The American College of Cardiology (ACC) and the American Heart Association (AHA) recommend early intervention for older persons with acute coronary syndrome (ACS) to improve prognosis. However, numerous studies demonstrate that elderly patients with acute myocardial infarction (AMI) are less likely than their younger counterparts to receive guideline‐recommended therapies.13 No prior studies specifically demonstrate that adherence to AMI guidelines is effective in patients admitted from post‐acute or long‐term care (PAC/LTC) settings such as nursing homes, intermediate care facilities, and LTC hospitals. Recognizing that the barriers to guideline‐adherent care among the elderly may also be present for clinically‐complex PAC/LTC patients, we examined whether hospitalized patients with AMI admitted from PAC/LTC settings were less likely to receive guideline‐recommended therapies and if guideline‐concordant treatment was associated with short‐term (30‐day) survival in this relatively vulnerable subgroup of patients.

Medical decision making, including applicability of guidelines, is not exclusively based on empirical evidence but is also related to morally complex issues such as patient age, social status, and other unknown factors. However, lack of outcome expectancy may limit adherence for AMI care in PAC/LTC populations.4 In particular, treating physicians may not expect that desired outcomes will result when guidelines are followed in the PAC/LTC group compared to community‐based patients. This notion is supported by other research indicating that physicians caring for nursing home residents' chronic health conditions often tailor the care approach according to the patients' functional and cognitive status rather than adhering to recommended guidelines.5 In a study that used hypothetical scenarios, nursing home patients with a better physical condition, a more obvious social role, and a lower age were more likely to be treated with life‐sustaining treatments than were other patients.6 For AMI care, some physicians provide care that is not guideline‐adherent due to concerns that reduced renal function is an absolute rather than relative contraindication to angiography.7, 8 And, because the clinical trials that informed practice guidelines for AMI care did not explicitly include individuals with the chronic complex medical problems prevalent among the PAC/LTC population, treating clinicians may be reluctant to apply acute care guidelines to this subgroup.9 However, we know of no prior research demonstrating that guideline‐adherent care for either chronic or acute conditions results in differential outcomes for PAC/LTC patients cared for in the hospital setting.

For the present study, we examined whether admission source was an independent predictor of AMI treatment and whether guideline‐concordant care was related to mortality for those admitted from PAC/LTC and community settings. We hypothesized that rates of guideline‐concordant care would be higher for patients admitted from community settings vs. PAC/LTC and that differences between the groups would be greater for more intensive interventions such as reperfusion compared to aspirin. The data included detailed clinical eligibility information for treatments based on contemporary ACC/AHA guidelines,10 along with numerous other patient demographic and clinical characteristics, thus allowing us to address the presumptive concern that PAC/LTC patients were sicker or otherwise less‐suited for treatment than other patients.

Methods

This retrospective cohort study relied on existing observational data. The primary data source for this research was the Cooperative Cardiovascular Project (CCP) national baseline data. The CCP was sponsored by the Centers for Medicare & Medicaid Services (CMS) to measure the quality of care provided to a national cohort of Medicare patients hospitalized with AMI. The national data collection and reporting effort was administered through the 53 Medicare Quality Improvement Organization (QIO) contracts established to serve each State, the District of Columbia, Puerto Rico, and the U.S. Virgin Islands. Hospital medical records were requested under QIO authority and then abstracted by centrally‐contracted Clinical Data Abstraction Centers (CDACs). Data quality monitoring involved random reabstraction of records with double entry of the information to ensure consistency across personnel, and data were found to be very reliable. Detailed data collection procedures and main findings from these data have been reported elsewhere.1126

The CCP baseline data included an initial sample of 234,754 records abstracted from inpatient medical charts for fee‐for‐services Medicare beneficiaries hospitalized in 1 of 6684 hospitals located in any of the 50 states, the District of Columbia, Puerto Rico, the U.S. Virgin Islands, American Samoa, Guam, and the Northern Mariana Islands between February 1994 and July 1995. Although the data analyzed for this research relate to hospitalizations for AMI in 1994‐1995, the 2008 ACC/AHA report regarding AMI performance measures retains recommendations for both early aspirin and reperfusion treatments.27 Even though the data are not derived from recent years, the CCP baseline data represent a unique dataset to address questions related to both clinical eligibility and guideline compliance for both community and PAC/LTC patients. The inclusion of PAC/LTC admissions and detailed information regarding clinical eligibility for treatment are particularly important to adequately address the research aim; the CCP baseline data are the single extant U.S. data source we identified that has both features.

AMI cases were identified through inpatient hospital claims using an International Classification of Diseases, 9th Revision, Clinical Modification (ICD‐9‐CM) principal discharge diagnosis of 410 (ACS) for extended chart review to verify AMI and determine clinical eligibility for treatments. CCP records were subsequently linked with the Medicare Denominator File, Area Resource File (ARF), and Medicare PPS cost reports for hospitals (PPS) to obtain additional information regarding patients, local health resources, and admitting hospital.

For the present study, we excluded cases without a confirmed AMI diagnosis; cases with missing geographic information to allow us to control for local practice variation including all cases from outside the Continental U.S.; cases admitted to nonacute facilities or with inadequate information to link with provider data; and cases that originated in states selected for the CCP pilot study due to differences in record abstraction timing and some of the measures. Clinical eligibility for treatments relied on the standardized criteria established by the CCP advisory panel and used in other research.10, 14, 2831

To test whether admission from a LTC setting was negatively associated with guideline adherence and if the relationship varied according to the intensity of the treatment, we examined 2 guidelines related to early interventions care during the hospital stay: (1) administration of aspirin; and (2) reperfusion through either thrombolytic drugs or percutaneous intervention (PTCA). We chose these measures because they range from a simple and readily‐available medical intervention (aspirin), to a clinically complex and costly intervention for a more clinically‐select group of patients (reperfusion). The hypothesis that more intensive acute treatment would be less likely for patients admitted from PAC/LTC settings was empirically tested by examining the differences in overall probabilities and adjusted probabilities of receiving each of these interventions. We then modeled the odds ratios (ORs) for survival based on receiving these treatments.

Guideline adherence and clinical eligibility indicators for the CCP data have been presented elsewhere.10, 20, 23, 29, 32 Using these criteria, we divided patients into clinical eligibility groups, including ideal candidates, eligible candidates, and candidates for whom the care was not indicated. For the present research, all eligible patients were included in the sample; with ideal eligibility included as a covariate in the regression models. All patients in the study sample were at least minimally eligible to receive aspirin during their hospital stay. Ideal candidates for aspirin did not have: a gastrointestinal (GI) ulcer, same day admission/discharge, history of bleeding disorder, risk of bleeding, anemia, allergy to aspirin, warfarin, or terminal illness. Eligible candidates for reperfusion via PTCA or thrombolysis were not transferred from another hospital or emergency department. Ideal eligibility for reperfusion required, in addition, that the patient: was under age 80 years; arrived at the hospital within 6 hours of symptom onset; showed evidence of a transmural (Q‐wave) MI or ST elevation in 2 contiguous leads on arrival electrocardiogram (ECG); was not taking warfarin; did not have cardiac arrest requiring cardiopulmonary resuscitation (CPR), cardioversion, defibrillation, or chemical cardioversion in the 6 hours prior; did not refuse a thrombolytic; did not have cardiac catheterization without PTCA within 12 hours of arrival; had no evidence of hepatic failure or cirrhosis; had no history of active ulcer disease, internal bleeding, trauma, or injury in the month prior to arrival; and had no bleeding risk, cerebral vascular accident, or surgery/biopsy within 2 months of admission.

Prearrival setting was of particular interest for the present study; this information was derived from the patient's medical chart using a standardized chart abstraction process for the CCP. From the original admission source categories, we created a single dichotomous variable that indicated PAC/LTC vs. community setting prior to arrival. We defined PAC/LTC settings to include patients admitted from either a skilled nursing facility (SNF) or intermediate care facility (ICF), chronic hospital, or other residential care facility. Three categories of admission source were used to identify the comparison sample: home, noninstitutional setting, and outpatient setting.

