Areeba Kara, MD, MS, FACP

Geographic cohorting (GCh, also known as “localization” or “regionalization”) refers to the practice wherein hospitalists are assigned to a single inpatient unit. Its adoption is increasing and in 2017, 30% of surveyed United States hospital medicine group leaders reported that their clinicians rounded on 1-2 units daily.¹ As a component of intervention bundles, GCh is associated with reductions in mortality, length of stay, and costs.^2,3

However, details on how GCh affects the hospitalist workday are unknown. Most time-motion studies of inpatient clinicians have reported the experiences of physicians in training with few specifically evaluating the workflow of attending hospitalists.⁴ Three studies of the attending hospitalist’s workday that were performed a decade ago excluded teams with learners, had patient loads as low as 9.4 per day, and did not differentiate between GCh and non-GCh models.^5-7

The objective of this observational study was to describe and compare the workday of GCh and non-GCh hospitalists by using automated geographical-tracking methods supplemented by in-person observations.

Setting and Participants

This work was conducted at a large academic center in the Midwestern US which adopted GCh in 2012. During the study, hospitalists staffed 11 GCh and four non-GCh teams. GCh teams aim to maintain ≥80% of their patients on their assigned unit and conduct interprofessional huddles on weekdays.³ Some units specialize in the care of specific populations (eg, patients with oncologic diagnoses), while others serve as general medical or surgical units. Non-GCh teams are assigned patients without regard to location. Resident housestaff are assigned only to GCh teams and residents and advanced practice providers (APPs) are never assigned to the same team. Based on team members, this yielded five distinct team types: GCh-hospitalist, GCh-hospitalist with APP, GCh-hospitalist with resident, non-GCh-hospitalist, and non-GCh-hospitalist with APP. Hospitalists provided verbal consent to participate. The protocol was reviewed and approved by the Indiana University Institutional Review Board. Two complementary observation modalities were used. Locator badges were used to quantify direct and indirect time unobtrusively over long periods. In-person observations were conducted to examine the workday in greater detail. Data were collected between October 2017 and May 2018.

Observations by Locator Badges

Our institution uses a system designed by Hill-Rom^® (Cary, North Carolina) to facilitate staff communication. Staff wear the I-Badge^® Locator Badge, which emits an infra-red signal.⁸ Centrally located receivers tabulate time spent by the badge wearer in each location (Appendix Figure 1). Each hospitalist was given a badge to wear at work for a minimum of six weeks, after which the I-Badge^® data were downloaded.

Schedules detailing each team’s members and assigned units (if cohorted) were retrieved. For each observed day, the hospitalist was linked to his or her team type and unit. Team lists were retrieved to ascertain patient load at the start of the day. Data sources were merged to categorize observations.

Observation Categories for Locator Badge Data

The I-Badge^® data provided details of how much time the hospitalist spent in each location (eg, nursing station, hallways, patient rooms). All observations in patient rooms were considered “direct care” while all other locations were categorized as “Indirect Care”. Observations were also categorized by the intensity of care provided on that unit, which included the Emergency Department (ED), Progressive Care Units (PCU), Medical-Surgical + PCU units (for units having a mixture of Medical-Surgical and PCU beds), and Medical-Surgical units.

In-person Observations

Four research assistants (RAs) were trained until interrater reliability using task times achieved an intraclass correlation coefficient of 0.98. Task categories included direct care (all time with patients), indirect care (computer interactions, communication), professional development, and travel and personal time. Interruptions were defined as “an unplanned and unscheduled task, causing a discontinuation, a noticeable break, or task switch behavior”.⁹ “Electronic interruptions” were caused by pagers or phones whereas in-person interruptions were “face-to-face” interruptions. When at least two tasks were performed simultaneously, it was considered multitasking. A data collection form created in REDCap was accessed on computer tablets or smartphones¹⁰ (Appendix Table 1). To limit each observation period to five hours, two RAs were scheduled each day. Observations were continued until the hospitalist reported that work activities were complete or until 5 pm.

Statistical Analysis

Due to the nested structure of the locator badge data, multilevel models that permit predictors to vary at more than one level were used.¹¹ The distribution of the duration of direct care observations was log normal for which the parameters were estimated using generalized linear mixed models (GLMM). The GLMM estimates were converted using a nonlinear transformation to predict the mean duration of interactions. The GLMM estimates were then used to predict time allocations for hospitalists with various workloads and contexts. The five team types were captured in a single categorical variable.

Univariate three-level models predicting minutes spent in direct care were tested for each predictor. Predictors, described below, were selected due to their hypothesized relation to time spent in direct patient care, or to account statistically for differences among teams due to the observational nature of the study.¹² Predictors were: Level 3, hospitalist characteristics (years since medical school, age, gender, international graduate, years at current hospital); Level 2, work day characteristics (number of units visited, number of patients visited, team type, weekday); and Level 1, individual observation characteristics (intensity of care on unit, number of visits to the same patient room per day). Predictors that were significantly related to the duration of direct care at P value <.05 and whose inclusion resulted in better model fit based on likelihood ratio tests were retained in a multivariate model. Additionally, a logistic regression model with random effects was tested to determine whether hospitalists working in GCh vs non-GCh teams (including teams with APPs and residents) made more than one visit to the same patient in a day. For duration of direct care encounters, the amount of variation explained (intraclass correlation) at the hospitalist level was .05, and at the day level was .03.

For total daily indirect care, a similar modeling process was used. A log normal distribution was used because the data was right-skewed and contained positive values. The restricted maximum likelihood method was used to calculate final estimates for models. Least square mean values for independent variables were subjected to backward transformation for interpretation. Post hoc pairwise comparisons between team types were conducted using Tukey–Kramer tests for direct and indirect care time. Analyses were conducted using SAS software version 9.4 (Cary, North Carolina).

The in-person observations were summarized using descriptive statistics. Exploratory analyses were performed using t-tests and Fisher’s exact tests to compare continuous and categorical variables respectively.

Locator Badge Observations

Participants

The 17 hospitalists had a mean (SD) age of 38 years (6.4); 10 (59%) were male, 7 (41%) were international medical graduates, and 10 (59%) had worked at the hospital ≥5 years. The duration of observation was <45 days for 7 hospitalists, 46-55 days for 4, and >55 days for 6, yielding observations for 666 hospitalist workdays. The mean time since medical school graduation was 13 years. Seven hospitalists were observed only in the GCh model, one was observed only in the non-GCh model, and nine were observed in both.

Team Characteristics

On average, non-GCh teams visited more units per day than GCh teams. Teams with APPs had higher patient loads (Table 1).

Time Observed in Direct and Indirect Care

In total, 10,522 observations were recorded in providing direct care. The average duration of a direct care encounter ranged from 4.1 to 5.8 minutes. The ratio of indirect to direct time ranged from 2.7 to 3.7 (Table 2).

The number of times that a hospitalist visited the same patient room in one day ranged from 1 to 9. Most (84%) of the patient rooms were visited once per day. The odds that a GCh hospitalist would visit a patient more than once per day were 1.8 times higher (95% CI: 1.37, 2.34; P < .0001) than for a non-GCh hospitalist (data not shown).

Predictors Associated with Time Expenditure

Predictors significantly associated with both the duration of direct care encounters and total daily indirect care time included team type and patient count. Predicted time in direct care encounters was highest for the GCh-hospitalist team (9.5 minutes) and lowest for the GCh-hospitalist with residents team (7 minutes). Predicted total indirect care time was highest for the GCh-hospitalist with APP team (160 minutes) while the lowest expenditure in indirect care time was predicted for the non-GCh-hospitalist team (102 minutes). Increasing patient load from 10 to 20 was predicted to decrease the duration of a direct care encounter by one minute (14%) and increase the total indirect care time by a larger amount (39 min, 24%).

The duration of direct care encounters was also inversely related with years since medical school and number of visits made to same patient room. Finally, acuity of care was associated with the duration of direct care encounters with the longest predicted encounters in the ED (9.4 minutes). Physician gender and age, international graduation, years at current hospital, weekday, and the number of units visited in a day were neither associated with direct care time at P value < .05 nor improved model fit and therefore were not retained in the final model (Table 3).

In-person Observations

Four hospitalists cohorted to general medical units and four non-GCh hospitalists were observed for one day each, yielding a total of 3,032 minutes of data. These hospitalists were on teams without residents or APPs. On average, GCh hospitalists had 78% of their patients on their assigned unit, rounded on fewer units (3 vs 6) and had two more patients at the start of the day than non-GCh hospitalists (14 vs 12). Age and gender distribution of the GCh and non-GCh hospitalists were similar.

As a percentage of total observed time, GCh hospitalists were noted to spend a larger proportion of the workday in computer interactions vs non-GCh hospitalists (56% vs 39%; P = .005). The proportion of time in other activities or locations was not statistically different between GCh and non-GCh hospitalists, including face-to-face communication (21% vs 15%), multitasking (18% vs 14%), time spent at the nursing station (58% vs 34%), direct care (15% vs 20%), and time traveling (4% vs 11%). The most frequently observed combination of multitasking was computer and phone use (59% of all multitasking) followed by computer use and face-to-face communication (17%; Appendix Figure 2).

The mean duration of an interruption was 1.3 minutes. More interruptions were observed in the GCh group than the non-GCh group (139 vs 102). Interruptions in the GCh group were face-to-face in 62% of instances and electronic in 25%. The remaining 13% were instances in which electronic and face-to-face interruptions occurred simultaneously. In the non-GCh group, 51% of interruptions were face-to-face; 47% were electronic; and 2% were simultaneous. GCh hospitalists were interrupted once every 14 minutes in the morning, with interruption frequency increasing to once every eight minutes in the afternoon. Non-GCh hospitalists were interrupted once every 13 minutes in the morning and saw interruption frequency decrease to once every 17 minutes in the afternoon. The task most frequently interrupted was computer use.

DISCUSSION

Previous investigations have studied the impact of cohorting on outcomes, including the facilitation of bedside rounding, adverse events, agreement between nurses and physicians on the plan of care, productivity, and the number of pages received.^13-16 Cohorting’s benefits are theorized to include increased hospitalist time with patients, while its downsides are perceived to include increased interruptions.^17,18 Neither has previously been evaluated by direct observation.

Our findings support cohorting’s association with increased hospitalist–patient time. While GCh hospitalists were observed spending 5% less time in direct care than non-GCh hospitalists by in-person observations, this difference did not achieve statistical significance and was unadjusted for hospitalist, patient load, team or patient characteristics. Using the larger badge dataset, the predicted values for time spent in direct care encounters were higher in cohorted teams. Pairwise comparisons consistently trended toward longer durations in cohorted vs noncohorted teams. The notable exception was in cohorted teams with residents, which had the shortest predicted patient visits; however, we did not have noncohorted teams with residents in our study, limiting interpretation. Additionally, the odds of repeat visits to a patient in a single day were almost twice as high in the cohorted vs noncohorted group. The magnitude of this gain, however, is estimated to be a modest 1.2 minutes for a hospitalist only team and 1.7 minutes for a hospitalist with APP team and may be insufficient to provide compassionate, patient-centered care.¹⁹

Furthermore, these gains may be eroded if patient loads are high: similar to a previous study, we found that the duration of each patient visit decreased by 14% when the load increased from 10 to 20 patients.⁶ The expected gains in efficiency from cohorting leads to an expectation that hospitalists can manage more patients, but such reflexive increases should be carefully considered.¹⁸

Similar to earlier investigations where hospitalists were found to spend 60 to 69% of the day in indirect care activities,^5,6 hospitalists in both cohorted and noncohorted models spent approximately three times more time in indirect than direct care. Cohorting was associated with increased indirect care time. This association was expected as interdisciplinary huddles and increased nursing and physician communication are both related to cohorting.^3,14 However, similar to previous reports, in-person observations revealed that the bulk of this indirect time was spent in computer interactions, rather than in interprofessional communication. Interactions with the electronic health record (EHR) consume between one-third to one-half of the day in inpatient settings.^20,21 While EHRs are intended to enhance safety, they also fulfill multiple, nonclinical purposes and increase time spent on documentation.^22,23 Nonclinical tasks may contribute to clinician burnout and detract from patient centeredness.²² Our findings suggest that cohorting may not offset the burden of these time-intensive EHR tasks. The larger expenditure of time spent in computer interactions observed in the GCh group may be partially explained both by the higher number of patients and the higher frequency of interruptions observed in this group; computer use was the task most frequently observed to be interrupted. While longer tasks are more likely to be interrupted, the interruption in turn further increases the time taken to complete the task.²⁴

The interruption rates we observed are concerning. The hospitalist workday emerges as cognitively intense. GCh hospitalists were noted to be interrupted as frequently as once every eight minutes, a rate more than double that of an earlier investigation and approaching that of ED physicians.^5,25,26 Interruptions and multitasking contribute to errors and a perception of increased workload and frustration for clinicians.^9,27-29 Although interruptions were pervasive, GCh hospitalists were interrupted more frequently, corroborating a national survey in which hospitalists perceived that cohorting increased face-to-face interruptions.³⁰ The prolonged availability of the cohorted hospitalist on the unit may require different strategies for promoting timely interactions while preserving uninterrupted work time. Our work, however, does not allow us to quantify appropriate and urgent interruptions that reflect improved teamwork and patient safety. Interruptions increase as patient loads increase.²⁵ The contribution to interruptions by the higher patient census on the GCh teams cannot be quantified in this work, but without attention to these details, potential benefits from GCh may be attenuated.

