, and they often have various medications that need to be monitored for effectiveness and safety, which can be time consuming. And, of course, we need to take time to screen for cardiovascular risk and cancer, too. Where to start?

Dr. Wilson’s solution makes sense to me: Take advantage of the annual wellness visit to discuss diet, exercise, mental health, vision and hearing, and social relationships. I am not so sure, however, if using formal screening instruments is the best way to do this, especially since there is no strong research that demonstrates improved patient-relevant outcomes using screening instruments, except, perhaps, for periodically screening for anxiety and depression.

It may be effective to use the “chat technique” and ask open-ended questions, such as: How are things going for you?

It may be as effective to use what I will call the “chat technique.” Start with open-ended questions and statements, such as: “How are things going for you?” “Tell me about your family.” “What do you do for physical activity?” and “How has your mood been lately?”

An excellent complement to the chat technique is the goal-setting approach championed by geriatrician and family physician Jim Mold.¹ His premise is that health itself is not the most important goal for most people, but rather a means to an end. That end is very specific to every person. An elderly, frail woman’s main life goal, for example, might be to remain in her own home for as long as possible or to live long enough to attend her great-grandson’s wedding.

Goal setting provides an excellent context for true shared decision-making. I agree with Dr. Wilson’s closing statement:

“As family physicians, it is important to capitalize on longitudinal relationships with patients and begin educating younger patients using this multidimensional framework to promote living ‘a productive and meaningful life’at any age.”

This month’s cover story, “A 4-pronged approach to foster healthy aging in older adults,” by Wilson and colleagues (page 376) provides a wealth of information about aspects of healthy aging that we should consider when we see our older patients. After reading this manuscript, I was a bit overwhelmed by the amount of information presented and, more so, by the thought of attempting to incorporate into my practice all of the possible screenings and interventions available to help older adults improve and maintain their health.

There is no debate about the importance of issues such as diet, exercise and mobility, mental health and cognition, vision and hearing, and strong social connections for maintaining health as we age. The difficulty comes in deciding how to spend our limited time with older patients during office encounters. Most older adults have several chronic diseases that need our attention, and they often have various medications that need to be monitored for effectiveness and safety, which can be time consuming. And, of course, we need to take time to screen for cardiovascular risk and cancer, too. Where to start?

Dr. Wilson’s solution makes sense to me: Take advantage of the annual wellness visit to discuss diet, exercise, mental health, vision and hearing, and social relationships. I am not so sure, however, if using formal screening instruments is the best way to do this, especially since there is no strong research that demonstrates improved patient-relevant outcomes using screening instruments, except, perhaps, for periodically screening for anxiety and depression.

It may be effective to use the “chat technique” and ask open-ended questions, such as: How are things going for you?

It may be as effective to use what I will call the “chat technique.” Start with open-ended questions and statements, such as: “How are things going for you?” “Tell me about your family.” “What do you do for physical activity?” and “How has your mood been lately?”

An excellent complement to the chat technique is the goal-setting approach championed by geriatrician and family physician Jim Mold.¹ His premise is that health itself is not the most important goal for most people, but rather a means to an end. That end is very specific to every person. An elderly, frail woman’s main life goal, for example, might be to remain in her own home for as long as possible or to live long enough to attend her great-grandson’s wedding.

Goal setting provides an excellent context for true shared decision-making. I agree with Dr. Wilson’s closing statement:

“As family physicians, it is important to capitalize on longitudinal relationships with patients and begin educating younger patients using this multidimensional framework to promote living ‘a productive and meaningful life’at any age.”

This month’s cover story, “A 4-pronged approach to foster healthy aging in older adults,” by Wilson and colleagues (page 376) provides a wealth of information about aspects of healthy aging that we should consider when we see our older patients. After reading this manuscript, I was a bit overwhelmed by the amount of information presented and, more so, by the thought of attempting to incorporate into my practice all of the possible screenings and interventions available to help older adults improve and maintain their health.