Because differences in care according to admission source could result from observable causes, multiple regression analysis was incorporated to control for observed factors previously shown to be associated with guideline adherence. These included: ideal eligibility for treatment; age; Caucasian (vs. other) ethnicity; gender; limitation of aggressive treatment orders (eg, do not resuscitate, do not intubate, chemical code only, no cardiac monitoring, no invasive procedures, no vasopressor, no antiarrhythmic therapy, no feeding tube, palliative care measures only); Charlson comorbidity index and Acute Physiology, Age, Chronic Health Evaluation assessment (3rd revision) (APACHE III) score, body mass index (BMI), rural hospital location, hospital teaching status, and number of full‐time equivalent cardiologists on staff at the treating hospital. The regression methods also included adjustment for clustering of patients within health services area to account for geographic variation in practice patterns.33

In developing the regression model, we predicted whether the patient received care in accord with guidelines and 30‐day mortality. We also tested whether the regression errors terms (unobserved variables) for these equations were significantly related to error terms in a regression to predict source of admission, which would indicate rejecting the hypothesis that admission source and treatments were determined independently of each other. In particular, admission source may be a proxy for underlying health status (severity of illness), care preferences, or other unobserved factors that differ systematically between patients admitted from the community vs. those admitted from PAC/LTC. In testing the models, we found that the error terms for both treatments (aspirin and reperfusion) and admission source models were significantly negatively correlated (rho or chi‐square P value <0.001), indicating the need to adjust regression estimates to account for unobserved variables related to both admission source and guideline concordant treatment. Because we rejected the hypothesis that admission source was exogenous to treatments, a seemingly‐unrelated regressions (SUR) bivariate probit model was deemed appropriate, as this methodology corrects for correlation between unobserved variables that are related to both admission source and treatment decisions (eg, residual confounding).34 And, since coefficients from SUR bivariate probit models are not directly interpretable as either ORs or relative risks with respect to the outcome variables, we converted the coefficients to reflect marginal probabilities. The correlation in error terms for models predicting 30‐day mortality and admission source was not substantively or statistically significant. As such, we utilized standard logistic regression methods for assessing mortality. Mortality models were predicted separately according to admission source and treatment to allow presentation of ORs associated with each treatment for each group.

Analyses used the Stata statistical package (version 10.1 SE).35 Approval for this use of the CCP data was received from the CMS. Approval for the data analysis protocol was received from the authors' institutional review board.

Results

Of the 128,183 patients in the analytic sample, 7.6% (n = 8151) were admitted from PAC/LTC (Table 1). The members of the PAC/LTC cohort were older on average than the community‐dwelling cohort (83 vs. 76 years, P < 0.001) and more likely to be female (69% vs. 48%, P < 0.001). Limitation of aggressive treatment orders (LAT/DNR) were in place for 55% of the PAC/LTC cohort compared to only 16% of the community‐dwelling cohort (P < 0.001). Severity of illness scores were higher among the PAC/LTC cohort with APACHE III scores of 50.8 in the PAC/LTC cohort vs. 36.8 in the community‐dwelling cohort (P < 0.001). The PAC/LTC cohort also had lower BMI (P < 0.001). Mortality at 30 days and 1 year was 39.5% and 65.4%, respectively, in the PAC/LTC cohort vs. 17.6% and 33.4%, respectively, in the community‐dwelling cohort. These differences across groups were significant at both time points (P < 0.001). PAC/LTC admissions were significantly more likely to be admitted to a hospital located in a rural area (P < 0.001), though the numbers of full‐time equivalent residents and presence of cardiologists in the treating hospitals were similar across groups.

Table 2 provides overall unadjusted data comparing eligibility and treatment information for PAC/LTC and community admissions. Rates of guideline adherence were uniformly higher for patients admitted from the community. Guideline adherence rates were higher for aspirin compared to reperfusion, and followed the predicted pattern that more resource‐intensive treatments would be less common for both groups and that PAC/LTC admissions would be less likely to receive treatments compared to patients admitted from community settings. Though all 8151 PAC/LTC patients were eligible to receive aspirin, only 4370 were ideally eligible and 3015 (69%) received acetylsalicylic acid (ASA). There were 1418 PAC/LTC patients (17% of the PAC/LTC sample) meeting at least minimal eligibility requirements for reperfusion. Among the 214 PAC/LTC cases that were ideally eligible for reperfusion, 65 (30%) received the treatment; 12 patients received PTCA and 53 received thrombolytic agents. Eligibility and treatment rates for reperfusion were substantially higher for the community sample, with almost 27% meeting minimum eligibility requirements and 60% of the ideally‐eligible group receiving the treatment.

Table 3 presents the adjusted probability of treatment based upon the SUR bivariate probit regression model. As with the unadjusted results presented in Table 2, PAC/LTC patients had a lower probability of treatment even after controlling for important patient and hospital characteristics. Compared to the unadjusted results, the adjusted probabilities calculated with the SUR bivariate probit model indicated a relatively higher predicted probability of treatment for the PAC/LTC patients and a relatively lower predicted probability of treatment among the community patients. In other words, the probability of treatment becomes more similar across groups once the adjustments for both observed and unobserved differences in patient characteristics are considered. Nonetheless, a difference in probability of treatment remains across the 2 groups.

To determine whether there was survival difference associated with treatment in these data, we conducted a logistic regression analyses to predict 30‐day mortality for both groups (Tables 4 and 5). Table 4 presents results (ORs) of our models emphasizing the relationship between aspirin and 30‐day mortality, while Table 5 presents the models with reperfusion. Model discrimination was tested using a C‐statistic and was at least 0.70 for all models, indicating good predictive validity. However, for the reperfusion models (Table 5) there were relatively few PAC/LTC patients ideally eligible for treatment, which limited statistical power. There was an association between aspirin provision and improved survival for both the PAC/LTC and community admissions (95% confidence intervals [CIs] were less than 1.0) for all eligible patients. For the eligible samples, we did not find the anticipated relationship between reperfusion and 30‐day survival. The ORs and CIs for community admissions were significantly greater than 1.0. However, we noted lower ORs of mortality for the subgroups of ideally eligible patients, with 95% CIs under 1.0 for both PAC/LTC and community admissions, indicating better survival among those who were ideally eligible for reperfusion treatment. The unadjusted data indicated that PAC/LTC patients were much more likely than their community counterparts to die within 30 days of AMI (Table 1). The multiple logistic regression results indicates PAC/LTC patients had similar ORs for mortality compared to community patients when aspirin was given to eligible patients and when reperfusion was given to ideally eligible patients (Tables 4 and 5). Based on the logistic regression results, we calculated that the adjusted probability of 30‐day mortality among eligible PAC/LTC patients who received aspirin was 0.14 compared to 0.32 for those who did not, which is a difference in probability of 0.18. For eligible community admissions, the adjusted probability of mortality with aspirin was 0.09 with aspirin treatment compared to 0.26 without. For reperfusion, the adjusted probability of 30‐day mortality for ideally eligible PAC/LTC admissions falls from 0.27 to 0.15 if treatment is given, representing a difference in probability of 0.12. Similarly, the adjusted probability difference for community admissions who were ideally eligible and received reperfusion was approximately 0.08 (P = 0.16 without treatment and P = 0.08 with treatment).

Discussion

This investigation has important implications. The results suggest systematic differences in care for PAC/LTC compared to community‐based patients hospitalized with AMI. It is possible that short‐term mortality was impacted by guideline adherence differences according to admission source. The analytic methods accounted for clinical eligibility, tested for residual confounding and used econometric methods (SUR bivariate probit) to correct it where found, and excluded patients who refused treatments. Therefore, poor eligibility and treatment refusal are inadequate explanations for the observed differences in treatment according to admission source from a PAC/LTC facility.

Providers may not to follow AMI treatment guidelines because the perceived risks for patients transferred from PAC/LTC were too great or due to a limited clinical evidence base. Even though PAC/LTC patients were not included in clinical trials for AMI care, studies that carefully use observational data may help guide applicability of clinical recommendations for acute care to subgroups of clinically complex patients. This study offers observational evidence and information to guide additional studies regarding of the clinical benefit of treating a particularly vulnerable subgroup of patients.

Other research has noted that adherence to clinical practice guidelines in PAC/LTC facilities is low.36, 37 LTC practitioners have been reluctant to apply clinical practice guidelines to residents with chronic illnesses because these regimens often do not take into consideration individuals with the multiple chronic diseases prevalent among PAC/LTC patients9 and the complexity of the PAC/LTC environment.38, 39 Rather than dismiss the utility of clinical practice guidelines in the PAC/LTC population, this study is one of the first to demonstrate that use of acute care clinical practice guidelines, particularly aspirin, was associated with improved acute care outcomes among PAC/LTC patients transferred to acute care hospitals with AMI. Thus, guidelines for acute inpatient care may be more readily applied to the PAC/LTC population than studies aimed at treating chronic illnesses.9, 38, 40 Our results indicate that reperfusion might not be indicated for the preponderance of PAC/LTC patients, but many would agree that treatments such as aspirin would be a low‐burden intervention for most PAC/LTC patients. This investigation supports considering AMI treatment guidelines even for frail subpopulations such as those transferred from PAC/LTC. Further, the findings suggest there may be important information obtained by including PAC/LTC patients in future clinical trials.