Previous work has delineated variables important in determining hospitalist workload,³¹ and our work contributes additional considerations. Hospitalist experience and resident presence on cohorted teams was associated with shorter patient visits, while ED encounters were predicted to be the most time intensive. Increasing numbers of units visited in a day was associated with more indirect time, while weekends were associated with a lower burden of indirect care. As expected, APP presence was associated with more time in indirect care as the hospitalist spends time in providing oversight. As noted, cohorting was associated with increases in both direct and indirect care time. These findings may help inform hospital medicine groups. Additionally, attention should be paid to the fact that while support for cohorting stems from investigations in which it was used as part of a bundle of interventions,^2,3 in practice, it is often implemented incompletely, with cohorted hospitalists dispersed over several units, or in isolation from other interventions.¹

Our work has several limitations. As a single-center investigation, our findings may not be generalizable to other institutions. Second, we did not evaluate clinical outcomes, clinician, patient or nursing satisfaction to assess the effect of cohorting. Third, we cannot comment on whether the observed interruptions were beneficial or detrimental. Finally, while we used statistical control for the measured imbalanced variables between groups, unmeasured confounding factors between team types including differences in patient populations, pathologies and severity of illness, or the unit’s work environment and processes may have affected results.

Our work underscores the importance of paying careful attention to specific components and monitoring for unintended consequences in a complex intervention such as cohorting to allow subsequent refinement. Further studies to assess the interplay between models of care, their impact on interruptions, multitasking, errors and clinician burnout may be necessary. Such investigations will be critical to support the evolution of hospital medicine that enables it to be the driver of excellence in care.

Acknowledgments

The authors thank the participating hospitalists, research assistants, Shelly Harrison, Joni Godfrey, Mark Luetkemeyer, Deanne Kashiwagi, Tammy Kemlage, Dustin Hertel and Adeel Zaidi for their enthusiasm and support. The authors also thank Ann Cottingham, Rich Frankel and Greg Sachs from the ASPIRE program for their guidance and vision. Dr. Weiner is Chief of Health Services Research and Development at the Richard L. Roudebush Veterans Affairs Medical Center in Indianapolis, Indiana.

Disclaimer

The views expressed in this article are those of the authors and do not necessarily represent the views of the U.S. Department of Veterans Affairs.

Geographic cohorting (GCh, also known as “localization” or “regionalization”) refers to the practice wherein hospitalists are assigned to a single inpatient unit. Its adoption is increasing and in 2017, 30% of surveyed United States hospital medicine group leaders reported that their clinicians rounded on 1-2 units daily.¹ As a component of intervention bundles, GCh is associated with reductions in mortality, length of stay, and costs.^2,3

However, details on how GCh affects the hospitalist workday are unknown. Most time-motion studies of inpatient clinicians have reported the experiences of physicians in training with few specifically evaluating the workflow of attending hospitalists.⁴ Three studies of the attending hospitalist’s workday that were performed a decade ago excluded teams with learners, had patient loads as low as 9.4 per day, and did not differentiate between GCh and non-GCh models.^5-7

The objective of this observational study was to describe and compare the workday of GCh and non-GCh hospitalists by using automated geographical-tracking methods supplemented by in-person observations.

Setting and Participants

This work was conducted at a large academic center in the Midwestern US which adopted GCh in 2012. During the study, hospitalists staffed 11 GCh and four non-GCh teams. GCh teams aim to maintain ≥80% of their patients on their assigned unit and conduct interprofessional huddles on weekdays.³ Some units specialize in the care of specific populations (eg, patients with oncologic diagnoses), while others serve as general medical or surgical units. Non-GCh teams are assigned patients without regard to location. Resident housestaff are assigned only to GCh teams and residents and advanced practice providers (APPs) are never assigned to the same team. Based on team members, this yielded five distinct team types: GCh-hospitalist, GCh-hospitalist with APP, GCh-hospitalist with resident, non-GCh-hospitalist, and non-GCh-hospitalist with APP. Hospitalists provided verbal consent to participate. The protocol was reviewed and approved by the Indiana University Institutional Review Board. Two complementary observation modalities were used. Locator badges were used to quantify direct and indirect time unobtrusively over long periods. In-person observations were conducted to examine the workday in greater detail. Data were collected between October 2017 and May 2018.

Observations by Locator Badges

Our institution uses a system designed by Hill-Rom^® (Cary, North Carolina) to facilitate staff communication. Staff wear the I-Badge^® Locator Badge, which emits an infra-red signal.⁸ Centrally located receivers tabulate time spent by the badge wearer in each location (Appendix Figure 1). Each hospitalist was given a badge to wear at work for a minimum of six weeks, after which the I-Badge^® data were downloaded.

Schedules detailing each team’s members and assigned units (if cohorted) were retrieved. For each observed day, the hospitalist was linked to his or her team type and unit. Team lists were retrieved to ascertain patient load at the start of the day. Data sources were merged to categorize observations.

Observation Categories for Locator Badge Data

The I-Badge^® data provided details of how much time the hospitalist spent in each location (eg, nursing station, hallways, patient rooms). All observations in patient rooms were considered “direct care” while all other locations were categorized as “Indirect Care”. Observations were also categorized by the intensity of care provided on that unit, which included the Emergency Department (ED), Progressive Care Units (PCU), Medical-Surgical + PCU units (for units having a mixture of Medical-Surgical and PCU beds), and Medical-Surgical units.

In-person Observations

Four research assistants (RAs) were trained until interrater reliability using task times achieved an intraclass correlation coefficient of 0.98. Task categories included direct care (all time with patients), indirect care (computer interactions, communication), professional development, and travel and personal time. Interruptions were defined as “an unplanned and unscheduled task, causing a discontinuation, a noticeable break, or task switch behavior”.⁹ “Electronic interruptions” were caused by pagers or phones whereas in-person interruptions were “face-to-face” interruptions. When at least two tasks were performed simultaneously, it was considered multitasking. A data collection form created in REDCap was accessed on computer tablets or smartphones¹⁰ (Appendix Table 1). To limit each observation period to five hours, two RAs were scheduled each day. Observations were continued until the hospitalist reported that work activities were complete or until 5 pm.

Statistical Analysis

Due to the nested structure of the locator badge data, multilevel models that permit predictors to vary at more than one level were used.¹¹ The distribution of the duration of direct care observations was log normal for which the parameters were estimated using generalized linear mixed models (GLMM). The GLMM estimates were converted using a nonlinear transformation to predict the mean duration of interactions. The GLMM estimates were then used to predict time allocations for hospitalists with various workloads and contexts. The five team types were captured in a single categorical variable.

Univariate three-level models predicting minutes spent in direct care were tested for each predictor. Predictors, described below, were selected due to their hypothesized relation to time spent in direct patient care, or to account statistically for differences among teams due to the observational nature of the study.¹² Predictors were: Level 3, hospitalist characteristics (years since medical school, age, gender, international graduate, years at current hospital); Level 2, work day characteristics (number of units visited, number of patients visited, team type, weekday); and Level 1, individual observation characteristics (intensity of care on unit, number of visits to the same patient room per day). Predictors that were significantly related to the duration of direct care at P value <.05 and whose inclusion resulted in better model fit based on likelihood ratio tests were retained in a multivariate model. Additionally, a logistic regression model with random effects was tested to determine whether hospitalists working in GCh vs non-GCh teams (including teams with APPs and residents) made more than one visit to the same patient in a day. For duration of direct care encounters, the amount of variation explained (intraclass correlation) at the hospitalist level was .05, and at the day level was .03.

For total daily indirect care, a similar modeling process was used. A log normal distribution was used because the data was right-skewed and contained positive values. The restricted maximum likelihood method was used to calculate final estimates for models. Least square mean values for independent variables were subjected to backward transformation for interpretation. Post hoc pairwise comparisons between team types were conducted using Tukey–Kramer tests for direct and indirect care time. Analyses were conducted using SAS software version 9.4 (Cary, North Carolina).

The in-person observations were summarized using descriptive statistics. Exploratory analyses were performed using t-tests and Fisher’s exact tests to compare continuous and categorical variables respectively.

Locator Badge Observations

Participants

The 17 hospitalists had a mean (SD) age of 38 years (6.4); 10 (59%) were male, 7 (41%) were international medical graduates, and 10 (59%) had worked at the hospital ≥5 years. The duration of observation was <45 days for 7 hospitalists, 46-55 days for 4, and >55 days for 6, yielding observations for 666 hospitalist workdays. The mean time since medical school graduation was 13 years. Seven hospitalists were observed only in the GCh model, one was observed only in the non-GCh model, and nine were observed in both.

Team Characteristics

On average, non-GCh teams visited more units per day than GCh teams. Teams with APPs had higher patient loads (Table 1).

Time Observed in Direct and Indirect Care

In total, 10,522 observations were recorded in providing direct care. The average duration of a direct care encounter ranged from 4.1 to 5.8 minutes. The ratio of indirect to direct time ranged from 2.7 to 3.7 (Table 2).

The number of times that a hospitalist visited the same patient room in one day ranged from 1 to 9. Most (84%) of the patient rooms were visited once per day. The odds that a GCh hospitalist would visit a patient more than once per day were 1.8 times higher (95% CI: 1.37, 2.34; P < .0001) than for a non-GCh hospitalist (data not shown).

Predictors Associated with Time Expenditure

Predictors significantly associated with both the duration of direct care encounters and total daily indirect care time included team type and patient count. Predicted time in direct care encounters was highest for the GCh-hospitalist team (9.5 minutes) and lowest for the GCh-hospitalist with residents team (7 minutes). Predicted total indirect care time was highest for the GCh-hospitalist with APP team (160 minutes) while the lowest expenditure in indirect care time was predicted for the non-GCh-hospitalist team (102 minutes). Increasing patient load from 10 to 20 was predicted to decrease the duration of a direct care encounter by one minute (14%) and increase the total indirect care time by a larger amount (39 min, 24%).

The duration of direct care encounters was also inversely related with years since medical school and number of visits made to same patient room. Finally, acuity of care was associated with the duration of direct care encounters with the longest predicted encounters in the ED (9.4 minutes). Physician gender and age, international graduation, years at current hospital, weekday, and the number of units visited in a day were neither associated with direct care time at P value < .05 nor improved model fit and therefore were not retained in the final model (Table 3).

In-person Observations

Four hospitalists cohorted to general medical units and four non-GCh hospitalists were observed for one day each, yielding a total of 3,032 minutes of data. These hospitalists were on teams without residents or APPs. On average, GCh hospitalists had 78% of their patients on their assigned unit, rounded on fewer units (3 vs 6) and had two more patients at the start of the day than non-GCh hospitalists (14 vs 12). Age and gender distribution of the GCh and non-GCh hospitalists were similar.

As a percentage of total observed time, GCh hospitalists were noted to spend a larger proportion of the workday in computer interactions vs non-GCh hospitalists (56% vs 39%; P = .005). The proportion of time in other activities or locations was not statistically different between GCh and non-GCh hospitalists, including face-to-face communication (21% vs 15%), multitasking (18% vs 14%), time spent at the nursing station (58% vs 34%), direct care (15% vs 20%), and time traveling (4% vs 11%). The most frequently observed combination of multitasking was computer and phone use (59% of all multitasking) followed by computer use and face-to-face communication (17%; Appendix Figure 2).

The mean duration of an interruption was 1.3 minutes. More interruptions were observed in the GCh group than the non-GCh group (139 vs 102). Interruptions in the GCh group were face-to-face in 62% of instances and electronic in 25%. The remaining 13% were instances in which electronic and face-to-face interruptions occurred simultaneously. In the non-GCh group, 51% of interruptions were face-to-face; 47% were electronic; and 2% were simultaneous. GCh hospitalists were interrupted once every 14 minutes in the morning, with interruption frequency increasing to once every eight minutes in the afternoon. Non-GCh hospitalists were interrupted once every 13 minutes in the morning and saw interruption frequency decrease to once every 17 minutes in the afternoon. The task most frequently interrupted was computer use.