There is no debate about the importance of issues such as diet, exercise and mobility, mental health and cognition, vision and hearing, and strong social connections for maintaining health as we age. The difficulty comes in deciding how to spend our limited time with older patients during office encounters. Most older adults have several chronic diseases that need our attention, and they often have various medications that need to be monitored for effectiveness and safety, which can be time consuming. And, of course, we need to take time to screen for cardiovascular risk and cancer, too. Where to start?

Dr. Wilson’s solution makes sense to me: Take advantage of the annual wellness visit to discuss diet, exercise, mental health, vision and hearing, and social relationships. I am not so sure, however, if using formal screening instruments is the best way to do this, especially since there is no strong research that demonstrates improved patient-relevant outcomes using screening instruments, except, perhaps, for periodically screening for anxiety and depression.

It may be effective to use the “chat technique” and ask open-ended questions, such as: How are things going for you?

It may be as effective to use what I will call the “chat technique.” Start with open-ended questions and statements, such as: “How are things going for you?” “Tell me about your family.” “What do you do for physical activity?” and “How has your mood been lately?”

An excellent complement to the chat technique is the goal-setting approach championed by geriatrician and family physician Jim Mold.¹ His premise is that health itself is not the most important goal for most people, but rather a means to an end. That end is very specific to every person. An elderly, frail woman’s main life goal, for example, might be to remain in her own home for as long as possible or to live long enough to attend her great-grandson’s wedding.

Goal setting provides an excellent context for true shared decision-making. I agree with Dr. Wilson’s closing statement:

“As family physicians, it is important to capitalize on longitudinal relationships with patients and begin educating younger patients using this multidimensional framework to promote living ‘a productive and meaningful life’at any age.”

Although early menopause is linked to increased risks in bone loss and fracture, new research indicates that, even among the majority of women who have menopause after age 45, the time since the final menstrual period can be a stronger predictor than chronological age for key risks in bone health and fracture.

Steve Debenport/Getty Images

In a large longitudinal cohort, the number of years since a woman’s final menstrual period specifically showed a stronger association with femoral neck bone mineral density (BMD) than chronological age, while an earlier age at menopause – even among those over 45 years, was linked to an increased risk of fracture.

“Most of our clinical tools to predict osteoporosis-related outcomes use chronological age,” first author Albert Shieh, MD, told this news organization.

“Our findings suggest that more research should be done to examine whether ovarian age (time since final menstrual period) should be used in these tools as well.”

An increased focus on the significance of age at the time of the final menstrual period, compared with chronological age, has gained interest in risk assessment because of the known acceleration in the decline of BMD that occurs 1 year prior to the final menstrual period and continues at a rapid pace for 3 years afterwards before slowing.

To further investigate the association with BMD, Dr. Shieh, an endocrinologist specializing in osteoporosis at the University of California, Los Angeles, and his colleagues turned to data from the Study of Women’s Health Across the Nation (SWAN), a longitudinal cohort study of ambulatory women with pre- or early perimenopausal baseline data and 15 annual follow-up assessments.

Outcomes regarding postmenopausal lumbar spine (LS) or femoral neck (FN) BMD were evaluated in 1,038 women, while the time to fracture in relation to the final menstrual period was separately evaluated in 1,554 women.

In both cohorts, the women had a known final menstrual period at age 45 or older, and on average, their final menstrual period occurred at age 52.

After a multivariate adjustment for age, body mass index, and various other factors, they found that each additional year after a woman’s final menstrual period was associated with a significant (0.006 g/cm²) reduction in postmenopausal lumbar spine BMD and a 0.004 g/cm² reduction femoral neck BMD (both P < .0001).

Conversely, chronological age was not associated with a change in femoral neck BMD when evaluated independently of years since the final menstrual period, the researchers reported in the Journal of Clinical Endocrinology and Metabolism.

Regarding lumbar spine BMD, chronological age was unexpectedly associated not just with change, but in fact with increases in lumbar spine BMD (P < .0001 per year). However, the authors speculate the change “is likely a reflection of age-associated degenerative changes causing false elevations in BMD measured by dual-energy x-ray absorptiometry.”