This study has several limitations. First, the data were collected during 1995, and may not adequately reflect the current state of the art for AMI treatment or other changes in the organization, financing, and delivery of care for AMI. Nevertheless, care guidelines for AMI have not changed in ways that we anticipate altering the patterns of care examined in this study. For example, in the 2004 National Healthcare Disparities Report,41 receipt of aspirin among elderly individuals ranged from 79.6% to 86%, which closely resembles our results. Despite overall care improvements from 1990 to 2006, women, minorities, and patients ages 75 years and older remain significantly less likely to receive revascularization or discharge lipid‐lowering therapy relative to their counterparts indicating that differences in care persist today.42 While the data used in these analyses existed before recommendations included specific guidance regarding the care of older adults, other researchers examined data collected from January 1, 2005 to June 30, 2006 and demonstrated that elderly individuals remained less likely to receive indicated therapies.43 Further, this is the only dataset we identified that included an adequate presence of both PAC/LTC and community admission sources and sufficient data to assess guideline adherence and other covariates for our models. Second, The SUR bivariate probit models that account for correlation of error terms in models predicting both admission source and treatment were included to minimize issues related to residual confounding, but may not completely eliminate all systematic variation related to the underlying health status of community vs. PAC/LTC residents. Third, limitation of aggressive treatments was not recorded as to specific type of directives but research has shown that orders to forego treatments other than CPR are written for fewer than 8 % of nursing home residents.44, 45 Furthermore, all of these patients were transferred to a hospital; these transfers almost certainly occurred with an expectation that acute treatment would be offered. Fourth, we were unable to distinguish PAC vs. LTC based on admission source categories provided in the original data source. Finally, PTCA and thrombolysis were considered as a single variable because separating the 2 procedures would result in inadequate sample size to detect statistical differences between the 2 groups.

Conclusions

Patients admitted from PAC/LTC settings were less likely to receive early guideline‐recommended treatment for AMI compared to community‐dwelling patients. Our study finds evidence that following the aspirin guideline may improve survival for most patients, but that reperfusion improved survival only for a clinically‐select subgroup of patients. As such, a possible recommendation for further clinical study is that low‐burden treatments such as aspirin should be offered to most patients with AMI, including those from PAC/LTC. Higher‐burden treatments with have greater associated risks, such as reperfusion, also require more study to inform situations applicable to PAC/LTC patients. Clinical trials data would be indicated to strengthen evidence regarding which AMI treatment guidelines should be followed in frail populations from PAC/LTC settings; we identified no randomized trials that specifically demonstrate efficacy of AMI guidelines for this subgroup of vulnerable patients.

The American College of Cardiology (ACC) and the American Heart Association (AHA) recommend early intervention for older persons with acute coronary syndrome (ACS) to improve prognosis. However, numerous studies demonstrate that elderly patients with acute myocardial infarction (AMI) are less likely than their younger counterparts to receive guideline‐recommended therapies.13 No prior studies specifically demonstrate that adherence to AMI guidelines is effective in patients admitted from post‐acute or long‐term care (PAC/LTC) settings such as nursing homes, intermediate care facilities, and LTC hospitals. Recognizing that the barriers to guideline‐adherent care among the elderly may also be present for clinically‐complex PAC/LTC patients, we examined whether hospitalized patients with AMI admitted from PAC/LTC settings were less likely to receive guideline‐recommended therapies and if guideline‐concordant treatment was associated with short‐term (30‐day) survival in this relatively vulnerable subgroup of patients.

Medical decision making, including applicability of guidelines, is not exclusively based on empirical evidence but is also related to morally complex issues such as patient age, social status, and other unknown factors. However, lack of outcome expectancy may limit adherence for AMI care in PAC/LTC populations.4 In particular, treating physicians may not expect that desired outcomes will result when guidelines are followed in the PAC/LTC group compared to community‐based patients. This notion is supported by other research indicating that physicians caring for nursing home residents' chronic health conditions often tailor the care approach according to the patients' functional and cognitive status rather than adhering to recommended guidelines.5 In a study that used hypothetical scenarios, nursing home patients with a better physical condition, a more obvious social role, and a lower age were more likely to be treated with life‐sustaining treatments than were other patients.6 For AMI care, some physicians provide care that is not guideline‐adherent due to concerns that reduced renal function is an absolute rather than relative contraindication to angiography.7, 8 And, because the clinical trials that informed practice guidelines for AMI care did not explicitly include individuals with the chronic complex medical problems prevalent among the PAC/LTC population, treating clinicians may be reluctant to apply acute care guidelines to this subgroup.9 However, we know of no prior research demonstrating that guideline‐adherent care for either chronic or acute conditions results in differential outcomes for PAC/LTC patients cared for in the hospital setting.

For the present study, we examined whether admission source was an independent predictor of AMI treatment and whether guideline‐concordant care was related to mortality for those admitted from PAC/LTC and community settings. We hypothesized that rates of guideline‐concordant care would be higher for patients admitted from community settings vs. PAC/LTC and that differences between the groups would be greater for more intensive interventions such as reperfusion compared to aspirin. The data included detailed clinical eligibility information for treatments based on contemporary ACC/AHA guidelines,10 along with numerous other patient demographic and clinical characteristics, thus allowing us to address the presumptive concern that PAC/LTC patients were sicker or otherwise less‐suited for treatment than other patients.

Methods

This retrospective cohort study relied on existing observational data. The primary data source for this research was the Cooperative Cardiovascular Project (CCP) national baseline data. The CCP was sponsored by the Centers for Medicare & Medicaid Services (CMS) to measure the quality of care provided to a national cohort of Medicare patients hospitalized with AMI. The national data collection and reporting effort was administered through the 53 Medicare Quality Improvement Organization (QIO) contracts established to serve each State, the District of Columbia, Puerto Rico, and the U.S. Virgin Islands. Hospital medical records were requested under QIO authority and then abstracted by centrally‐contracted Clinical Data Abstraction Centers (CDACs). Data quality monitoring involved random reabstraction of records with double entry of the information to ensure consistency across personnel, and data were found to be very reliable. Detailed data collection procedures and main findings from these data have been reported elsewhere.1126

The CCP baseline data included an initial sample of 234,754 records abstracted from inpatient medical charts for fee‐for‐services Medicare beneficiaries hospitalized in 1 of 6684 hospitals located in any of the 50 states, the District of Columbia, Puerto Rico, the U.S. Virgin Islands, American Samoa, Guam, and the Northern Mariana Islands between February 1994 and July 1995. Although the data analyzed for this research relate to hospitalizations for AMI in 1994‐1995, the 2008 ACC/AHA report regarding AMI performance measures retains recommendations for both early aspirin and reperfusion treatments.27 Even though the data are not derived from recent years, the CCP baseline data represent a unique dataset to address questions related to both clinical eligibility and guideline compliance for both community and PAC/LTC patients. The inclusion of PAC/LTC admissions and detailed information regarding clinical eligibility for treatment are particularly important to adequately address the research aim; the CCP baseline data are the single extant U.S. data source we identified that has both features.

AMI cases were identified through inpatient hospital claims using an International Classification of Diseases, 9th Revision, Clinical Modification (ICD‐9‐CM) principal discharge diagnosis of 410 (ACS) for extended chart review to verify AMI and determine clinical eligibility for treatments. CCP records were subsequently linked with the Medicare Denominator File, Area Resource File (ARF), and Medicare PPS cost reports for hospitals (PPS) to obtain additional information regarding patients, local health resources, and admitting hospital.

For the present study, we excluded cases without a confirmed AMI diagnosis; cases with missing geographic information to allow us to control for local practice variation including all cases from outside the Continental U.S.; cases admitted to nonacute facilities or with inadequate information to link with provider data; and cases that originated in states selected for the CCP pilot study due to differences in record abstraction timing and some of the measures. Clinical eligibility for treatments relied on the standardized criteria established by the CCP advisory panel and used in other research.10, 14, 2831

To test whether admission from a LTC setting was negatively associated with guideline adherence and if the relationship varied according to the intensity of the treatment, we examined 2 guidelines related to early interventions care during the hospital stay: (1) administration of aspirin; and (2) reperfusion through either thrombolytic drugs or percutaneous intervention (PTCA). We chose these measures because they range from a simple and readily‐available medical intervention (aspirin), to a clinically complex and costly intervention for a more clinically‐select group of patients (reperfusion). The hypothesis that more intensive acute treatment would be less likely for patients admitted from PAC/LTC settings was empirically tested by examining the differences in overall probabilities and adjusted probabilities of receiving each of these interventions. We then modeled the odds ratios (ORs) for survival based on receiving these treatments.