DISCUSSION

Previous investigations have studied the impact of cohorting on outcomes, including the facilitation of bedside rounding, adverse events, agreement between nurses and physicians on the plan of care, productivity, and the number of pages received.^13-16 Cohorting’s benefits are theorized to include increased hospitalist time with patients, while its downsides are perceived to include increased interruptions.^17,18 Neither has previously been evaluated by direct observation.

Our findings support cohorting’s association with increased hospitalist–patient time. While GCh hospitalists were observed spending 5% less time in direct care than non-GCh hospitalists by in-person observations, this difference did not achieve statistical significance and was unadjusted for hospitalist, patient load, team or patient characteristics. Using the larger badge dataset, the predicted values for time spent in direct care encounters were higher in cohorted teams. Pairwise comparisons consistently trended toward longer durations in cohorted vs noncohorted teams. The notable exception was in cohorted teams with residents, which had the shortest predicted patient visits; however, we did not have noncohorted teams with residents in our study, limiting interpretation. Additionally, the odds of repeat visits to a patient in a single day were almost twice as high in the cohorted vs noncohorted group. The magnitude of this gain, however, is estimated to be a modest 1.2 minutes for a hospitalist only team and 1.7 minutes for a hospitalist with APP team and may be insufficient to provide compassionate, patient-centered care.¹⁹

Furthermore, these gains may be eroded if patient loads are high: similar to a previous study, we found that the duration of each patient visit decreased by 14% when the load increased from 10 to 20 patients.⁶ The expected gains in efficiency from cohorting leads to an expectation that hospitalists can manage more patients, but such reflexive increases should be carefully considered.¹⁸

Similar to earlier investigations where hospitalists were found to spend 60 to 69% of the day in indirect care activities,^5,6 hospitalists in both cohorted and noncohorted models spent approximately three times more time in indirect than direct care. Cohorting was associated with increased indirect care time. This association was expected as interdisciplinary huddles and increased nursing and physician communication are both related to cohorting.^3,14 However, similar to previous reports, in-person observations revealed that the bulk of this indirect time was spent in computer interactions, rather than in interprofessional communication. Interactions with the electronic health record (EHR) consume between one-third to one-half of the day in inpatient settings.^20,21 While EHRs are intended to enhance safety, they also fulfill multiple, nonclinical purposes and increase time spent on documentation.^22,23 Nonclinical tasks may contribute to clinician burnout and detract from patient centeredness.²² Our findings suggest that cohorting may not offset the burden of these time-intensive EHR tasks. The larger expenditure of time spent in computer interactions observed in the GCh group may be partially explained both by the higher number of patients and the higher frequency of interruptions observed in this group; computer use was the task most frequently observed to be interrupted. While longer tasks are more likely to be interrupted, the interruption in turn further increases the time taken to complete the task.²⁴

The interruption rates we observed are concerning. The hospitalist workday emerges as cognitively intense. GCh hospitalists were noted to be interrupted as frequently as once every eight minutes, a rate more than double that of an earlier investigation and approaching that of ED physicians.^5,25,26 Interruptions and multitasking contribute to errors and a perception of increased workload and frustration for clinicians.^9,27-29 Although interruptions were pervasive, GCh hospitalists were interrupted more frequently, corroborating a national survey in which hospitalists perceived that cohorting increased face-to-face interruptions.³⁰ The prolonged availability of the cohorted hospitalist on the unit may require different strategies for promoting timely interactions while preserving uninterrupted work time. Our work, however, does not allow us to quantify appropriate and urgent interruptions that reflect improved teamwork and patient safety. Interruptions increase as patient loads increase.²⁵ The contribution to interruptions by the higher patient census on the GCh teams cannot be quantified in this work, but without attention to these details, potential benefits from GCh may be attenuated.

Previous work has delineated variables important in determining hospitalist workload,³¹ and our work contributes additional considerations. Hospitalist experience and resident presence on cohorted teams was associated with shorter patient visits, while ED encounters were predicted to be the most time intensive. Increasing numbers of units visited in a day was associated with more indirect time, while weekends were associated with a lower burden of indirect care. As expected, APP presence was associated with more time in indirect care as the hospitalist spends time in providing oversight. As noted, cohorting was associated with increases in both direct and indirect care time. These findings may help inform hospital medicine groups. Additionally, attention should be paid to the fact that while support for cohorting stems from investigations in which it was used as part of a bundle of interventions,^2,3 in practice, it is often implemented incompletely, with cohorted hospitalists dispersed over several units, or in isolation from other interventions.¹

Our work has several limitations. As a single-center investigation, our findings may not be generalizable to other institutions. Second, we did not evaluate clinical outcomes, clinician, patient or nursing satisfaction to assess the effect of cohorting. Third, we cannot comment on whether the observed interruptions were beneficial or detrimental. Finally, while we used statistical control for the measured imbalanced variables between groups, unmeasured confounding factors between team types including differences in patient populations, pathologies and severity of illness, or the unit’s work environment and processes may have affected results.

Our work underscores the importance of paying careful attention to specific components and monitoring for unintended consequences in a complex intervention such as cohorting to allow subsequent refinement. Further studies to assess the interplay between models of care, their impact on interruptions, multitasking, errors and clinician burnout may be necessary. Such investigations will be critical to support the evolution of hospital medicine that enables it to be the driver of excellence in care.

Acknowledgments

The authors thank the participating hospitalists, research assistants, Shelly Harrison, Joni Godfrey, Mark Luetkemeyer, Deanne Kashiwagi, Tammy Kemlage, Dustin Hertel and Adeel Zaidi for their enthusiasm and support. The authors also thank Ann Cottingham, Rich Frankel and Greg Sachs from the ASPIRE program for their guidance and vision. Dr. Weiner is Chief of Health Services Research and Development at the Richard L. Roudebush Veterans Affairs Medical Center in Indianapolis, Indiana.

Disclaimer

The views expressed in this article are those of the authors and do not necessarily represent the views of the U.S. Department of Veterans Affairs.

Geographic cohorting (GCh, also known as “localization” or “regionalization”) refers to the practice wherein hospitalists are assigned to a single inpatient unit. Its adoption is increasing and in 2017, 30% of surveyed United States hospital medicine group leaders reported that their clinicians rounded on 1-2 units daily.¹ As a component of intervention bundles, GCh is associated with reductions in mortality, length of stay, and costs.^2,3

However, details on how GCh affects the hospitalist workday are unknown. Most time-motion studies of inpatient clinicians have reported the experiences of physicians in training with few specifically evaluating the workflow of attending hospitalists.⁴ Three studies of the attending hospitalist’s workday that were performed a decade ago excluded teams with learners, had patient loads as low as 9.4 per day, and did not differentiate between GCh and non-GCh models.^5-7

The objective of this observational study was to describe and compare the workday of GCh and non-GCh hospitalists by using automated geographical-tracking methods supplemented by in-person observations.

Setting and Participants

This work was conducted at a large academic center in the Midwestern US which adopted GCh in 2012. During the study, hospitalists staffed 11 GCh and four non-GCh teams. GCh teams aim to maintain ≥80% of their patients on their assigned unit and conduct interprofessional huddles on weekdays.³ Some units specialize in the care of specific populations (eg, patients with oncologic diagnoses), while others serve as general medical or surgical units. Non-GCh teams are assigned patients without regard to location. Resident housestaff are assigned only to GCh teams and residents and advanced practice providers (APPs) are never assigned to the same team. Based on team members, this yielded five distinct team types: GCh-hospitalist, GCh-hospitalist with APP, GCh-hospitalist with resident, non-GCh-hospitalist, and non-GCh-hospitalist with APP. Hospitalists provided verbal consent to participate. The protocol was reviewed and approved by the Indiana University Institutional Review Board. Two complementary observation modalities were used. Locator badges were used to quantify direct and indirect time unobtrusively over long periods. In-person observations were conducted to examine the workday in greater detail. Data were collected between October 2017 and May 2018.

Observations by Locator Badges

Our institution uses a system designed by Hill-Rom^® (Cary, North Carolina) to facilitate staff communication. Staff wear the I-Badge^® Locator Badge, which emits an infra-red signal.⁸ Centrally located receivers tabulate time spent by the badge wearer in each location (Appendix Figure 1). Each hospitalist was given a badge to wear at work for a minimum of six weeks, after which the I-Badge^® data were downloaded.

Schedules detailing each team’s members and assigned units (if cohorted) were retrieved. For each observed day, the hospitalist was linked to his or her team type and unit. Team lists were retrieved to ascertain patient load at the start of the day. Data sources were merged to categorize observations.

Observation Categories for Locator Badge Data

The I-Badge^® data provided details of how much time the hospitalist spent in each location (eg, nursing station, hallways, patient rooms). All observations in patient rooms were considered “direct care” while all other locations were categorized as “Indirect Care”. Observations were also categorized by the intensity of care provided on that unit, which included the Emergency Department (ED), Progressive Care Units (PCU), Medical-Surgical + PCU units (for units having a mixture of Medical-Surgical and PCU beds), and Medical-Surgical units.

In-person Observations

Four research assistants (RAs) were trained until interrater reliability using task times achieved an intraclass correlation coefficient of 0.98. Task categories included direct care (all time with patients), indirect care (computer interactions, communication), professional development, and travel and personal time. Interruptions were defined as “an unplanned and unscheduled task, causing a discontinuation, a noticeable break, or task switch behavior”.⁹ “Electronic interruptions” were caused by pagers or phones whereas in-person interruptions were “face-to-face” interruptions. When at least two tasks were performed simultaneously, it was considered multitasking. A data collection form created in REDCap was accessed on computer tablets or smartphones¹⁰ (Appendix Table 1). To limit each observation period to five hours, two RAs were scheduled each day. Observations were continued until the hospitalist reported that work activities were complete or until 5 pm.

Statistical Analysis

Due to the nested structure of the locator badge data, multilevel models that permit predictors to vary at more than one level were used.¹¹ The distribution of the duration of direct care observations was log normal for which the parameters were estimated using generalized linear mixed models (GLMM). The GLMM estimates were converted using a nonlinear transformation to predict the mean duration of interactions. The GLMM estimates were then used to predict time allocations for hospitalists with various workloads and contexts. The five team types were captured in a single categorical variable.

Univariate three-level models predicting minutes spent in direct care were tested for each predictor. Predictors, described below, were selected due to their hypothesized relation to time spent in direct patient care, or to account statistically for differences among teams due to the observational nature of the study.¹² Predictors were: Level 3, hospitalist characteristics (years since medical school, age, gender, international graduate, years at current hospital); Level 2, work day characteristics (number of units visited, number of patients visited, team type, weekday); and Level 1, individual observation characteristics (intensity of care on unit, number of visits to the same patient room per day). Predictors that were significantly related to the duration of direct care at P value <.05 and whose inclusion resulted in better model fit based on likelihood ratio tests were retained in a multivariate model. Additionally, a logistic regression model with random effects was tested to determine whether hospitalists working in GCh vs non-GCh teams (including teams with APPs and residents) made more than one visit to the same patient in a day. For duration of direct care encounters, the amount of variation explained (intraclass correlation) at the hospitalist level was .05, and at the day level was .03.

For total daily indirect care, a similar modeling process was used. A log normal distribution was used because the data was right-skewed and contained positive values. The restricted maximum likelihood method was used to calculate final estimates for models. Least square mean values for independent variables were subjected to backward transformation for interpretation. Post hoc pairwise comparisons between team types were conducted using Tukey–Kramer tests for direct and indirect care time. Analyses were conducted using SAS software version 9.4 (Cary, North Carolina).

The in-person observations were summarized using descriptive statistics. Exploratory analyses were performed using t-tests and Fisher’s exact tests to compare continuous and categorical variables respectively.

Locator Badge Observations

Participants

The 17 hospitalists had a mean (SD) age of 38 years (6.4); 10 (59%) were male, 7 (41%) were international medical graduates, and 10 (59%) had worked at the hospital ≥5 years. The duration of observation was <45 days for 7 hospitalists, 46-55 days for 4, and >55 days for 6, yielding observations for 666 hospitalist workdays. The mean time since medical school graduation was 13 years. Seven hospitalists were observed only in the GCh model, one was observed only in the non-GCh model, and nine were observed in both.

Team Characteristics

On average, non-GCh teams visited more units per day than GCh teams. Teams with APPs had higher patient loads (Table 1).

Time Observed in Direct and Indirect Care

In total, 10,522 observations were recorded in providing direct care. The average duration of a direct care encounter ranged from 4.1 to 5.8 minutes. The ratio of indirect to direct time ranged from 2.7 to 3.7 (Table 2).