Fracture risk with earlier menopause

In terms of the fracture risk analysis, despite the women all being aged 45 or older, earlier age at menopause was still tied to an increased risk of incident fracture, with a 5% increase in risk for each earlier year in age at the time of the final menstrual period (P = .02).

Compared with women who had their final menstrual period at age 55, for instance, those who finished menstruating at age 47 had a 6.3% greater 20-year cumulative fracture risk, the authors note.

While previous findings from the Malmo Perimenopausal Study showed menopause prior to the age of 47 to be associated with an 83% and 59% greater risk of densitometric osteoporosis and fracture, respectively, by age 77, the authors note that the new study is unique in including only women who had a final menstrual period over the age of 45, therefore reducing the potential confounding of data on women under 45.

The new results “add to a growing body of literature suggesting that the endocrine changes that occur during the menopause transition trigger a pathophysiologic cascade that leads to organ dysfunction,” the authors note.

In terms of implications in risk assessment, “future studies should examine whether years since the final menstrual period predicts major osteoporotic fractures and hip fractures, specifically, and, if so, whether replacing chronological age with years since the final menstrual period improves the performance of clinical prediction tools, such as FRAX [Fracture Risk Assessment Tool],” they add.

Addition to guidelines?

Commenting on the findings, Peter Ebeling, MD, the current president of the American Society of Bone and Mineral Research, noted that the study importantly “confirms what we had previously anticipated, that in women with menopause who are 45 years of age or older a lower age of final menstrual period is associated with lower spine and hip BMD and more fractures.”

“We had already known this for women with premature ovarian insufficiency or an early menopause, and this extends the observation to the vast majority of women – more than 90% – with a normal menopause age,” said Dr. Ebeling, professor of medicine at Monash Health, Monash University, in Melbourne.

Despite the known importance of the time since final menstrual period, guidelines still focus on age in terms of chronology, rather than biology, emphasizing the risk among women over 50, in general, rather than the time since the last menstrual period, he noted.

“There is an important difference [between those two], as shown by this study,” he said. “Guidelines could be easily adapted to reflect this.”

Specifically, the association between lower age of final menstrual period and lower spine and hip BMD and more fractures requires “more formal assessment to determine whether adding age of final menstrual period to existing fracture risk calculator tools, like FRAX, can improve absolute fracture risk prediction,” Dr. Ebeling noted.

The authors and Dr. Ebeling had no disclosures to report.

Although early menopause is linked to increased risks in bone loss and fracture, new research indicates that, even among the majority of women who have menopause after age 45, the time since the final menstrual period can be a stronger predictor than chronological age for key risks in bone health and fracture.

Steve Debenport/Getty Images

In a large longitudinal cohort, the number of years since a woman’s final menstrual period specifically showed a stronger association with femoral neck bone mineral density (BMD) than chronological age, while an earlier age at menopause – even among those over 45 years, was linked to an increased risk of fracture.

“Most of our clinical tools to predict osteoporosis-related outcomes use chronological age,” first author Albert Shieh, MD, told this news organization.

“Our findings suggest that more research should be done to examine whether ovarian age (time since final menstrual period) should be used in these tools as well.”

An increased focus on the significance of age at the time of the final menstrual period, compared with chronological age, has gained interest in risk assessment because of the known acceleration in the decline of BMD that occurs 1 year prior to the final menstrual period and continues at a rapid pace for 3 years afterwards before slowing.

To further investigate the association with BMD, Dr. Shieh, an endocrinologist specializing in osteoporosis at the University of California, Los Angeles, and his colleagues turned to data from the Study of Women’s Health Across the Nation (SWAN), a longitudinal cohort study of ambulatory women with pre- or early perimenopausal baseline data and 15 annual follow-up assessments.

Outcomes regarding postmenopausal lumbar spine (LS) or femoral neck (FN) BMD were evaluated in 1,038 women, while the time to fracture in relation to the final menstrual period was separately evaluated in 1,554 women.

In both cohorts, the women had a known final menstrual period at age 45 or older, and on average, their final menstrual period occurred at age 52.