Guideline adherence and clinical eligibility indicators for the CCP data have been presented elsewhere.10, 20, 23, 29, 32 Using these criteria, we divided patients into clinical eligibility groups, including ideal candidates, eligible candidates, and candidates for whom the care was not indicated. For the present research, all eligible patients were included in the sample; with ideal eligibility included as a covariate in the regression models. All patients in the study sample were at least minimally eligible to receive aspirin during their hospital stay. Ideal candidates for aspirin did not have: a gastrointestinal (GI) ulcer, same day admission/discharge, history of bleeding disorder, risk of bleeding, anemia, allergy to aspirin, warfarin, or terminal illness. Eligible candidates for reperfusion via PTCA or thrombolysis were not transferred from another hospital or emergency department. Ideal eligibility for reperfusion required, in addition, that the patient: was under age 80 years; arrived at the hospital within 6 hours of symptom onset; showed evidence of a transmural (Q‐wave) MI or ST elevation in 2 contiguous leads on arrival electrocardiogram (ECG); was not taking warfarin; did not have cardiac arrest requiring cardiopulmonary resuscitation (CPR), cardioversion, defibrillation, or chemical cardioversion in the 6 hours prior; did not refuse a thrombolytic; did not have cardiac catheterization without PTCA within 12 hours of arrival; had no evidence of hepatic failure or cirrhosis; had no history of active ulcer disease, internal bleeding, trauma, or injury in the month prior to arrival; and had no bleeding risk, cerebral vascular accident, or surgery/biopsy within 2 months of admission.

Prearrival setting was of particular interest for the present study; this information was derived from the patient's medical chart using a standardized chart abstraction process for the CCP. From the original admission source categories, we created a single dichotomous variable that indicated PAC/LTC vs. community setting prior to arrival. We defined PAC/LTC settings to include patients admitted from either a skilled nursing facility (SNF) or intermediate care facility (ICF), chronic hospital, or other residential care facility. Three categories of admission source were used to identify the comparison sample: home, noninstitutional setting, and outpatient setting.

Because differences in care according to admission source could result from observable causes, multiple regression analysis was incorporated to control for observed factors previously shown to be associated with guideline adherence. These included: ideal eligibility for treatment; age; Caucasian (vs. other) ethnicity; gender; limitation of aggressive treatment orders (eg, do not resuscitate, do not intubate, chemical code only, no cardiac monitoring, no invasive procedures, no vasopressor, no antiarrhythmic therapy, no feeding tube, palliative care measures only); Charlson comorbidity index and Acute Physiology, Age, Chronic Health Evaluation assessment (3rd revision) (APACHE III) score, body mass index (BMI), rural hospital location, hospital teaching status, and number of full‐time equivalent cardiologists on staff at the treating hospital. The regression methods also included adjustment for clustering of patients within health services area to account for geographic variation in practice patterns.33

In developing the regression model, we predicted whether the patient received care in accord with guidelines and 30‐day mortality. We also tested whether the regression errors terms (unobserved variables) for these equations were significantly related to error terms in a regression to predict source of admission, which would indicate rejecting the hypothesis that admission source and treatments were determined independently of each other. In particular, admission source may be a proxy for underlying health status (severity of illness), care preferences, or other unobserved factors that differ systematically between patients admitted from the community vs. those admitted from PAC/LTC. In testing the models, we found that the error terms for both treatments (aspirin and reperfusion) and admission source models were significantly negatively correlated (rho or chi‐square P value <0.001), indicating the need to adjust regression estimates to account for unobserved variables related to both admission source and guideline concordant treatment. Because we rejected the hypothesis that admission source was exogenous to treatments, a seemingly‐unrelated regressions (SUR) bivariate probit model was deemed appropriate, as this methodology corrects for correlation between unobserved variables that are related to both admission source and treatment decisions (eg, residual confounding).34 And, since coefficients from SUR bivariate probit models are not directly interpretable as either ORs or relative risks with respect to the outcome variables, we converted the coefficients to reflect marginal probabilities. The correlation in error terms for models predicting 30‐day mortality and admission source was not substantively or statistically significant. As such, we utilized standard logistic regression methods for assessing mortality. Mortality models were predicted separately according to admission source and treatment to allow presentation of ORs associated with each treatment for each group.

Analyses used the Stata statistical package (version 10.1 SE).35 Approval for this use of the CCP data was received from the CMS. Approval for the data analysis protocol was received from the authors' institutional review board.

Results

Of the 128,183 patients in the analytic sample, 7.6% (n = 8151) were admitted from PAC/LTC (Table 1). The members of the PAC/LTC cohort were older on average than the community‐dwelling cohort (83 vs. 76 years, P < 0.001) and more likely to be female (69% vs. 48%, P < 0.001). Limitation of aggressive treatment orders (LAT/DNR) were in place for 55% of the PAC/LTC cohort compared to only 16% of the community‐dwelling cohort (P < 0.001). Severity of illness scores were higher among the PAC/LTC cohort with APACHE III scores of 50.8 in the PAC/LTC cohort vs. 36.8 in the community‐dwelling cohort (P < 0.001). The PAC/LTC cohort also had lower BMI (P < 0.001). Mortality at 30 days and 1 year was 39.5% and 65.4%, respectively, in the PAC/LTC cohort vs. 17.6% and 33.4%, respectively, in the community‐dwelling cohort. These differences across groups were significant at both time points (P < 0.001). PAC/LTC admissions were significantly more likely to be admitted to a hospital located in a rural area (P < 0.001), though the numbers of full‐time equivalent residents and presence of cardiologists in the treating hospitals were similar across groups.

Table 2 provides overall unadjusted data comparing eligibility and treatment information for PAC/LTC and community admissions. Rates of guideline adherence were uniformly higher for patients admitted from the community. Guideline adherence rates were higher for aspirin compared to reperfusion, and followed the predicted pattern that more resource‐intensive treatments would be less common for both groups and that PAC/LTC admissions would be less likely to receive treatments compared to patients admitted from community settings. Though all 8151 PAC/LTC patients were eligible to receive aspirin, only 4370 were ideally eligible and 3015 (69%) received acetylsalicylic acid (ASA). There were 1418 PAC/LTC patients (17% of the PAC/LTC sample) meeting at least minimal eligibility requirements for reperfusion. Among the 214 PAC/LTC cases that were ideally eligible for reperfusion, 65 (30%) received the treatment; 12 patients received PTCA and 53 received thrombolytic agents. Eligibility and treatment rates for reperfusion were substantially higher for the community sample, with almost 27% meeting minimum eligibility requirements and 60% of the ideally‐eligible group receiving the treatment.

Table 3 presents the adjusted probability of treatment based upon the SUR bivariate probit regression model. As with the unadjusted results presented in Table 2, PAC/LTC patients had a lower probability of treatment even after controlling for important patient and hospital characteristics. Compared to the unadjusted results, the adjusted probabilities calculated with the SUR bivariate probit model indicated a relatively higher predicted probability of treatment for the PAC/LTC patients and a relatively lower predicted probability of treatment among the community patients. In other words, the probability of treatment becomes more similar across groups once the adjustments for both observed and unobserved differences in patient characteristics are considered. Nonetheless, a difference in probability of treatment remains across the 2 groups.

To determine whether there was survival difference associated with treatment in these data, we conducted a logistic regression analyses to predict 30‐day mortality for both groups (Tables 4 and 5). Table 4 presents results (ORs) of our models emphasizing the relationship between aspirin and 30‐day mortality, while Table 5 presents the models with reperfusion. Model discrimination was tested using a C‐statistic and was at least 0.70 for all models, indicating good predictive validity. However, for the reperfusion models (Table 5) there were relatively few PAC/LTC patients ideally eligible for treatment, which limited statistical power. There was an association between aspirin provision and improved survival for both the PAC/LTC and community admissions (95% confidence intervals [CIs] were less than 1.0) for all eligible patients. For the eligible samples, we did not find the anticipated relationship between reperfusion and 30‐day survival. The ORs and CIs for community admissions were significantly greater than 1.0. However, we noted lower ORs of mortality for the subgroups of ideally eligible patients, with 95% CIs under 1.0 for both PAC/LTC and community admissions, indicating better survival among those who were ideally eligible for reperfusion treatment. The unadjusted data indicated that PAC/LTC patients were much more likely than their community counterparts to die within 30 days of AMI (Table 1). The multiple logistic regression results indicates PAC/LTC patients had similar ORs for mortality compared to community patients when aspirin was given to eligible patients and when reperfusion was given to ideally eligible patients (Tables 4 and 5). Based on the logistic regression results, we calculated that the adjusted probability of 30‐day mortality among eligible PAC/LTC patients who received aspirin was 0.14 compared to 0.32 for those who did not, which is a difference in probability of 0.18. For eligible community admissions, the adjusted probability of mortality with aspirin was 0.09 with aspirin treatment compared to 0.26 without. For reperfusion, the adjusted probability of 30‐day mortality for ideally eligible PAC/LTC admissions falls from 0.27 to 0.15 if treatment is given, representing a difference in probability of 0.12. Similarly, the adjusted probability difference for community admissions who were ideally eligible and received reperfusion was approximately 0.08 (P = 0.16 without treatment and P = 0.08 with treatment).