The number of times that a hospitalist visited the same patient room in one day ranged from 1 to 9. Most (84%) of the patient rooms were visited once per day. The odds that a GCh hospitalist would visit a patient more than once per day were 1.8 times higher (95% CI: 1.37, 2.34; P < .0001) than for a non-GCh hospitalist (data not shown).

Predictors Associated with Time Expenditure

Predictors significantly associated with both the duration of direct care encounters and total daily indirect care time included team type and patient count. Predicted time in direct care encounters was highest for the GCh-hospitalist team (9.5 minutes) and lowest for the GCh-hospitalist with residents team (7 minutes). Predicted total indirect care time was highest for the GCh-hospitalist with APP team (160 minutes) while the lowest expenditure in indirect care time was predicted for the non-GCh-hospitalist team (102 minutes). Increasing patient load from 10 to 20 was predicted to decrease the duration of a direct care encounter by one minute (14%) and increase the total indirect care time by a larger amount (39 min, 24%).

The duration of direct care encounters was also inversely related with years since medical school and number of visits made to same patient room. Finally, acuity of care was associated with the duration of direct care encounters with the longest predicted encounters in the ED (9.4 minutes). Physician gender and age, international graduation, years at current hospital, weekday, and the number of units visited in a day were neither associated with direct care time at P value < .05 nor improved model fit and therefore were not retained in the final model (Table 3).

In-person Observations

Four hospitalists cohorted to general medical units and four non-GCh hospitalists were observed for one day each, yielding a total of 3,032 minutes of data. These hospitalists were on teams without residents or APPs. On average, GCh hospitalists had 78% of their patients on their assigned unit, rounded on fewer units (3 vs 6) and had two more patients at the start of the day than non-GCh hospitalists (14 vs 12). Age and gender distribution of the GCh and non-GCh hospitalists were similar.

As a percentage of total observed time, GCh hospitalists were noted to spend a larger proportion of the workday in computer interactions vs non-GCh hospitalists (56% vs 39%; P = .005). The proportion of time in other activities or locations was not statistically different between GCh and non-GCh hospitalists, including face-to-face communication (21% vs 15%), multitasking (18% vs 14%), time spent at the nursing station (58% vs 34%), direct care (15% vs 20%), and time traveling (4% vs 11%). The most frequently observed combination of multitasking was computer and phone use (59% of all multitasking) followed by computer use and face-to-face communication (17%; Appendix Figure 2).

The mean duration of an interruption was 1.3 minutes. More interruptions were observed in the GCh group than the non-GCh group (139 vs 102). Interruptions in the GCh group were face-to-face in 62% of instances and electronic in 25%. The remaining 13% were instances in which electronic and face-to-face interruptions occurred simultaneously. In the non-GCh group, 51% of interruptions were face-to-face; 47% were electronic; and 2% were simultaneous. GCh hospitalists were interrupted once every 14 minutes in the morning, with interruption frequency increasing to once every eight minutes in the afternoon. Non-GCh hospitalists were interrupted once every 13 minutes in the morning and saw interruption frequency decrease to once every 17 minutes in the afternoon. The task most frequently interrupted was computer use.

DISCUSSION

Previous investigations have studied the impact of cohorting on outcomes, including the facilitation of bedside rounding, adverse events, agreement between nurses and physicians on the plan of care, productivity, and the number of pages received.^13-16 Cohorting’s benefits are theorized to include increased hospitalist time with patients, while its downsides are perceived to include increased interruptions.^17,18 Neither has previously been evaluated by direct observation.

Our findings support cohorting’s association with increased hospitalist–patient time. While GCh hospitalists were observed spending 5% less time in direct care than non-GCh hospitalists by in-person observations, this difference did not achieve statistical significance and was unadjusted for hospitalist, patient load, team or patient characteristics. Using the larger badge dataset, the predicted values for time spent in direct care encounters were higher in cohorted teams. Pairwise comparisons consistently trended toward longer durations in cohorted vs noncohorted teams. The notable exception was in cohorted teams with residents, which had the shortest predicted patient visits; however, we did not have noncohorted teams with residents in our study, limiting interpretation. Additionally, the odds of repeat visits to a patient in a single day were almost twice as high in the cohorted vs noncohorted group. The magnitude of this gain, however, is estimated to be a modest 1.2 minutes for a hospitalist only team and 1.7 minutes for a hospitalist with APP team and may be insufficient to provide compassionate, patient-centered care.¹⁹

Furthermore, these gains may be eroded if patient loads are high: similar to a previous study, we found that the duration of each patient visit decreased by 14% when the load increased from 10 to 20 patients.⁶ The expected gains in efficiency from cohorting leads to an expectation that hospitalists can manage more patients, but such reflexive increases should be carefully considered.¹⁸

Similar to earlier investigations where hospitalists were found to spend 60 to 69% of the day in indirect care activities,^5,6 hospitalists in both cohorted and noncohorted models spent approximately three times more time in indirect than direct care. Cohorting was associated with increased indirect care time. This association was expected as interdisciplinary huddles and increased nursing and physician communication are both related to cohorting.^3,14 However, similar to previous reports, in-person observations revealed that the bulk of this indirect time was spent in computer interactions, rather than in interprofessional communication. Interactions with the electronic health record (EHR) consume between one-third to one-half of the day in inpatient settings.^20,21 While EHRs are intended to enhance safety, they also fulfill multiple, nonclinical purposes and increase time spent on documentation.^22,23 Nonclinical tasks may contribute to clinician burnout and detract from patient centeredness.²² Our findings suggest that cohorting may not offset the burden of these time-intensive EHR tasks. The larger expenditure of time spent in computer interactions observed in the GCh group may be partially explained both by the higher number of patients and the higher frequency of interruptions observed in this group; computer use was the task most frequently observed to be interrupted. While longer tasks are more likely to be interrupted, the interruption in turn further increases the time taken to complete the task.²⁴

The interruption rates we observed are concerning. The hospitalist workday emerges as cognitively intense. GCh hospitalists were noted to be interrupted as frequently as once every eight minutes, a rate more than double that of an earlier investigation and approaching that of ED physicians.^5,25,26 Interruptions and multitasking contribute to errors and a perception of increased workload and frustration for clinicians.^9,27-29 Although interruptions were pervasive, GCh hospitalists were interrupted more frequently, corroborating a national survey in which hospitalists perceived that cohorting increased face-to-face interruptions.³⁰ The prolonged availability of the cohorted hospitalist on the unit may require different strategies for promoting timely interactions while preserving uninterrupted work time. Our work, however, does not allow us to quantify appropriate and urgent interruptions that reflect improved teamwork and patient safety. Interruptions increase as patient loads increase.²⁵ The contribution to interruptions by the higher patient census on the GCh teams cannot be quantified in this work, but without attention to these details, potential benefits from GCh may be attenuated.

Previous work has delineated variables important in determining hospitalist workload,³¹ and our work contributes additional considerations. Hospitalist experience and resident presence on cohorted teams was associated with shorter patient visits, while ED encounters were predicted to be the most time intensive. Increasing numbers of units visited in a day was associated with more indirect time, while weekends were associated with a lower burden of indirect care. As expected, APP presence was associated with more time in indirect care as the hospitalist spends time in providing oversight. As noted, cohorting was associated with increases in both direct and indirect care time. These findings may help inform hospital medicine groups. Additionally, attention should be paid to the fact that while support for cohorting stems from investigations in which it was used as part of a bundle of interventions,^2,3 in practice, it is often implemented incompletely, with cohorted hospitalists dispersed over several units, or in isolation from other interventions.¹

Our work has several limitations. As a single-center investigation, our findings may not be generalizable to other institutions. Second, we did not evaluate clinical outcomes, clinician, patient or nursing satisfaction to assess the effect of cohorting. Third, we cannot comment on whether the observed interruptions were beneficial or detrimental. Finally, while we used statistical control for the measured imbalanced variables between groups, unmeasured confounding factors between team types including differences in patient populations, pathologies and severity of illness, or the unit’s work environment and processes may have affected results.

Our work underscores the importance of paying careful attention to specific components and monitoring for unintended consequences in a complex intervention such as cohorting to allow subsequent refinement. Further studies to assess the interplay between models of care, their impact on interruptions, multitasking, errors and clinician burnout may be necessary. Such investigations will be critical to support the evolution of hospital medicine that enables it to be the driver of excellence in care.

Acknowledgments

The authors thank the participating hospitalists, research assistants, Shelly Harrison, Joni Godfrey, Mark Luetkemeyer, Deanne Kashiwagi, Tammy Kemlage, Dustin Hertel and Adeel Zaidi for their enthusiasm and support. The authors also thank Ann Cottingham, Rich Frankel and Greg Sachs from the ASPIRE program for their guidance and vision. Dr. Weiner is Chief of Health Services Research and Development at the Richard L. Roudebush Veterans Affairs Medical Center in Indianapolis, Indiana.

Disclaimer

The views expressed in this article are those of the authors and do not necessarily represent the views of the U.S. Department of Veterans Affairs.

A 32-year-old woman presented to the emergency department (ED) with 3 months of abdominal pain and 1 week of vomiting.

The differential diagnosis of abdominal pain is broad. This presentation could be caused by disorders of the gastrointestinal (GI), gynecologic, urinary, or, less likely, the neuromuscular systems. The presence of vomiting supports a GI cause. Pregnancy should be excluded in any woman of childbearing age presenting with abdominal pain.

Characteristics of the pain, including location, temporal characteristics, severity, and aggravating and alleviating factors, can narrow the differential diagnosis. The past medical history, including prior surgeries, menstrual, and obstetric history, is also critical.

Approximately 3 months prior to presentation, she reported a tick bite that had evolved into a circumferential targetoid rash. Her primary care provider performed serologic testing for Lyme disease, which was negative, and prescribed doxycycline, which she stopped after a week because of nausea and diffuse, achy, and constant abdominal pain. After initial improvement, symptoms recurred a week prior to presentation. The nausea was now associated with intractable vomiting and anorexia. She denied hematemesis or coffee ground emesis. Her abdominal pain intensified and radiated to her back. She lost 10 pounds over the past week. She denied headache, constipation, diarrhea, blood per rectum, melena, dysuria, vaginal discharge, or rash. She reported chills and temperatures up to 37.8 ° C at home.

She had a history of migraine headaches for which she took ibuprofen occasionally but took no other prescription or over-the-counter medications. She had never smoked, consumed 2 alcoholic beverages a month, and denied illicit drug use. She lived with her boyfriend on a farm in Indiana where she raised chickens, rabbits, and ducks.

The patient dates the onset of nausea and abdominal pain to a course of doxycycline, presumably prescribed for early Lyme disease, which was stopped after only 1 week. GI side effects, including nausea, vomiting, and upper abdominal pain, are common with doxycycline and may account for the early symptoms. However, these symptoms typically resolve promptly with drug discontinuation. Doxycycline may rarely cause esophageal and gastric ulcers, which could explain her symptoms.

Fewer than half of patients with erythema migrans caused by Lyme disease are seropositive at presentation, as there has been insufficient time for antibodies to develop. Lyme disease typically affects the skin, joints, heart, and nervous system and only rarely affects the GI tract. Acute Lyme disease can cause intestinal pseudoobstruction, splenomegaly, and mild hepatitis. Although Lyme disease is unlikely to be the cause of the current symptoms, serologic testing should be repeated and should be positive if the patient now has early disseminated disease.

Patients with Lyme disease are occasionally coinfected with a second organism. Ixodes scapularis, the tick that transmits Lyme disease in the Northeast and Midwest, can be coinfected with Babesia microti, a red cell parasite. Babesiosis can persist for months and presents with fever, malaise, and many other nonspecific symptoms, including some that this patient has: anorexia, weight loss, abdominal pain, and vomiting.

The history of migraine and intractable vomiting suggests the possibility of cyclic vomiting syndrome. This syndrome is characterized by episodic bouts of vomiting lasting from hours to as long as a week. The vomiting is often accompanied by abdominal pain and occasionally headaches. Episodes are separated by asymptomatic periods that may last months. Cyclic vomiting syndrome can occur at any age but is more common in children, those with a personal or family history of migraines, and heavy users of cannabis. At least 3 stereotypical episodes are required to make the diagnosis, so a history of prior similar symptoms should be explored.

The differential diagnosis of abdominal pain and vomiting should stay broad until a comprehensive physical exam and initial laboratory tests are performed. Volume status should be assessed by estimating jugular venous pressure and by obtaining supine and standing blood pressure measurements. The abdomen should be examined carefully, and the presence or absence of hepatomegaly, splenomegaly, masses, and ascites should be specifically noted. The presence of bradycardia, oligoarticular arthritis, or neuropathy could provide supporting evidence for Lyme disease. Pregnancy is less likely given the diffuse and persistent nature of the pain but should still be excluded.