After a multivariate adjustment for age, body mass index, and various other factors, they found that each additional year after a woman’s final menstrual period was associated with a significant (0.006 g/cm²) reduction in postmenopausal lumbar spine BMD and a 0.004 g/cm² reduction femoral neck BMD (both P < .0001).

Conversely, chronological age was not associated with a change in femoral neck BMD when evaluated independently of years since the final menstrual period, the researchers reported in the Journal of Clinical Endocrinology and Metabolism.

Regarding lumbar spine BMD, chronological age was unexpectedly associated not just with change, but in fact with increases in lumbar spine BMD (P < .0001 per year). However, the authors speculate the change “is likely a reflection of age-associated degenerative changes causing false elevations in BMD measured by dual-energy x-ray absorptiometry.”

Fracture risk with earlier menopause

In terms of the fracture risk analysis, despite the women all being aged 45 or older, earlier age at menopause was still tied to an increased risk of incident fracture, with a 5% increase in risk for each earlier year in age at the time of the final menstrual period (P = .02).

Compared with women who had their final menstrual period at age 55, for instance, those who finished menstruating at age 47 had a 6.3% greater 20-year cumulative fracture risk, the authors note.

While previous findings from the Malmo Perimenopausal Study showed menopause prior to the age of 47 to be associated with an 83% and 59% greater risk of densitometric osteoporosis and fracture, respectively, by age 77, the authors note that the new study is unique in including only women who had a final menstrual period over the age of 45, therefore reducing the potential confounding of data on women under 45.

The new results “add to a growing body of literature suggesting that the endocrine changes that occur during the menopause transition trigger a pathophysiologic cascade that leads to organ dysfunction,” the authors note.

In terms of implications in risk assessment, “future studies should examine whether years since the final menstrual period predicts major osteoporotic fractures and hip fractures, specifically, and, if so, whether replacing chronological age with years since the final menstrual period improves the performance of clinical prediction tools, such as FRAX [Fracture Risk Assessment Tool],” they add.

Addition to guidelines?

Commenting on the findings, Peter Ebeling, MD, the current president of the American Society of Bone and Mineral Research, noted that the study importantly “confirms what we had previously anticipated, that in women with menopause who are 45 years of age or older a lower age of final menstrual period is associated with lower spine and hip BMD and more fractures.”

“We had already known this for women with premature ovarian insufficiency or an early menopause, and this extends the observation to the vast majority of women – more than 90% – with a normal menopause age,” said Dr. Ebeling, professor of medicine at Monash Health, Monash University, in Melbourne.

Despite the known importance of the time since final menstrual period, guidelines still focus on age in terms of chronology, rather than biology, emphasizing the risk among women over 50, in general, rather than the time since the last menstrual period, he noted.

“There is an important difference [between those two], as shown by this study,” he said. “Guidelines could be easily adapted to reflect this.”

Specifically, the association between lower age of final menstrual period and lower spine and hip BMD and more fractures requires “more formal assessment to determine whether adding age of final menstrual period to existing fracture risk calculator tools, like FRAX, can improve absolute fracture risk prediction,” Dr. Ebeling noted.

The authors and Dr. Ebeling had no disclosures to report.

Although early menopause is linked to increased risks in bone loss and fracture, new research indicates that, even among the majority of women who have menopause after age 45, the time since the final menstrual period can be a stronger predictor than chronological age for key risks in bone health and fracture.

Steve Debenport/Getty Images

In a large longitudinal cohort, the number of years since a woman’s final menstrual period specifically showed a stronger association with femoral neck bone mineral density (BMD) than chronological age, while an earlier age at menopause – even among those over 45 years, was linked to an increased risk of fracture.

“Most of our clinical tools to predict osteoporosis-related outcomes use chronological age,” first author Albert Shieh, MD, told this news organization.

“Our findings suggest that more research should be done to examine whether ovarian age (time since final menstrual period) should be used in these tools as well.”