Discussion

This investigation has important implications. The results suggest systematic differences in care for PAC/LTC compared to community‐based patients hospitalized with AMI. It is possible that short‐term mortality was impacted by guideline adherence differences according to admission source. The analytic methods accounted for clinical eligibility, tested for residual confounding and used econometric methods (SUR bivariate probit) to correct it where found, and excluded patients who refused treatments. Therefore, poor eligibility and treatment refusal are inadequate explanations for the observed differences in treatment according to admission source from a PAC/LTC facility.

Providers may not to follow AMI treatment guidelines because the perceived risks for patients transferred from PAC/LTC were too great or due to a limited clinical evidence base. Even though PAC/LTC patients were not included in clinical trials for AMI care, studies that carefully use observational data may help guide applicability of clinical recommendations for acute care to subgroups of clinically complex patients. This study offers observational evidence and information to guide additional studies regarding of the clinical benefit of treating a particularly vulnerable subgroup of patients.

Other research has noted that adherence to clinical practice guidelines in PAC/LTC facilities is low.36, 37 LTC practitioners have been reluctant to apply clinical practice guidelines to residents with chronic illnesses because these regimens often do not take into consideration individuals with the multiple chronic diseases prevalent among PAC/LTC patients9 and the complexity of the PAC/LTC environment.38, 39 Rather than dismiss the utility of clinical practice guidelines in the PAC/LTC population, this study is one of the first to demonstrate that use of acute care clinical practice guidelines, particularly aspirin, was associated with improved acute care outcomes among PAC/LTC patients transferred to acute care hospitals with AMI. Thus, guidelines for acute inpatient care may be more readily applied to the PAC/LTC population than studies aimed at treating chronic illnesses.9, 38, 40 Our results indicate that reperfusion might not be indicated for the preponderance of PAC/LTC patients, but many would agree that treatments such as aspirin would be a low‐burden intervention for most PAC/LTC patients. This investigation supports considering AMI treatment guidelines even for frail subpopulations such as those transferred from PAC/LTC. Further, the findings suggest there may be important information obtained by including PAC/LTC patients in future clinical trials.

This study has several limitations. First, the data were collected during 1995, and may not adequately reflect the current state of the art for AMI treatment or other changes in the organization, financing, and delivery of care for AMI. Nevertheless, care guidelines for AMI have not changed in ways that we anticipate altering the patterns of care examined in this study. For example, in the 2004 National Healthcare Disparities Report,41 receipt of aspirin among elderly individuals ranged from 79.6% to 86%, which closely resembles our results. Despite overall care improvements from 1990 to 2006, women, minorities, and patients ages 75 years and older remain significantly less likely to receive revascularization or discharge lipid‐lowering therapy relative to their counterparts indicating that differences in care persist today.42 While the data used in these analyses existed before recommendations included specific guidance regarding the care of older adults, other researchers examined data collected from January 1, 2005 to June 30, 2006 and demonstrated that elderly individuals remained less likely to receive indicated therapies.43 Further, this is the only dataset we identified that included an adequate presence of both PAC/LTC and community admission sources and sufficient data to assess guideline adherence and other covariates for our models. Second, The SUR bivariate probit models that account for correlation of error terms in models predicting both admission source and treatment were included to minimize issues related to residual confounding, but may not completely eliminate all systematic variation related to the underlying health status of community vs. PAC/LTC residents. Third, limitation of aggressive treatments was not recorded as to specific type of directives but research has shown that orders to forego treatments other than CPR are written for fewer than 8 % of nursing home residents.44, 45 Furthermore, all of these patients were transferred to a hospital; these transfers almost certainly occurred with an expectation that acute treatment would be offered. Fourth, we were unable to distinguish PAC vs. LTC based on admission source categories provided in the original data source. Finally, PTCA and thrombolysis were considered as a single variable because separating the 2 procedures would result in inadequate sample size to detect statistical differences between the 2 groups.

Conclusions

Patients admitted from PAC/LTC settings were less likely to receive early guideline‐recommended treatment for AMI compared to community‐dwelling patients. Our study finds evidence that following the aspirin guideline may improve survival for most patients, but that reperfusion improved survival only for a clinically‐select subgroup of patients. As such, a possible recommendation for further clinical study is that low‐burden treatments such as aspirin should be offered to most patients with AMI, including those from PAC/LTC. Higher‐burden treatments with have greater associated risks, such as reperfusion, also require more study to inform situations applicable to PAC/LTC patients. Clinical trials data would be indicated to strengthen evidence regarding which AMI treatment guidelines should be followed in frail populations from PAC/LTC settings; we identified no randomized trials that specifically demonstrate efficacy of AMI guidelines for this subgroup of vulnerable patients.

The American College of Cardiology (ACC) and the American Heart Association (AHA) recommend early intervention for older persons with acute coronary syndrome (ACS) to improve prognosis. However, numerous studies demonstrate that elderly patients with acute myocardial infarction (AMI) are less likely than their younger counterparts to receive guideline‐recommended therapies.13 No prior studies specifically demonstrate that adherence to AMI guidelines is effective in patients admitted from post‐acute or long‐term care (PAC/LTC) settings such as nursing homes, intermediate care facilities, and LTC hospitals. Recognizing that the barriers to guideline‐adherent care among the elderly may also be present for clinically‐complex PAC/LTC patients, we examined whether hospitalized patients with AMI admitted from PAC/LTC settings were less likely to receive guideline‐recommended therapies and if guideline‐concordant treatment was associated with short‐term (30‐day) survival in this relatively vulnerable subgroup of patients.

Medical decision making, including applicability of guidelines, is not exclusively based on empirical evidence but is also related to morally complex issues such as patient age, social status, and other unknown factors. However, lack of outcome expectancy may limit adherence for AMI care in PAC/LTC populations.4 In particular, treating physicians may not expect that desired outcomes will result when guidelines are followed in the PAC/LTC group compared to community‐based patients. This notion is supported by other research indicating that physicians caring for nursing home residents' chronic health conditions often tailor the care approach according to the patients' functional and cognitive status rather than adhering to recommended guidelines.5 In a study that used hypothetical scenarios, nursing home patients with a better physical condition, a more obvious social role, and a lower age were more likely to be treated with life‐sustaining treatments than were other patients.6 For AMI care, some physicians provide care that is not guideline‐adherent due to concerns that reduced renal function is an absolute rather than relative contraindication to angiography.7, 8 And, because the clinical trials that informed practice guidelines for AMI care did not explicitly include individuals with the chronic complex medical problems prevalent among the PAC/LTC population, treating clinicians may be reluctant to apply acute care guidelines to this subgroup.9 However, we know of no prior research demonstrating that guideline‐adherent care for either chronic or acute conditions results in differential outcomes for PAC/LTC patients cared for in the hospital setting.

For the present study, we examined whether admission source was an independent predictor of AMI treatment and whether guideline‐concordant care was related to mortality for those admitted from PAC/LTC and community settings. We hypothesized that rates of guideline‐concordant care would be higher for patients admitted from community settings vs. PAC/LTC and that differences between the groups would be greater for more intensive interventions such as reperfusion compared to aspirin. The data included detailed clinical eligibility information for treatments based on contemporary ACC/AHA guidelines,10 along with numerous other patient demographic and clinical characteristics, thus allowing us to address the presumptive concern that PAC/LTC patients were sicker or otherwise less‐suited for treatment than other patients.