On physical examination, she was distressed, writhing on the bed, and appearing comfortable only on her side with her knees flexed. Her temperature was 36.5 ° C, heart rate 83 beats per minute, respiratory rate 18 breaths per minute, blood pressure 143/77 mmHg, and oxygen saturation 94% while breathing ambient air. Her abdomen was diffusely tender, most markedly in the epigastrium. Abdominal rigidity, rebound tenderness, and costovertebral tenderness were absent. There was no rash; the previously reported targetoid skin lesion was no longer present. The remainder of the exam was normal.

Laboratory evaluation showed a white count of 7900/mm3, hemoglobin 14.3 gm/dL with normocytic indices, and a platelet count of 175,000/mm3. Sodium was 130 mmol/L, potassium was 3.1 mmol/L, bicarbonate 26 mmol/L, blood urea nitrogen 15 mg/dL, creatinine 0.6 mg/dL, and glucose 92 mg/dL. Serum calcium, aspartate aminotransferase, alanine aminotransferase, bilirubin, and lipase were normal. A urine pregnancy test was negative. Urine analysis was negative for nitrites and leukocyte esterase. Abdominal and pelvic computed tomography (CT) scan with intravenous (IV) contrast performed 3 days prior at an outside ED revealed a 3.4 centimeter left ovarian cyst. A subsequent transvaginal ultrasound was negative for cyst torsion and confirmed appropriate placement of an intrauterine device.

The absence of abdominal rigidity and rebound tenderness does not exclude peritonitis. A normal white blood cell count also does not reliably exclude serious intraabdominal pathology. However, the CT scan argues strongly against many common causes of abdominal pain, including appendicitis, diverticulitis, perforated ulcer, intestinal obstruction, and malignancy, assuming the symptoms have not changed since it was performed.

The patient’s laboratory studies argue against biliary obstruction, pancreatitis, pregnancy, hypercalcemia, and ongoing urinary tract infection. Patients with functional gallbladder disorders may have normal laboratory and CT findings but typically have recurrent, biliary-colic-type pain. The low serum potassium, a high blood urea nitrogen to creatinine ratio, and a low serum sodium reflect her significant vomiting. The hyponatremia is consistent with the appropriate release of antidiuretic hormone (ADH) in the setting of volume depletion. She should receive isotonic fluids plus potassium in addition to symptomatic treatment of pain and nausea. Given the severity and duration of symptoms, an esophagogastroduodenoscopy (EGD) should be performed to exclude GI mucosal disease, including peptic ulcer disease and gastritis, which may not be evident on the CT scan.

Additional diagnoses should be considered at this point. This patient has exposure to chickens, ducks, rabbits, and ticks as well as reported chills and mild temperature elevation at home. Tularemia, which can be transmitted by tick bites or exposure to infected rabbits, can cause a prolonged illness. Some patients have abdominal pain, anorexia, nausea, and weight loss, although fever is usually more prominent. Tularemia is uncommon and most frequently seen in the south-central part of the United States but has been reported throughout the country. She should be queried regarding additional exposures, including well water to assess her risk for Campylobacter infection.

Opiate withdrawal can present with pain and vomiting, but she reports no opiate use and lacks other findings such pupillary dilation or piloerection. Given the prevalence of opiate abuse, however, a toxicology screen should be performed. Hypercalcemia and diabetic ketoacidosis as metabolic causes of abdominal pain have been ruled out by her laboratory values. If no other cause is identified, other metabolic etiologies like Addison disease, familial Mediterranean fever, or porphyria should be considered.

Cyclic vomiting syndrome should still be on the differential. It is a diagnosis of exclusion requiring a history of recurrent, stereotypical episodes, which should be explicitly explored.

The patient was admitted to a medical unit by the hospitalist service and received IV normal saline, parenteral potassium, and IV pantoprazole. She underwent an EGD that revealed minor erosions in the antrum of the stomach. Biopsies were obtained.

Seven hours after the endoscopy, the patient had a brief period of confusion followed by a generalized tonic-clonic seizure lasting 1 minute. A head CT without contrast was negative for any focal abnormality. Repeat laboratory evaluation revealed that serum sodium was 125 mmol/L, and serum glucose was 113 mg/dL. She was transferred to the progressive care unit and received IV levetiracetam.

The endoscopy excluded structural abnormalities of the stomach and duodenum. The patient now has an additional problem, seizure, which needs to be incorporated in the diagnostic reasoning.

Seizures can be caused by the rapid development of severe hyponatremia, with serum sodium levels usually less than 120 mmol/L. Seizures caused by hyponatremia are typically preceded by headache and lethargy, as the intracellular movement of excess water causes cerebral edema. Hyponatremia is unlikely to be the cause of her seizure but should nevertheless be evaluated with a urine sodium concentration and serum and urine osmolality. If she is euvolemic, the IV fluids should be stopped and her free water intake should be restricted to avoid worsening the hyponatremia, as it is potentially caused by the syndrome of inappropriate ADH (SIADH).

There are many other possible causes for new onset seizures in adults, including brain tumor, head trauma, alcohol withdrawal, medications, and central nervous system infection, including Lyme disease. Lyme serologies should be repeated.

In this patient, it is likely that the seizure is a manifestation of the same illness that is causing her vomiting and abdominal pain. Seizure is not a feature of cyclic vomiting syndrome in adults. It is also not a feature of tularemia, adrenal insufficiency, or opioid withdrawal.

Acute intermittent porphyria (AIP) can cause both abdominal and neurologic problems. Hyponatremia is common during acute attacks, caused by either the inappropriate release of ADH or the appropriate release of the hormone if there is fluid loss. AIP is a rare diagnosis but could explain the uncommon combination of abdominal pain, vomiting, seizure, and hyponatremia. A spot urine porphobilinogen test should be sent to assess for AIP.

Additional laboratory studies were sent. Serum osmolality was 269 mosm/kg with a corresponding urine osmolality of 699 mosm/kg. A random urine sodium was 145 mEq/L. Thyroid stimulating hormone and cosyntropin stimulating testing were normal. IgM and IgG antibodies to Borrelia burgdorferi were negative. Urine porphobilinogen was sent. An electroencephalogram did not reveal epileptiform discharges. Magnetic resonance imaging (MRI) of the brain was significant for T2/FLAIR hyperintensity in the cortex and subcortical white matter of the occipital lobes bilaterally. Hypertonic saline and fluid restriction were initiated.

The patient’s labs are consistent with SIADH. Excessive ADH release because of volume depletion and consequent hyponatremia should have improved rapidly with the administration of saline. The high urine sodium suggests that she is now volume replete, while the high urine osmolality is consistent with the presence of excessive ADH in the absence of appropriate stimuli. In the context of normal thyroid and adrenal function, the hyponatremia is likely due to the SIADH.

Negative serologic testing for Lyme disease, 3 months after the onset of rash, excludes this diagnosis.

The MRI findings are consistent with posterior reversible encephalopathy syndrome (PRES), a clinicoradiographic syndrome of headache, altered mental status, seizure, and/or vision loss with associated white matter abnormalities of the posterior cerebral hemispheres. PRES has been reported with AIP as well as other disorders, most commonly hypertensive encephalopathy, eclampsia, and immunosuppressive drug use.

The patient’s sodium improved with fluid restriction and the administration of hypertonic saline. There was no recurrence of seizure activity. Amlodipine was initiated for blood pressure readings as high as 156/106 mmHg. A hepatobiliary scan revealed a gallbladder ejection fraction of 13%. Biopsies from her endoscopy revealed nonspecific inflammation without the presence of Helicobacter pylori. The patient was discharged home 7 days after admission after stabilization of serum sodium, improvement in her abdominal pain, and tolerance of oral intake. A plan was made for outpatient cholecystectomy.

Many causes of abdominal pain have been excluded and the remaining diagnostic possibility, porphyria, is rare. The clinicians have revisited their differential and considered other causes of abdominal pain, including functional gallbladder disorders. However, chronic cholecystitis (or functional gallbladder disorder) is not this patient’s primary problem. The diffuse, severe, and constant abdominal pain prior to admission is not typical of biliary pain, and many medical conditions and drugs, including amlodipine, can lead to a positive hepatobiliary scan. Chronic cholecystitis would not explain her seizure.

AIP remains at the top of the differential for this young woman. A urine porphobilinogen has been sent and must be followed up prior to any further workup or surgery.

One week after discharge, the patient’s urine porphobilinogen resulted at 172.8 mCmol/ (upper limits of normal 8.8). Sequencing analysis for genes coding the enzymes involved in the synthetic pathway for heme were sent. Hydroxymethylbilane synthase, coproporphyrinogen oxidase, and protoporphyrinogen oxidase mutation assays were all normal. Despite the normal genetic assays, the diagnosis of AIP was made on the basis of the clinical presentation and elevated urine porphobilinogen. The patient was referred to a hematologist and initiated on oral glucose supplements and hematin infusions.

Although abdominal pain has a broad differential, the combination of abdominal pain and neurologic or psychiatric symptoms should suggest the possibility of porphyria, especially if symptoms are recurrent or unexplained. The porphyrias are a group of disorders caused by defects in the synthetic pathway of heme, leading to an overproduction and accumulation of precursors. Heme is a component of multiple proteins, including hemoglobin, myoglobin, and the cytochrome P450 enzymes. Although it is synthesized in all tissues, the bone marrow and liver are the organs most actively involved. The porphyrias can be classified according to the primary site of the overproduction and accumulation of heme precursors (liver vs bone marrow). Although there is overlap between the 2 groups, hepatic porphyrias often present with acute neurovisceral symptoms, while the erythropoietic porphyrias often cause cutaneous photosensitivity.¹

AIP is the most common hepatic porphyria with a prevalence of 1 in 20,000 in Caucasians of Western European descent.¹ AIP is caused by a defect in the gene that encodes porphobilinogen deaminase, leading to the accumulation of porphobilinogen.¹ The cardinal manifestation is an acute porphyric attack. While the precise mechanisms underlying the symptoms are unknown, the accumulating metabolites may be directly neurotoxic.² Attacks are precipitated by factors that induce heme synthesis, including caloric restriction, alcohol, and certain medications, particularly those that upregulate cyP450. The most commonly implicated drugs are anesthetics, antiepileptics, sulfonamides, rifampin, and estrogen and progesterone. Attacks can also be precipitated by changes in endogenous sex hormone levels, like the increase in progesterone seen in the luteal phase of the menstrual cycle, which may account for the higher incidence of symptomatic attacks in women.³

Acute attacks of AIP may have a wide variety of presentations; the disease was referred to as the “little imitator” in the early 20th century.⁴ The most common symptom is acute, severe abdominal pain, which may mimic an acute abdomen. Because the pain is neuropathic rather than inflammatory, abdominal tenderness, rebound, fever, and leukocytosis are usually absent, as they were in this patient. Abdominal pain is often accompanied by neuropsychiatric symptoms, including sensory and motor neuropathy, anxiety, hallucinations, delirium, and altered level of consciousness. Seizure occurs in 20% of cases. Involvement of the autonomic nervous system causes tachycardia and new onset hypertension in the majority of patients as well as restlessness and tremor. Hyponatremia, mediated by the syndrome of inappropriate ADH secretion, occurs in nearly a third of patients.^5,6 MRI findings consistent with PRES have also been described in AIP.⁷

The diagnosis of AIP is often delayed; diagnosis later in the disease course is associated with a poorer prognosis.⁸ Reported intervals between presentation and diagnosis range from several months to as long as 20 years.⁹ Associating the use of medications, caloric restriction, or the menstrual cycle with the exacerbation of symptoms or darkening of urine can help prompt an earlier diagnosis.⁶

AIP can be diagnosed by detecting a greater than 5-fold elevation of urinary porphobilinogen excretion in conjunction with the typical symptoms of an acute attack.⁵ Renal dysfunction causes urinary excretion of PBG to fall and serum levels to rise.¹⁰ Serum PBG levels should therefore be sent when AIP is suspected in the setting of renal dysfunction. The primary role of genetic testing in a patient who has AIP confirmed clinically and biochemically is to assist in genetic counseling and to identify asymptomatic family members.¹¹ Genetic testing is not required to confirm the diagnosis and does not help prognosticate. It is unusual that a mutation was not detected in this case, as the current sensitivity of genetic testing is 97% to 100%.¹¹

There are 4 principles of management of an acute porphyric attack. First, any precipitating factors such as medications should be stopped. Second, abdominal pain should be treated appropriately with opioids, if necessary. Third, if autonomic dysfunction is present, beta-blockers or clonidine should be given to treat hypertension.⁵ Finally, glucose and/or hemin should be administered to downregulate aminolevulinic acid (ALA) synthase by negative feedback. Downregulation of ALA synthase decreases the accumulation of the neurotoxic porphyrin precursors ALA and PBG.5 For patients with mild symptoms, glucose alone (300-500 g/d) may be enough to abort the attack.¹² This can be achieved via a high-carbohydrate diet in those able to tolerate oral intake or via continuous infusions of dextrose containing fluids.⁵ For more severe attacks with associated polyneuropathy, respiratory muscle weakness, or seizures, or for attacks that are not resolving, heme preparations dosed at 3 to 4 mg/kg/d for 3 to 4 days are indicated.⁵

The recent diagnosis of acute Lyme disease was a distractor in this presentation. In Lyme endemic areas, patients with erythema migrans are treated based on the clinical presentation rather than serologic testing.¹³ Although this patient took only 1 week of doxycycline, testing during this hospitalization showed that she had either been cured early or had not had Lyme disease in the first place. There is no known association between Lyme disease and the porphyrias, and doxycycline is not a common precipitant of AIP attacks.¹⁴ However, the GI side effects of doxycycline may have decreased caloric intake and ultimately provoked the patient’s first attack of AIP. The clinicians in this case appropriately avoided the “target” but hit the mark by correctly diagnosing AIP.