An increased focus on the significance of age at the time of the final menstrual period, compared with chronological age, has gained interest in risk assessment because of the known acceleration in the decline of BMD that occurs 1 year prior to the final menstrual period and continues at a rapid pace for 3 years afterwards before slowing.

To further investigate the association with BMD, Dr. Shieh, an endocrinologist specializing in osteoporosis at the University of California, Los Angeles, and his colleagues turned to data from the Study of Women’s Health Across the Nation (SWAN), a longitudinal cohort study of ambulatory women with pre- or early perimenopausal baseline data and 15 annual follow-up assessments.

Outcomes regarding postmenopausal lumbar spine (LS) or femoral neck (FN) BMD were evaluated in 1,038 women, while the time to fracture in relation to the final menstrual period was separately evaluated in 1,554 women.

In both cohorts, the women had a known final menstrual period at age 45 or older, and on average, their final menstrual period occurred at age 52.

After a multivariate adjustment for age, body mass index, and various other factors, they found that each additional year after a woman’s final menstrual period was associated with a significant (0.006 g/cm²) reduction in postmenopausal lumbar spine BMD and a 0.004 g/cm² reduction femoral neck BMD (both P < .0001).

Conversely, chronological age was not associated with a change in femoral neck BMD when evaluated independently of years since the final menstrual period, the researchers reported in the Journal of Clinical Endocrinology and Metabolism.

Regarding lumbar spine BMD, chronological age was unexpectedly associated not just with change, but in fact with increases in lumbar spine BMD (P < .0001 per year). However, the authors speculate the change “is likely a reflection of age-associated degenerative changes causing false elevations in BMD measured by dual-energy x-ray absorptiometry.”

Fracture risk with earlier menopause

In terms of the fracture risk analysis, despite the women all being aged 45 or older, earlier age at menopause was still tied to an increased risk of incident fracture, with a 5% increase in risk for each earlier year in age at the time of the final menstrual period (P = .02).

Compared with women who had their final menstrual period at age 55, for instance, those who finished menstruating at age 47 had a 6.3% greater 20-year cumulative fracture risk, the authors note.

While previous findings from the Malmo Perimenopausal Study showed menopause prior to the age of 47 to be associated with an 83% and 59% greater risk of densitometric osteoporosis and fracture, respectively, by age 77, the authors note that the new study is unique in including only women who had a final menstrual period over the age of 45, therefore reducing the potential confounding of data on women under 45.

The new results “add to a growing body of literature suggesting that the endocrine changes that occur during the menopause transition trigger a pathophysiologic cascade that leads to organ dysfunction,” the authors note.

In terms of implications in risk assessment, “future studies should examine whether years since the final menstrual period predicts major osteoporotic fractures and hip fractures, specifically, and, if so, whether replacing chronological age with years since the final menstrual period improves the performance of clinical prediction tools, such as FRAX [Fracture Risk Assessment Tool],” they add.

Addition to guidelines?

Commenting on the findings, Peter Ebeling, MD, the current president of the American Society of Bone and Mineral Research, noted that the study importantly “confirms what we had previously anticipated, that in women with menopause who are 45 years of age or older a lower age of final menstrual period is associated with lower spine and hip BMD and more fractures.”

“We had already known this for women with premature ovarian insufficiency or an early menopause, and this extends the observation to the vast majority of women – more than 90% – with a normal menopause age,” said Dr. Ebeling, professor of medicine at Monash Health, Monash University, in Melbourne.

Despite the known importance of the time since final menstrual period, guidelines still focus on age in terms of chronology, rather than biology, emphasizing the risk among women over 50, in general, rather than the time since the last menstrual period, he noted.

“There is an important difference [between those two], as shown by this study,” he said. “Guidelines could be easily adapted to reflect this.”

Specifically, the association between lower age of final menstrual period and lower spine and hip BMD and more fractures requires “more formal assessment to determine whether adding age of final menstrual period to existing fracture risk calculator tools, like FRAX, can improve absolute fracture risk prediction,” Dr. Ebeling noted.

The authors and Dr. Ebeling had no disclosures to report.