Methods

This retrospective cohort study relied on existing observational data. The primary data source for this research was the Cooperative Cardiovascular Project (CCP) national baseline data. The CCP was sponsored by the Centers for Medicare & Medicaid Services (CMS) to measure the quality of care provided to a national cohort of Medicare patients hospitalized with AMI. The national data collection and reporting effort was administered through the 53 Medicare Quality Improvement Organization (QIO) contracts established to serve each State, the District of Columbia, Puerto Rico, and the U.S. Virgin Islands. Hospital medical records were requested under QIO authority and then abstracted by centrally‐contracted Clinical Data Abstraction Centers (CDACs). Data quality monitoring involved random reabstraction of records with double entry of the information to ensure consistency across personnel, and data were found to be very reliable. Detailed data collection procedures and main findings from these data have been reported elsewhere.1126

The CCP baseline data included an initial sample of 234,754 records abstracted from inpatient medical charts for fee‐for‐services Medicare beneficiaries hospitalized in 1 of 6684 hospitals located in any of the 50 states, the District of Columbia, Puerto Rico, the U.S. Virgin Islands, American Samoa, Guam, and the Northern Mariana Islands between February 1994 and July 1995. Although the data analyzed for this research relate to hospitalizations for AMI in 1994‐1995, the 2008 ACC/AHA report regarding AMI performance measures retains recommendations for both early aspirin and reperfusion treatments.27 Even though the data are not derived from recent years, the CCP baseline data represent a unique dataset to address questions related to both clinical eligibility and guideline compliance for both community and PAC/LTC patients. The inclusion of PAC/LTC admissions and detailed information regarding clinical eligibility for treatment are particularly important to adequately address the research aim; the CCP baseline data are the single extant U.S. data source we identified that has both features.

AMI cases were identified through inpatient hospital claims using an International Classification of Diseases, 9th Revision, Clinical Modification (ICD‐9‐CM) principal discharge diagnosis of 410 (ACS) for extended chart review to verify AMI and determine clinical eligibility for treatments. CCP records were subsequently linked with the Medicare Denominator File, Area Resource File (ARF), and Medicare PPS cost reports for hospitals (PPS) to obtain additional information regarding patients, local health resources, and admitting hospital.

For the present study, we excluded cases without a confirmed AMI diagnosis; cases with missing geographic information to allow us to control for local practice variation including all cases from outside the Continental U.S.; cases admitted to nonacute facilities or with inadequate information to link with provider data; and cases that originated in states selected for the CCP pilot study due to differences in record abstraction timing and some of the measures. Clinical eligibility for treatments relied on the standardized criteria established by the CCP advisory panel and used in other research.10, 14, 2831

To test whether admission from a LTC setting was negatively associated with guideline adherence and if the relationship varied according to the intensity of the treatment, we examined 2 guidelines related to early interventions care during the hospital stay: (1) administration of aspirin; and (2) reperfusion through either thrombolytic drugs or percutaneous intervention (PTCA). We chose these measures because they range from a simple and readily‐available medical intervention (aspirin), to a clinically complex and costly intervention for a more clinically‐select group of patients (reperfusion). The hypothesis that more intensive acute treatment would be less likely for patients admitted from PAC/LTC settings was empirically tested by examining the differences in overall probabilities and adjusted probabilities of receiving each of these interventions. We then modeled the odds ratios (ORs) for survival based on receiving these treatments.

Guideline adherence and clinical eligibility indicators for the CCP data have been presented elsewhere.10, 20, 23, 29, 32 Using these criteria, we divided patients into clinical eligibility groups, including ideal candidates, eligible candidates, and candidates for whom the care was not indicated. For the present research, all eligible patients were included in the sample; with ideal eligibility included as a covariate in the regression models. All patients in the study sample were at least minimally eligible to receive aspirin during their hospital stay. Ideal candidates for aspirin did not have: a gastrointestinal (GI) ulcer, same day admission/discharge, history of bleeding disorder, risk of bleeding, anemia, allergy to aspirin, warfarin, or terminal illness. Eligible candidates for reperfusion via PTCA or thrombolysis were not transferred from another hospital or emergency department. Ideal eligibility for reperfusion required, in addition, that the patient: was under age 80 years; arrived at the hospital within 6 hours of symptom onset; showed evidence of a transmural (Q‐wave) MI or ST elevation in 2 contiguous leads on arrival electrocardiogram (ECG); was not taking warfarin; did not have cardiac arrest requiring cardiopulmonary resuscitation (CPR), cardioversion, defibrillation, or chemical cardioversion in the 6 hours prior; did not refuse a thrombolytic; did not have cardiac catheterization without PTCA within 12 hours of arrival; had no evidence of hepatic failure or cirrhosis; had no history of active ulcer disease, internal bleeding, trauma, or injury in the month prior to arrival; and had no bleeding risk, cerebral vascular accident, or surgery/biopsy within 2 months of admission.

Prearrival setting was of particular interest for the present study; this information was derived from the patient's medical chart using a standardized chart abstraction process for the CCP. From the original admission source categories, we created a single dichotomous variable that indicated PAC/LTC vs. community setting prior to arrival. We defined PAC/LTC settings to include patients admitted from either a skilled nursing facility (SNF) or intermediate care facility (ICF), chronic hospital, or other residential care facility. Three categories of admission source were used to identify the comparison sample: home, noninstitutional setting, and outpatient setting.

Because differences in care according to admission source could result from observable causes, multiple regression analysis was incorporated to control for observed factors previously shown to be associated with guideline adherence. These included: ideal eligibility for treatment; age; Caucasian (vs. other) ethnicity; gender; limitation of aggressive treatment orders (eg, do not resuscitate, do not intubate, chemical code only, no cardiac monitoring, no invasive procedures, no vasopressor, no antiarrhythmic therapy, no feeding tube, palliative care measures only); Charlson comorbidity index and Acute Physiology, Age, Chronic Health Evaluation assessment (3rd revision) (APACHE III) score, body mass index (BMI), rural hospital location, hospital teaching status, and number of full‐time equivalent cardiologists on staff at the treating hospital. The regression methods also included adjustment for clustering of patients within health services area to account for geographic variation in practice patterns.33

In developing the regression model, we predicted whether the patient received care in accord with guidelines and 30‐day mortality. We also tested whether the regression errors terms (unobserved variables) for these equations were significantly related to error terms in a regression to predict source of admission, which would indicate rejecting the hypothesis that admission source and treatments were determined independently of each other. In particular, admission source may be a proxy for underlying health status (severity of illness), care preferences, or other unobserved factors that differ systematically between patients admitted from the community vs. those admitted from PAC/LTC. In testing the models, we found that the error terms for both treatments (aspirin and reperfusion) and admission source models were significantly negatively correlated (rho or chi‐square P value <0.001), indicating the need to adjust regression estimates to account for unobserved variables related to both admission source and guideline concordant treatment. Because we rejected the hypothesis that admission source was exogenous to treatments, a seemingly‐unrelated regressions (SUR) bivariate probit model was deemed appropriate, as this methodology corrects for correlation between unobserved variables that are related to both admission source and treatment decisions (eg, residual confounding).34 And, since coefficients from SUR bivariate probit models are not directly interpretable as either ORs or relative risks with respect to the outcome variables, we converted the coefficients to reflect marginal probabilities. The correlation in error terms for models predicting 30‐day mortality and admission source was not substantively or statistically significant. As such, we utilized standard logistic regression methods for assessing mortality. Mortality models were predicted separately according to admission source and treatment to allow presentation of ORs associated with each treatment for each group.

Analyses used the Stata statistical package (version 10.1 SE).35 Approval for this use of the CCP data was received from the CMS. Approval for the data analysis protocol was received from the authors' institutional review board.

Results

Of the 128,183 patients in the analytic sample, 7.6% (n = 8151) were admitted from PAC/LTC (Table 1). The members of the PAC/LTC cohort were older on average than the community‐dwelling cohort (83 vs. 76 years, P < 0.001) and more likely to be female (69% vs. 48%, P < 0.001). Limitation of aggressive treatment orders (LAT/DNR) were in place for 55% of the PAC/LTC cohort compared to only 16% of the community‐dwelling cohort (P < 0.001). Severity of illness scores were higher among the PAC/LTC cohort with APACHE III scores of 50.8 in the PAC/LTC cohort vs. 36.8 in the community‐dwelling cohort (P < 0.001). The PAC/LTC cohort also had lower BMI (P < 0.001). Mortality at 30 days and 1 year was 39.5% and 65.4%, respectively, in the PAC/LTC cohort vs. 17.6% and 33.4%, respectively, in the community‐dwelling cohort. These differences across groups were significant at both time points (P < 0.001). PAC/LTC admissions were significantly more likely to be admitted to a hospital located in a rural area (P < 0.001), though the numbers of full‐time equivalent residents and presence of cardiologists in the treating hospitals were similar across groups.