• Consider AIP in patients with unexplained abdominal pain, especially when accompanied by neuropsychiatric symptoms and autonomic lability.
• Diagnose AIP by sending a urine PBG during a suspected acute attack.
• Treat AIP acutely by removing precipitants, treating abdominal pain, and initiating dextrose-containing fluids and hemin infusions to downregulate ALA synthase.

The authors thank the patient who enthusiastically supported the writing of this report.

Disclosure

Warren Gavin, MD has disclosed participation in expert testimony. The authors have no financial or other conflicts of interest to disclose.

A 32-year-old woman presented to the emergency department (ED) with 3 months of abdominal pain and 1 week of vomiting.

The differential diagnosis of abdominal pain is broad. This presentation could be caused by disorders of the gastrointestinal (GI), gynecologic, urinary, or, less likely, the neuromuscular systems. The presence of vomiting supports a GI cause. Pregnancy should be excluded in any woman of childbearing age presenting with abdominal pain.

Characteristics of the pain, including location, temporal characteristics, severity, and aggravating and alleviating factors, can narrow the differential diagnosis. The past medical history, including prior surgeries, menstrual, and obstetric history, is also critical.

Approximately 3 months prior to presentation, she reported a tick bite that had evolved into a circumferential targetoid rash. Her primary care provider performed serologic testing for Lyme disease, which was negative, and prescribed doxycycline, which she stopped after a week because of nausea and diffuse, achy, and constant abdominal pain. After initial improvement, symptoms recurred a week prior to presentation. The nausea was now associated with intractable vomiting and anorexia. She denied hematemesis or coffee ground emesis. Her abdominal pain intensified and radiated to her back. She lost 10 pounds over the past week. She denied headache, constipation, diarrhea, blood per rectum, melena, dysuria, vaginal discharge, or rash. She reported chills and temperatures up to 37.8 ° C at home.

She had a history of migraine headaches for which she took ibuprofen occasionally but took no other prescription or over-the-counter medications. She had never smoked, consumed 2 alcoholic beverages a month, and denied illicit drug use. She lived with her boyfriend on a farm in Indiana where she raised chickens, rabbits, and ducks.

The patient dates the onset of nausea and abdominal pain to a course of doxycycline, presumably prescribed for early Lyme disease, which was stopped after only 1 week. GI side effects, including nausea, vomiting, and upper abdominal pain, are common with doxycycline and may account for the early symptoms. However, these symptoms typically resolve promptly with drug discontinuation. Doxycycline may rarely cause esophageal and gastric ulcers, which could explain her symptoms.

Fewer than half of patients with erythema migrans caused by Lyme disease are seropositive at presentation, as there has been insufficient time for antibodies to develop. Lyme disease typically affects the skin, joints, heart, and nervous system and only rarely affects the GI tract. Acute Lyme disease can cause intestinal pseudoobstruction, splenomegaly, and mild hepatitis. Although Lyme disease is unlikely to be the cause of the current symptoms, serologic testing should be repeated and should be positive if the patient now has early disseminated disease.

Patients with Lyme disease are occasionally coinfected with a second organism. Ixodes scapularis, the tick that transmits Lyme disease in the Northeast and Midwest, can be coinfected with Babesia microti, a red cell parasite. Babesiosis can persist for months and presents with fever, malaise, and many other nonspecific symptoms, including some that this patient has: anorexia, weight loss, abdominal pain, and vomiting.

The history of migraine and intractable vomiting suggests the possibility of cyclic vomiting syndrome. This syndrome is characterized by episodic bouts of vomiting lasting from hours to as long as a week. The vomiting is often accompanied by abdominal pain and occasionally headaches. Episodes are separated by asymptomatic periods that may last months. Cyclic vomiting syndrome can occur at any age but is more common in children, those with a personal or family history of migraines, and heavy users of cannabis. At least 3 stereotypical episodes are required to make the diagnosis, so a history of prior similar symptoms should be explored.

The differential diagnosis of abdominal pain and vomiting should stay broad until a comprehensive physical exam and initial laboratory tests are performed. Volume status should be assessed by estimating jugular venous pressure and by obtaining supine and standing blood pressure measurements. The abdomen should be examined carefully, and the presence or absence of hepatomegaly, splenomegaly, masses, and ascites should be specifically noted. The presence of bradycardia, oligoarticular arthritis, or neuropathy could provide supporting evidence for Lyme disease. Pregnancy is less likely given the diffuse and persistent nature of the pain but should still be excluded.

On physical examination, she was distressed, writhing on the bed, and appearing comfortable only on her side with her knees flexed. Her temperature was 36.5 ° C, heart rate 83 beats per minute, respiratory rate 18 breaths per minute, blood pressure 143/77 mmHg, and oxygen saturation 94% while breathing ambient air. Her abdomen was diffusely tender, most markedly in the epigastrium. Abdominal rigidity, rebound tenderness, and costovertebral tenderness were absent. There was no rash; the previously reported targetoid skin lesion was no longer present. The remainder of the exam was normal.

Laboratory evaluation showed a white count of 7900/mm3, hemoglobin 14.3 gm/dL with normocytic indices, and a platelet count of 175,000/mm3. Sodium was 130 mmol/L, potassium was 3.1 mmol/L, bicarbonate 26 mmol/L, blood urea nitrogen 15 mg/dL, creatinine 0.6 mg/dL, and glucose 92 mg/dL. Serum calcium, aspartate aminotransferase, alanine aminotransferase, bilirubin, and lipase were normal. A urine pregnancy test was negative. Urine analysis was negative for nitrites and leukocyte esterase. Abdominal and pelvic computed tomography (CT) scan with intravenous (IV) contrast performed 3 days prior at an outside ED revealed a 3.4 centimeter left ovarian cyst. A subsequent transvaginal ultrasound was negative for cyst torsion and confirmed appropriate placement of an intrauterine device.

The absence of abdominal rigidity and rebound tenderness does not exclude peritonitis. A normal white blood cell count also does not reliably exclude serious intraabdominal pathology. However, the CT scan argues strongly against many common causes of abdominal pain, including appendicitis, diverticulitis, perforated ulcer, intestinal obstruction, and malignancy, assuming the symptoms have not changed since it was performed.

The patient’s laboratory studies argue against biliary obstruction, pancreatitis, pregnancy, hypercalcemia, and ongoing urinary tract infection. Patients with functional gallbladder disorders may have normal laboratory and CT findings but typically have recurrent, biliary-colic-type pain. The low serum potassium, a high blood urea nitrogen to creatinine ratio, and a low serum sodium reflect her significant vomiting. The hyponatremia is consistent with the appropriate release of antidiuretic hormone (ADH) in the setting of volume depletion. She should receive isotonic fluids plus potassium in addition to symptomatic treatment of pain and nausea. Given the severity and duration of symptoms, an esophagogastroduodenoscopy (EGD) should be performed to exclude GI mucosal disease, including peptic ulcer disease and gastritis, which may not be evident on the CT scan.

Additional diagnoses should be considered at this point. This patient has exposure to chickens, ducks, rabbits, and ticks as well as reported chills and mild temperature elevation at home. Tularemia, which can be transmitted by tick bites or exposure to infected rabbits, can cause a prolonged illness. Some patients have abdominal pain, anorexia, nausea, and weight loss, although fever is usually more prominent. Tularemia is uncommon and most frequently seen in the south-central part of the United States but has been reported throughout the country. She should be queried regarding additional exposures, including well water to assess her risk for Campylobacter infection.

Opiate withdrawal can present with pain and vomiting, but she reports no opiate use and lacks other findings such pupillary dilation or piloerection. Given the prevalence of opiate abuse, however, a toxicology screen should be performed. Hypercalcemia and diabetic ketoacidosis as metabolic causes of abdominal pain have been ruled out by her laboratory values. If no other cause is identified, other metabolic etiologies like Addison disease, familial Mediterranean fever, or porphyria should be considered.

Cyclic vomiting syndrome should still be on the differential. It is a diagnosis of exclusion requiring a history of recurrent, stereotypical episodes, which should be explicitly explored.

The patient was admitted to a medical unit by the hospitalist service and received IV normal saline, parenteral potassium, and IV pantoprazole. She underwent an EGD that revealed minor erosions in the antrum of the stomach. Biopsies were obtained.

Seven hours after the endoscopy, the patient had a brief period of confusion followed by a generalized tonic-clonic seizure lasting 1 minute. A head CT without contrast was negative for any focal abnormality. Repeat laboratory evaluation revealed that serum sodium was 125 mmol/L, and serum glucose was 113 mg/dL. She was transferred to the progressive care unit and received IV levetiracetam.

The endoscopy excluded structural abnormalities of the stomach and duodenum. The patient now has an additional problem, seizure, which needs to be incorporated in the diagnostic reasoning.

Seizures can be caused by the rapid development of severe hyponatremia, with serum sodium levels usually less than 120 mmol/L. Seizures caused by hyponatremia are typically preceded by headache and lethargy, as the intracellular movement of excess water causes cerebral edema. Hyponatremia is unlikely to be the cause of her seizure but should nevertheless be evaluated with a urine sodium concentration and serum and urine osmolality. If she is euvolemic, the IV fluids should be stopped and her free water intake should be restricted to avoid worsening the hyponatremia, as it is potentially caused by the syndrome of inappropriate ADH (SIADH).

There are many other possible causes for new onset seizures in adults, including brain tumor, head trauma, alcohol withdrawal, medications, and central nervous system infection, including Lyme disease. Lyme serologies should be repeated.

In this patient, it is likely that the seizure is a manifestation of the same illness that is causing her vomiting and abdominal pain. Seizure is not a feature of cyclic vomiting syndrome in adults. It is also not a feature of tularemia, adrenal insufficiency, or opioid withdrawal.

Acute intermittent porphyria (AIP) can cause both abdominal and neurologic problems. Hyponatremia is common during acute attacks, caused by either the inappropriate release of ADH or the appropriate release of the hormone if there is fluid loss. AIP is a rare diagnosis but could explain the uncommon combination of abdominal pain, vomiting, seizure, and hyponatremia. A spot urine porphobilinogen test should be sent to assess for AIP.

Additional laboratory studies were sent. Serum osmolality was 269 mosm/kg with a corresponding urine osmolality of 699 mosm/kg. A random urine sodium was 145 mEq/L. Thyroid stimulating hormone and cosyntropin stimulating testing were normal. IgM and IgG antibodies to Borrelia burgdorferi were negative. Urine porphobilinogen was sent. An electroencephalogram did not reveal epileptiform discharges. Magnetic resonance imaging (MRI) of the brain was significant for T2/FLAIR hyperintensity in the cortex and subcortical white matter of the occipital lobes bilaterally. Hypertonic saline and fluid restriction were initiated.

The patient’s labs are consistent with SIADH. Excessive ADH release because of volume depletion and consequent hyponatremia should have improved rapidly with the administration of saline. The high urine sodium suggests that she is now volume replete, while the high urine osmolality is consistent with the presence of excessive ADH in the absence of appropriate stimuli. In the context of normal thyroid and adrenal function, the hyponatremia is likely due to the SIADH.

Negative serologic testing for Lyme disease, 3 months after the onset of rash, excludes this diagnosis.

The MRI findings are consistent with posterior reversible encephalopathy syndrome (PRES), a clinicoradiographic syndrome of headache, altered mental status, seizure, and/or vision loss with associated white matter abnormalities of the posterior cerebral hemispheres. PRES has been reported with AIP as well as other disorders, most commonly hypertensive encephalopathy, eclampsia, and immunosuppressive drug use.