Table 2 provides overall unadjusted data comparing eligibility and treatment information for PAC/LTC and community admissions. Rates of guideline adherence were uniformly higher for patients admitted from the community. Guideline adherence rates were higher for aspirin compared to reperfusion, and followed the predicted pattern that more resource‐intensive treatments would be less common for both groups and that PAC/LTC admissions would be less likely to receive treatments compared to patients admitted from community settings. Though all 8151 PAC/LTC patients were eligible to receive aspirin, only 4370 were ideally eligible and 3015 (69%) received acetylsalicylic acid (ASA). There were 1418 PAC/LTC patients (17% of the PAC/LTC sample) meeting at least minimal eligibility requirements for reperfusion. Among the 214 PAC/LTC cases that were ideally eligible for reperfusion, 65 (30%) received the treatment; 12 patients received PTCA and 53 received thrombolytic agents. Eligibility and treatment rates for reperfusion were substantially higher for the community sample, with almost 27% meeting minimum eligibility requirements and 60% of the ideally‐eligible group receiving the treatment.

Table 3 presents the adjusted probability of treatment based upon the SUR bivariate probit regression model. As with the unadjusted results presented in Table 2, PAC/LTC patients had a lower probability of treatment even after controlling for important patient and hospital characteristics. Compared to the unadjusted results, the adjusted probabilities calculated with the SUR bivariate probit model indicated a relatively higher predicted probability of treatment for the PAC/LTC patients and a relatively lower predicted probability of treatment among the community patients. In other words, the probability of treatment becomes more similar across groups once the adjustments for both observed and unobserved differences in patient characteristics are considered. Nonetheless, a difference in probability of treatment remains across the 2 groups.

To determine whether there was survival difference associated with treatment in these data, we conducted a logistic regression analyses to predict 30‐day mortality for both groups (Tables 4 and 5). Table 4 presents results (ORs) of our models emphasizing the relationship between aspirin and 30‐day mortality, while Table 5 presents the models with reperfusion. Model discrimination was tested using a C‐statistic and was at least 0.70 for all models, indicating good predictive validity. However, for the reperfusion models (Table 5) there were relatively few PAC/LTC patients ideally eligible for treatment, which limited statistical power. There was an association between aspirin provision and improved survival for both the PAC/LTC and community admissions (95% confidence intervals [CIs] were less than 1.0) for all eligible patients. For the eligible samples, we did not find the anticipated relationship between reperfusion and 30‐day survival. The ORs and CIs for community admissions were significantly greater than 1.0. However, we noted lower ORs of mortality for the subgroups of ideally eligible patients, with 95% CIs under 1.0 for both PAC/LTC and community admissions, indicating better survival among those who were ideally eligible for reperfusion treatment. The unadjusted data indicated that PAC/LTC patients were much more likely than their community counterparts to die within 30 days of AMI (Table 1). The multiple logistic regression results indicates PAC/LTC patients had similar ORs for mortality compared to community patients when aspirin was given to eligible patients and when reperfusion was given to ideally eligible patients (Tables 4 and 5). Based on the logistic regression results, we calculated that the adjusted probability of 30‐day mortality among eligible PAC/LTC patients who received aspirin was 0.14 compared to 0.32 for those who did not, which is a difference in probability of 0.18. For eligible community admissions, the adjusted probability of mortality with aspirin was 0.09 with aspirin treatment compared to 0.26 without. For reperfusion, the adjusted probability of 30‐day mortality for ideally eligible PAC/LTC admissions falls from 0.27 to 0.15 if treatment is given, representing a difference in probability of 0.12. Similarly, the adjusted probability difference for community admissions who were ideally eligible and received reperfusion was approximately 0.08 (P = 0.16 without treatment and P = 0.08 with treatment).

Discussion

This investigation has important implications. The results suggest systematic differences in care for PAC/LTC compared to community‐based patients hospitalized with AMI. It is possible that short‐term mortality was impacted by guideline adherence differences according to admission source. The analytic methods accounted for clinical eligibility, tested for residual confounding and used econometric methods (SUR bivariate probit) to correct it where found, and excluded patients who refused treatments. Therefore, poor eligibility and treatment refusal are inadequate explanations for the observed differences in treatment according to admission source from a PAC/LTC facility.

Providers may not to follow AMI treatment guidelines because the perceived risks for patients transferred from PAC/LTC were too great or due to a limited clinical evidence base. Even though PAC/LTC patients were not included in clinical trials for AMI care, studies that carefully use observational data may help guide applicability of clinical recommendations for acute care to subgroups of clinically complex patients. This study offers observational evidence and information to guide additional studies regarding of the clinical benefit of treating a particularly vulnerable subgroup of patients.

Other research has noted that adherence to clinical practice guidelines in PAC/LTC facilities is low.36, 37 LTC practitioners have been reluctant to apply clinical practice guidelines to residents with chronic illnesses because these regimens often do not take into consideration individuals with the multiple chronic diseases prevalent among PAC/LTC patients9 and the complexity of the PAC/LTC environment.38, 39 Rather than dismiss the utility of clinical practice guidelines in the PAC/LTC population, this study is one of the first to demonstrate that use of acute care clinical practice guidelines, particularly aspirin, was associated with improved acute care outcomes among PAC/LTC patients transferred to acute care hospitals with AMI. Thus, guidelines for acute inpatient care may be more readily applied to the PAC/LTC population than studies aimed at treating chronic illnesses.9, 38, 40 Our results indicate that reperfusion might not be indicated for the preponderance of PAC/LTC patients, but many would agree that treatments such as aspirin would be a low‐burden intervention for most PAC/LTC patients. This investigation supports considering AMI treatment guidelines even for frail subpopulations such as those transferred from PAC/LTC. Further, the findings suggest there may be important information obtained by including PAC/LTC patients in future clinical trials.

This study has several limitations. First, the data were collected during 1995, and may not adequately reflect the current state of the art for AMI treatment or other changes in the organization, financing, and delivery of care for AMI. Nevertheless, care guidelines for AMI have not changed in ways that we anticipate altering the patterns of care examined in this study. For example, in the 2004 National Healthcare Disparities Report,41 receipt of aspirin among elderly individuals ranged from 79.6% to 86%, which closely resembles our results. Despite overall care improvements from 1990 to 2006, women, minorities, and patients ages 75 years and older remain significantly less likely to receive revascularization or discharge lipid‐lowering therapy relative to their counterparts indicating that differences in care persist today.42 While the data used in these analyses existed before recommendations included specific guidance regarding the care of older adults, other researchers examined data collected from January 1, 2005 to June 30, 2006 and demonstrated that elderly individuals remained less likely to receive indicated therapies.43 Further, this is the only dataset we identified that included an adequate presence of both PAC/LTC and community admission sources and sufficient data to assess guideline adherence and other covariates for our models. Second, The SUR bivariate probit models that account for correlation of error terms in models predicting both admission source and treatment were included to minimize issues related to residual confounding, but may not completely eliminate all systematic variation related to the underlying health status of community vs. PAC/LTC residents. Third, limitation of aggressive treatments was not recorded as to specific type of directives but research has shown that orders to forego treatments other than CPR are written for fewer than 8 % of nursing home residents.44, 45 Furthermore, all of these patients were transferred to a hospital; these transfers almost certainly occurred with an expectation that acute treatment would be offered. Fourth, we were unable to distinguish PAC vs. LTC based on admission source categories provided in the original data source. Finally, PTCA and thrombolysis were considered as a single variable because separating the 2 procedures would result in inadequate sample size to detect statistical differences between the 2 groups.

Conclusions

Patients admitted from PAC/LTC settings were less likely to receive early guideline‐recommended treatment for AMI compared to community‐dwelling patients. Our study finds evidence that following the aspirin guideline may improve survival for most patients, but that reperfusion improved survival only for a clinically‐select subgroup of patients. As such, a possible recommendation for further clinical study is that low‐burden treatments such as aspirin should be offered to most patients with AMI, including those from PAC/LTC. Higher‐burden treatments with have greater associated risks, such as reperfusion, also require more study to inform situations applicable to PAC/LTC patients. Clinical trials data would be indicated to strengthen evidence regarding which AMI treatment guidelines should be followed in frail populations from PAC/LTC settings; we identified no randomized trials that specifically demonstrate efficacy of AMI guidelines for this subgroup of vulnerable patients.

Physicians wear white coats. In many medical centers, the length of one's coat grows with seniority; medical students, interns, and residents wear short white coats, while attending staff graduate to long white coats with their names embroidered on the front. This traditional uniform serves a similar role to the stripes on a military sleeve. That is, by examining the length of a person's coat, a nurse or other hospital employee can rapidly determine the seniority, and theoretically the increased medical knowledge, of the person inside.