The patient’s sodium improved with fluid restriction and the administration of hypertonic saline. There was no recurrence of seizure activity. Amlodipine was initiated for blood pressure readings as high as 156/106 mmHg. A hepatobiliary scan revealed a gallbladder ejection fraction of 13%. Biopsies from her endoscopy revealed nonspecific inflammation without the presence of Helicobacter pylori. The patient was discharged home 7 days after admission after stabilization of serum sodium, improvement in her abdominal pain, and tolerance of oral intake. A plan was made for outpatient cholecystectomy.

Many causes of abdominal pain have been excluded and the remaining diagnostic possibility, porphyria, is rare. The clinicians have revisited their differential and considered other causes of abdominal pain, including functional gallbladder disorders. However, chronic cholecystitis (or functional gallbladder disorder) is not this patient’s primary problem. The diffuse, severe, and constant abdominal pain prior to admission is not typical of biliary pain, and many medical conditions and drugs, including amlodipine, can lead to a positive hepatobiliary scan. Chronic cholecystitis would not explain her seizure.

AIP remains at the top of the differential for this young woman. A urine porphobilinogen has been sent and must be followed up prior to any further workup or surgery.

One week after discharge, the patient’s urine porphobilinogen resulted at 172.8 mCmol/ (upper limits of normal 8.8). Sequencing analysis for genes coding the enzymes involved in the synthetic pathway for heme were sent. Hydroxymethylbilane synthase, coproporphyrinogen oxidase, and protoporphyrinogen oxidase mutation assays were all normal. Despite the normal genetic assays, the diagnosis of AIP was made on the basis of the clinical presentation and elevated urine porphobilinogen. The patient was referred to a hematologist and initiated on oral glucose supplements and hematin infusions.

Although abdominal pain has a broad differential, the combination of abdominal pain and neurologic or psychiatric symptoms should suggest the possibility of porphyria, especially if symptoms are recurrent or unexplained. The porphyrias are a group of disorders caused by defects in the synthetic pathway of heme, leading to an overproduction and accumulation of precursors. Heme is a component of multiple proteins, including hemoglobin, myoglobin, and the cytochrome P450 enzymes. Although it is synthesized in all tissues, the bone marrow and liver are the organs most actively involved. The porphyrias can be classified according to the primary site of the overproduction and accumulation of heme precursors (liver vs bone marrow). Although there is overlap between the 2 groups, hepatic porphyrias often present with acute neurovisceral symptoms, while the erythropoietic porphyrias often cause cutaneous photosensitivity.¹

AIP is the most common hepatic porphyria with a prevalence of 1 in 20,000 in Caucasians of Western European descent.¹ AIP is caused by a defect in the gene that encodes porphobilinogen deaminase, leading to the accumulation of porphobilinogen.¹ The cardinal manifestation is an acute porphyric attack. While the precise mechanisms underlying the symptoms are unknown, the accumulating metabolites may be directly neurotoxic.² Attacks are precipitated by factors that induce heme synthesis, including caloric restriction, alcohol, and certain medications, particularly those that upregulate cyP450. The most commonly implicated drugs are anesthetics, antiepileptics, sulfonamides, rifampin, and estrogen and progesterone. Attacks can also be precipitated by changes in endogenous sex hormone levels, like the increase in progesterone seen in the luteal phase of the menstrual cycle, which may account for the higher incidence of symptomatic attacks in women.³

Acute attacks of AIP may have a wide variety of presentations; the disease was referred to as the “little imitator” in the early 20th century.⁴ The most common symptom is acute, severe abdominal pain, which may mimic an acute abdomen. Because the pain is neuropathic rather than inflammatory, abdominal tenderness, rebound, fever, and leukocytosis are usually absent, as they were in this patient. Abdominal pain is often accompanied by neuropsychiatric symptoms, including sensory and motor neuropathy, anxiety, hallucinations, delirium, and altered level of consciousness. Seizure occurs in 20% of cases. Involvement of the autonomic nervous system causes tachycardia and new onset hypertension in the majority of patients as well as restlessness and tremor. Hyponatremia, mediated by the syndrome of inappropriate ADH secretion, occurs in nearly a third of patients.^5,6 MRI findings consistent with PRES have also been described in AIP.⁷

The diagnosis of AIP is often delayed; diagnosis later in the disease course is associated with a poorer prognosis.⁸ Reported intervals between presentation and diagnosis range from several months to as long as 20 years.⁹ Associating the use of medications, caloric restriction, or the menstrual cycle with the exacerbation of symptoms or darkening of urine can help prompt an earlier diagnosis.⁶

AIP can be diagnosed by detecting a greater than 5-fold elevation of urinary porphobilinogen excretion in conjunction with the typical symptoms of an acute attack.⁵ Renal dysfunction causes urinary excretion of PBG to fall and serum levels to rise.¹⁰ Serum PBG levels should therefore be sent when AIP is suspected in the setting of renal dysfunction. The primary role of genetic testing in a patient who has AIP confirmed clinically and biochemically is to assist in genetic counseling and to identify asymptomatic family members.¹¹ Genetic testing is not required to confirm the diagnosis and does not help prognosticate. It is unusual that a mutation was not detected in this case, as the current sensitivity of genetic testing is 97% to 100%.¹¹

There are 4 principles of management of an acute porphyric attack. First, any precipitating factors such as medications should be stopped. Second, abdominal pain should be treated appropriately with opioids, if necessary. Third, if autonomic dysfunction is present, beta-blockers or clonidine should be given to treat hypertension.⁵ Finally, glucose and/or hemin should be administered to downregulate aminolevulinic acid (ALA) synthase by negative feedback. Downregulation of ALA synthase decreases the accumulation of the neurotoxic porphyrin precursors ALA and PBG.5 For patients with mild symptoms, glucose alone (300-500 g/d) may be enough to abort the attack.¹² This can be achieved via a high-carbohydrate diet in those able to tolerate oral intake or via continuous infusions of dextrose containing fluids.⁵ For more severe attacks with associated polyneuropathy, respiratory muscle weakness, or seizures, or for attacks that are not resolving, heme preparations dosed at 3 to 4 mg/kg/d for 3 to 4 days are indicated.⁵

The recent diagnosis of acute Lyme disease was a distractor in this presentation. In Lyme endemic areas, patients with erythema migrans are treated based on the clinical presentation rather than serologic testing.¹³ Although this patient took only 1 week of doxycycline, testing during this hospitalization showed that she had either been cured early or had not had Lyme disease in the first place. There is no known association between Lyme disease and the porphyrias, and doxycycline is not a common precipitant of AIP attacks.¹⁴ However, the GI side effects of doxycycline may have decreased caloric intake and ultimately provoked the patient’s first attack of AIP. The clinicians in this case appropriately avoided the “target” but hit the mark by correctly diagnosing AIP.

• Consider AIP in patients with unexplained abdominal pain, especially when accompanied by neuropsychiatric symptoms and autonomic lability.
• Diagnose AIP by sending a urine PBG during a suspected acute attack.
• Treat AIP acutely by removing precipitants, treating abdominal pain, and initiating dextrose-containing fluids and hemin infusions to downregulate ALA synthase.

The authors thank the patient who enthusiastically supported the writing of this report.

Disclosure

Warren Gavin, MD has disclosed participation in expert testimony. The authors have no financial or other conflicts of interest to disclose.

A 32-year-old woman presented to the emergency department (ED) with 3 months of abdominal pain and 1 week of vomiting.

The differential diagnosis of abdominal pain is broad. This presentation could be caused by disorders of the gastrointestinal (GI), gynecologic, urinary, or, less likely, the neuromuscular systems. The presence of vomiting supports a GI cause. Pregnancy should be excluded in any woman of childbearing age presenting with abdominal pain.

Characteristics of the pain, including location, temporal characteristics, severity, and aggravating and alleviating factors, can narrow the differential diagnosis. The past medical history, including prior surgeries, menstrual, and obstetric history, is also critical.

Approximately 3 months prior to presentation, she reported a tick bite that had evolved into a circumferential targetoid rash. Her primary care provider performed serologic testing for Lyme disease, which was negative, and prescribed doxycycline, which she stopped after a week because of nausea and diffuse, achy, and constant abdominal pain. After initial improvement, symptoms recurred a week prior to presentation. The nausea was now associated with intractable vomiting and anorexia. She denied hematemesis or coffee ground emesis. Her abdominal pain intensified and radiated to her back. She lost 10 pounds over the past week. She denied headache, constipation, diarrhea, blood per rectum, melena, dysuria, vaginal discharge, or rash. She reported chills and temperatures up to 37.8 ° C at home.

She had a history of migraine headaches for which she took ibuprofen occasionally but took no other prescription or over-the-counter medications. She had never smoked, consumed 2 alcoholic beverages a month, and denied illicit drug use. She lived with her boyfriend on a farm in Indiana where she raised chickens, rabbits, and ducks.

The patient dates the onset of nausea and abdominal pain to a course of doxycycline, presumably prescribed for early Lyme disease, which was stopped after only 1 week. GI side effects, including nausea, vomiting, and upper abdominal pain, are common with doxycycline and may account for the early symptoms. However, these symptoms typically resolve promptly with drug discontinuation. Doxycycline may rarely cause esophageal and gastric ulcers, which could explain her symptoms.

Fewer than half of patients with erythema migrans caused by Lyme disease are seropositive at presentation, as there has been insufficient time for antibodies to develop. Lyme disease typically affects the skin, joints, heart, and nervous system and only rarely affects the GI tract. Acute Lyme disease can cause intestinal pseudoobstruction, splenomegaly, and mild hepatitis. Although Lyme disease is unlikely to be the cause of the current symptoms, serologic testing should be repeated and should be positive if the patient now has early disseminated disease.

Patients with Lyme disease are occasionally coinfected with a second organism. Ixodes scapularis, the tick that transmits Lyme disease in the Northeast and Midwest, can be coinfected with Babesia microti, a red cell parasite. Babesiosis can persist for months and presents with fever, malaise, and many other nonspecific symptoms, including some that this patient has: anorexia, weight loss, abdominal pain, and vomiting.

The history of migraine and intractable vomiting suggests the possibility of cyclic vomiting syndrome. This syndrome is characterized by episodic bouts of vomiting lasting from hours to as long as a week. The vomiting is often accompanied by abdominal pain and occasionally headaches. Episodes are separated by asymptomatic periods that may last months. Cyclic vomiting syndrome can occur at any age but is more common in children, those with a personal or family history of migraines, and heavy users of cannabis. At least 3 stereotypical episodes are required to make the diagnosis, so a history of prior similar symptoms should be explored.

The differential diagnosis of abdominal pain and vomiting should stay broad until a comprehensive physical exam and initial laboratory tests are performed. Volume status should be assessed by estimating jugular venous pressure and by obtaining supine and standing blood pressure measurements. The abdomen should be examined carefully, and the presence or absence of hepatomegaly, splenomegaly, masses, and ascites should be specifically noted. The presence of bradycardia, oligoarticular arthritis, or neuropathy could provide supporting evidence for Lyme disease. Pregnancy is less likely given the diffuse and persistent nature of the pain but should still be excluded.

On physical examination, she was distressed, writhing on the bed, and appearing comfortable only on her side with her knees flexed. Her temperature was 36.5 ° C, heart rate 83 beats per minute, respiratory rate 18 breaths per minute, blood pressure 143/77 mmHg, and oxygen saturation 94% while breathing ambient air. Her abdomen was diffusely tender, most markedly in the epigastrium. Abdominal rigidity, rebound tenderness, and costovertebral tenderness were absent. There was no rash; the previously reported targetoid skin lesion was no longer present. The remainder of the exam was normal.

Laboratory evaluation showed a white count of 7900/mm3, hemoglobin 14.3 gm/dL with normocytic indices, and a platelet count of 175,000/mm3. Sodium was 130 mmol/L, potassium was 3.1 mmol/L, bicarbonate 26 mmol/L, blood urea nitrogen 15 mg/dL, creatinine 0.6 mg/dL, and glucose 92 mg/dL. Serum calcium, aspartate aminotransferase, alanine aminotransferase, bilirubin, and lipase were normal. A urine pregnancy test was negative. Urine analysis was negative for nitrites and leukocyte esterase. Abdominal and pelvic computed tomography (CT) scan with intravenous (IV) contrast performed 3 days prior at an outside ED revealed a 3.4 centimeter left ovarian cyst. A subsequent transvaginal ultrasound was negative for cyst torsion and confirmed appropriate placement of an intrauterine device.

The absence of abdominal rigidity and rebound tenderness does not exclude peritonitis. A normal white blood cell count also does not reliably exclude serious intraabdominal pathology. However, the CT scan argues strongly against many common causes of abdominal pain, including appendicitis, diverticulitis, perforated ulcer, intestinal obstruction, and malignancy, assuming the symptoms have not changed since it was performed.

The patient’s laboratory studies argue against biliary obstruction, pancreatitis, pregnancy, hypercalcemia, and ongoing urinary tract infection. Patients with functional gallbladder disorders may have normal laboratory and CT findings but typically have recurrent, biliary-colic-type pain. The low serum potassium, a high blood urea nitrogen to creatinine ratio, and a low serum sodium reflect her significant vomiting. The hyponatremia is consistent with the appropriate release of antidiuretic hormone (ADH) in the setting of volume depletion. She should receive isotonic fluids plus potassium in addition to symptomatic treatment of pain and nausea. Given the severity and duration of symptoms, an esophagogastroduodenoscopy (EGD) should be performed to exclude GI mucosal disease, including peptic ulcer disease and gastritis, which may not be evident on the CT scan.

Additional diagnoses should be considered at this point. This patient has exposure to chickens, ducks, rabbits, and ticks as well as reported chills and mild temperature elevation at home. Tularemia, which can be transmitted by tick bites or exposure to infected rabbits, can cause a prolonged illness. Some patients have abdominal pain, anorexia, nausea, and weight loss, although fever is usually more prominent. Tularemia is uncommon and most frequently seen in the south-central part of the United States but has been reported throughout the country. She should be queried regarding additional exposures, including well water to assess her risk for Campylobacter infection.

Opiate withdrawal can present with pain and vomiting, but she reports no opiate use and lacks other findings such pupillary dilation or piloerection. Given the prevalence of opiate abuse, however, a toxicology screen should be performed. Hypercalcemia and diabetic ketoacidosis as metabolic causes of abdominal pain have been ruled out by her laboratory values. If no other cause is identified, other metabolic etiologies like Addison disease, familial Mediterranean fever, or porphyria should be considered.

Cyclic vomiting syndrome should still be on the differential. It is a diagnosis of exclusion requiring a history of recurrent, stereotypical episodes, which should be explicitly explored.

The patient was admitted to a medical unit by the hospitalist service and received IV normal saline, parenteral potassium, and IV pantoprazole. She underwent an EGD that revealed minor erosions in the antrum of the stomach. Biopsies were obtained.

Seven hours after the endoscopy, the patient had a brief period of confusion followed by a generalized tonic-clonic seizure lasting 1 minute. A head CT without contrast was negative for any focal abnormality. Repeat laboratory evaluation revealed that serum sodium was 125 mmol/L, and serum glucose was 113 mg/dL. She was transferred to the progressive care unit and received IV levetiracetam.

The endoscopy excluded structural abnormalities of the stomach and duodenum. The patient now has an additional problem, seizure, which needs to be incorporated in the diagnostic reasoning.

Seizures can be caused by the rapid development of severe hyponatremia, with serum sodium levels usually less than 120 mmol/L. Seizures caused by hyponatremia are typically preceded by headache and lethargy, as the intracellular movement of excess water causes cerebral edema. Hyponatremia is unlikely to be the cause of her seizure but should nevertheless be evaluated with a urine sodium concentration and serum and urine osmolality. If she is euvolemic, the IV fluids should be stopped and her free water intake should be restricted to avoid worsening the hyponatremia, as it is potentially caused by the syndrome of inappropriate ADH (SIADH).

There are many other possible causes for new onset seizures in adults, including brain tumor, head trauma, alcohol withdrawal, medications, and central nervous system infection, including Lyme disease. Lyme serologies should be repeated.

In this patient, it is likely that the seizure is a manifestation of the same illness that is causing her vomiting and abdominal pain. Seizure is not a feature of cyclic vomiting syndrome in adults. It is also not a feature of tularemia, adrenal insufficiency, or opioid withdrawal.

Acute intermittent porphyria (AIP) can cause both abdominal and neurologic problems. Hyponatremia is common during acute attacks, caused by either the inappropriate release of ADH or the appropriate release of the hormone if there is fluid loss. AIP is a rare diagnosis but could explain the uncommon combination of abdominal pain, vomiting, seizure, and hyponatremia. A spot urine porphobilinogen test should be sent to assess for AIP.

Additional laboratory studies were sent. Serum osmolality was 269 mosm/kg with a corresponding urine osmolality of 699 mosm/kg. A random urine sodium was 145 mEq/L. Thyroid stimulating hormone and cosyntropin stimulating testing were normal. IgM and IgG antibodies to Borrelia burgdorferi were negative. Urine porphobilinogen was sent. An electroencephalogram did not reveal epileptiform discharges. Magnetic resonance imaging (MRI) of the brain was significant for T2/FLAIR hyperintensity in the cortex and subcortical white matter of the occipital lobes bilaterally. Hypertonic saline and fluid restriction were initiated.

The patient’s labs are consistent with SIADH. Excessive ADH release because of volume depletion and consequent hyponatremia should have improved rapidly with the administration of saline. The high urine sodium suggests that she is now volume replete, while the high urine osmolality is consistent with the presence of excessive ADH in the absence of appropriate stimuli. In the context of normal thyroid and adrenal function, the hyponatremia is likely due to the SIADH.

Negative serologic testing for Lyme disease, 3 months after the onset of rash, excludes this diagnosis.

The MRI findings are consistent with posterior reversible encephalopathy syndrome (PRES), a clinicoradiographic syndrome of headache, altered mental status, seizure, and/or vision loss with associated white matter abnormalities of the posterior cerebral hemispheres. PRES has been reported with AIP as well as other disorders, most commonly hypertensive encephalopathy, eclampsia, and immunosuppressive drug use.

The patient’s sodium improved with fluid restriction and the administration of hypertonic saline. There was no recurrence of seizure activity. Amlodipine was initiated for blood pressure readings as high as 156/106 mmHg. A hepatobiliary scan revealed a gallbladder ejection fraction of 13%. Biopsies from her endoscopy revealed nonspecific inflammation without the presence of Helicobacter pylori. The patient was discharged home 7 days after admission after stabilization of serum sodium, improvement in her abdominal pain, and tolerance of oral intake. A plan was made for outpatient cholecystectomy.

Many causes of abdominal pain have been excluded and the remaining diagnostic possibility, porphyria, is rare. The clinicians have revisited their differential and considered other causes of abdominal pain, including functional gallbladder disorders. However, chronic cholecystitis (or functional gallbladder disorder) is not this patient’s primary problem. The diffuse, severe, and constant abdominal pain prior to admission is not typical of biliary pain, and many medical conditions and drugs, including amlodipine, can lead to a positive hepatobiliary scan. Chronic cholecystitis would not explain her seizure.

AIP remains at the top of the differential for this young woman. A urine porphobilinogen has been sent and must be followed up prior to any further workup or surgery.

One week after discharge, the patient’s urine porphobilinogen resulted at 172.8 mCmol/ (upper limits of normal 8.8). Sequencing analysis for genes coding the enzymes involved in the synthetic pathway for heme were sent. Hydroxymethylbilane synthase, coproporphyrinogen oxidase, and protoporphyrinogen oxidase mutation assays were all normal. Despite the normal genetic assays, the diagnosis of AIP was made on the basis of the clinical presentation and elevated urine porphobilinogen. The patient was referred to a hematologist and initiated on oral glucose supplements and hematin infusions.

Although abdominal pain has a broad differential, the combination of abdominal pain and neurologic or psychiatric symptoms should suggest the possibility of porphyria, especially if symptoms are recurrent or unexplained. The porphyrias are a group of disorders caused by defects in the synthetic pathway of heme, leading to an overproduction and accumulation of precursors. Heme is a component of multiple proteins, including hemoglobin, myoglobin, and the cytochrome P450 enzymes. Although it is synthesized in all tissues, the bone marrow and liver are the organs most actively involved. The porphyrias can be classified according to the primary site of the overproduction and accumulation of heme precursors (liver vs bone marrow). Although there is overlap between the 2 groups, hepatic porphyrias often present with acute neurovisceral symptoms, while the erythropoietic porphyrias often cause cutaneous photosensitivity.¹

AIP is the most common hepatic porphyria with a prevalence of 1 in 20,000 in Caucasians of Western European descent.¹ AIP is caused by a defect in the gene that encodes porphobilinogen deaminase, leading to the accumulation of porphobilinogen.¹ The cardinal manifestation is an acute porphyric attack. While the precise mechanisms underlying the symptoms are unknown, the accumulating metabolites may be directly neurotoxic.² Attacks are precipitated by factors that induce heme synthesis, including caloric restriction, alcohol, and certain medications, particularly those that upregulate cyP450. The most commonly implicated drugs are anesthetics, antiepileptics, sulfonamides, rifampin, and estrogen and progesterone. Attacks can also be precipitated by changes in endogenous sex hormone levels, like the increase in progesterone seen in the luteal phase of the menstrual cycle, which may account for the higher incidence of symptomatic attacks in women.³

Acute attacks of AIP may have a wide variety of presentations; the disease was referred to as the “little imitator” in the early 20th century.⁴ The most common symptom is acute, severe abdominal pain, which may mimic an acute abdomen. Because the pain is neuropathic rather than inflammatory, abdominal tenderness, rebound, fever, and leukocytosis are usually absent, as they were in this patient. Abdominal pain is often accompanied by neuropsychiatric symptoms, including sensory and motor neuropathy, anxiety, hallucinations, delirium, and altered level of consciousness. Seizure occurs in 20% of cases. Involvement of the autonomic nervous system causes tachycardia and new onset hypertension in the majority of patients as well as restlessness and tremor. Hyponatremia, mediated by the syndrome of inappropriate ADH secretion, occurs in nearly a third of patients.^5,6 MRI findings consistent with PRES have also been described in AIP.⁷

The diagnosis of AIP is often delayed; diagnosis later in the disease course is associated with a poorer prognosis.⁸ Reported intervals between presentation and diagnosis range from several months to as long as 20 years.⁹ Associating the use of medications, caloric restriction, or the menstrual cycle with the exacerbation of symptoms or darkening of urine can help prompt an earlier diagnosis.⁶

AIP can be diagnosed by detecting a greater than 5-fold elevation of urinary porphobilinogen excretion in conjunction with the typical symptoms of an acute attack.⁵ Renal dysfunction causes urinary excretion of PBG to fall and serum levels to rise.¹⁰ Serum PBG levels should therefore be sent when AIP is suspected in the setting of renal dysfunction. The primary role of genetic testing in a patient who has AIP confirmed clinically and biochemically is to assist in genetic counseling and to identify asymptomatic family members.¹¹ Genetic testing is not required to confirm the diagnosis and does not help prognosticate. It is unusual that a mutation was not detected in this case, as the current sensitivity of genetic testing is 97% to 100%.¹¹

There are 4 principles of management of an acute porphyric attack. First, any precipitating factors such as medications should be stopped. Second, abdominal pain should be treated appropriately with opioids, if necessary. Third, if autonomic dysfunction is present, beta-blockers or clonidine should be given to treat hypertension.⁵ Finally, glucose and/or hemin should be administered to downregulate aminolevulinic acid (ALA) synthase by negative feedback. Downregulation of ALA synthase decreases the accumulation of the neurotoxic porphyrin precursors ALA and PBG.5 For patients with mild symptoms, glucose alone (300-500 g/d) may be enough to abort the attack.¹² This can be achieved via a high-carbohydrate diet in those able to tolerate oral intake or via continuous infusions of dextrose containing fluids.⁵ For more severe attacks with associated polyneuropathy, respiratory muscle weakness, or seizures, or for attacks that are not resolving, heme preparations dosed at 3 to 4 mg/kg/d for 3 to 4 days are indicated.⁵

The recent diagnosis of acute Lyme disease was a distractor in this presentation. In Lyme endemic areas, patients with erythema migrans are treated based on the clinical presentation rather than serologic testing.¹³ Although this patient took only 1 week of doxycycline, testing during this hospitalization showed that she had either been cured early or had not had Lyme disease in the first place. There is no known association between Lyme disease and the porphyrias, and doxycycline is not a common precipitant of AIP attacks.¹⁴ However, the GI side effects of doxycycline may have decreased caloric intake and ultimately provoked the patient’s first attack of AIP. The clinicians in this case appropriately avoided the “target” but hit the mark by correctly diagnosing AIP.

• Consider AIP in patients with unexplained abdominal pain, especially when accompanied by neuropsychiatric symptoms and autonomic lability.
• Diagnose AIP by sending a urine PBG during a suspected acute attack.
• Treat AIP acutely by removing precipitants, treating abdominal pain, and initiating dextrose-containing fluids and hemin infusions to downregulate ALA synthase.

The authors thank the patient who enthusiastically supported the writing of this report.

Disclosure

Warren Gavin, MD has disclosed participation in expert testimony. The authors have no financial or other conflicts of interest to disclose.