Of course, it isn't quite this simple. In many places, all residents wear long coats (with embroidered names). In other hospitals, attending staff wear short coats. The problem of distinguishing between a medical student, resident, and attending physician can be quite vexing, particularly after the summer months when the anxiety visible on the faces of new house staff and third‐year medical students fades away into the more seasoned look of fatigue and malaise. As hospital‐based practitioners, what are we to do?

To be certain there are clues one can use to identify one's rank in the medical profession. Often medical students wear a medical school pin bestowed upon them at a robing ceremony or other coming‐of‐age festivity to mark the transition to the clinical training years.1 (Little do they know that the primary utility of such adornments is to mark them, as though with a scarlet letter, for easy identification when one wishes to pimp the medical team.)2 Similarly, one can look for an arm patch. Just as a mother hen has the need to identify her own chicks, so too is it helpful for the residency director to have each of his or her own residents easily identifiable by the residency patch emblazoned upon the arm of their (long) white coat. The patch test can fail, though, for too often the residency emblem is merely a simple modification of the hospital or medical center logo, and thus not easily distinguishable.

When all else fails, of course, you can look to the pockets. As one's medical knowledge and training rank increases, the number of papers, pens, and instruments in the pockets of the white coat decreases. This inverse relationship provides some increased ability to identify medical students and junior house staff. For example, a short white coat, busting with oversized index cards held together by a large metal ring, several tattered and folded journal articles, and a worn spiral‐bound text suggests a medical student or intern. If they have an electrocardiogram (ECG), calipers, and tuning fork visible, safe bet is you've found a medical student. Conversely, if the white coat sports several free pens (with medication logos embossed on their stems) and has more than a few stains, chances are you've spotted an intern.

Unfortunately, none of this is of much utility in identifying a physician, as the initial premise that physicians wear white coats may be false. The problem is 2‐fold. First of all, not all physicians wear white coats (or any coat for that matter), and, many nonphysicians wear white coats. Commonly, phlebotomists, pharmacists, and respiratory technicians wear white coats; long white coats, in fact. So do nutritionists, speech pathologists, the clerk at the radiology file room, and even the cashiers in the cafeteria. And why not? Each of these persons has an important role to play in the operation of a modern medical center. The long white coat serves as professional uniform to identify the wearer as contributing to the mission of the medical center. It engenders confidence and suggests cleanliness and purity.

The problem remains, however, what should I, as an attending physician wear? You see, patients encounter so many persons in their visits to the hospital that it is not clear who their doctor is. (It's not statistically likely to be the man in a long white coat.) Being able to identify the attending physician is important. The attending physician is ultimately responsible for the patient's care.

There are many guidelines for how to dress. For example, don't wear white after Labor Day. The pleats on a cummerbund point so that the folds open pointing up (apparently it was originally meant to serve as a ticket holder, perhaps in the days before pockets?). Match your belt to your shoes. The list goes on. However, physicians are not commonly associated with natty attire, so fashion help for the MD is hard to find, though nonetheless necessary.

Even wearing white is questionable. White robes have been associated with purity and sanctity for centuries. Religious leaders have donned white for spiritual cleansing of their communities on the most holy of days. I like the idea of appearing pure and holy. Of course, I don't want to mislead anybody, either.

Brides have traditionally worn white dresses. But, while many believe this is to convey a sense of premarital purity, more likely the tradition stems from an ancient Roman practice of wearing white as a symbol of joyous celebration. Interestingly, in some parts of Asia, people at a funeral wear white while the deceased is dressed in red.

In some environments, the culture of the medical center prescribes appropriate apparel. The Mayo Clinic in Minnesota, for example, has had a tradition of having their physician staff dress in business attire. By this, they mean conservative sport coats or suits with ties for men, and similar appropriate women's business clothing. As noted by Leonard L. Berry and Neeli Bendapudi in their article Why Docs Don't Wear White Coats or Polo Shirts at the Mayo Clinic3 in the Harvard Business School publication Working Knowledge for Business Leaders, while some may consider this semiformal business dress pretentious, it should be considered no more pretentious than, say, the dress code for airline pilots. Airline passengers don't want to see their pilot in a polo shirt, and patients feel the same way about their doctors. The business attire is a uniform; it's a visible clue that communicates respect to patients and their families. But, isn't a white coat a uniform that conveys respect? Perhaps a white coat isn't safe if the physician wants to stand out to oncoming traffic in his snowy Minnesota environs.

Besides, is it true that patients don't want their physician to wear a polo shirt? Perhaps casual dress will break down 1 of the patient‐doctor barriers to communication and allow for improved comfort with greater honesty in patientphysician interactions? Prior to designing a prospective controlled randomized trial to answer this question myself, I reviewed the available literature.

It turns out, that an evaluation of polo‐shirt‐wearing physicians has been carried out. Drs. Barrett and Booth4 from the Birmingham Maternity Hospital in England questioned 203 groups of parents and children (406 individuals) about various levels of physician dress. Seventy percent of participants thought that how the doctor dressed was important. Among children, a male physician in a polo shirt was considered more friendly and gentle than the male physician in a white coat (who did get points for being more competent and more concerned). Women physicians in T‐shirts were also though to be friendlier than if in a white coat, but similarly less competent. Parents were more likely to prefer casually‐dressed physicians and were poor at predicting what their children would want.

So, a polo shirt makes me look friendly, gentle, and less competent? What about a polo shirt under a white coatis that the whole package? What about business attire, as per the Mayo Clinic requirements? These questions remain unanswered. So, back to the literature.

In the Journal of the American Medical Association, in 1987, Dunn et al.5 evaluated 200 medical patients in Boston and San Francisco regarding their preference for physician dress. Sixty‐five percent believed physicians should wear a white coat, 27% said no tennis shoes, one‐half said no blue jeans, and about one‐third thought male physicians should wear ties and female physicians should be in a skirt or dress. I suppose the conclusion here is to wear a white coat with or without jeans and most of the time without a tie, though almost always with proper shoes, or at least without tennis shoes. (I practice in Boston and trained partly in San Francisco so this advice seems particularly valid for me.)

It may be more obvious what to do in Japan. Ikusaka et al.6 evaluated the experience of patients at a university clinic seen by a consulting physician in either a white coat, or private clothes. To me, private clothes imply pajamas and a bathrobe, but we must assume this means some form of professional dress lacking a white coat. It turns out that 71% of the Japanese patients seeing a doctor in a white coat preferred a white coat, though more patients seeing a physician in a white coat (vs. private clothes) felt tense during their consultation. The researchers stress that the presence of a white coat did not increase satisfaction with the consultation. They conclude, that while patients may say they prefer a white coat, maybe it would be better not to wear one since it makes patients feel tense.

In addition to feeling tense, white coats may cause hypertension. The phenomenon of elevated blood pressure when in the presence of the physician (or other hospital staff in a white coat) has been long documented. This white coat hypertension can be found in more than 15% of the population who have a measured blood pressure in the office of over 140/90 mmHg with normal daytime mean ambulatory blood pressure readings (when not around a white‐coat‐wearing stress‐inducing medical worker).7 Older adults, females, and nonsmokers were more likely to have white coat hypertension than other persons.

And yet, older adults prefer white coats. The Japanese study (Ikusaka et al.6) concluded that elderly patients prefer a white coat to other attire. Similarly, a study from the Royal Free Hospital, London, showed that white coats were twice as popular with patients as they were with physicians.8 Specifically, patients found the white coats made doctors easier to identify. In an article by the British Broadcasting Corporation (BBC) on the subject, it was noted that the elderly largely preferred physicians in white coats, while children preferred physicians without white coats. British children must prefer a friendly doctor to a competent one.

The article further suggests that only 1 in 8 physicians wears a white coat, complaining that they are too hot and uncomfortable, and may carry the risk of transmitting infections. The white coat, the symbol of cleanliness and purity, a source of infection? To add hypocrisy to the equation, one‐half of physicians who thought white coats should be worn admitted to never actually wearing a white coat. In fact, only 7 of 86 physicians surveyed wore their white coat on a daily basis. The BBC goes on to note that in Australia, the white coat is gaining momentum as there seems to be a movement towards rediscovering the white coat as a symbol of purpose and pride as a profession.8

Really? Let's consult the literature! According to Dr. D.A. Watson,9 White coats have largely disappeared from Australian teaching hospitals and the majority of junior doctors in Australia oppose the wearing of white coats. In a survey of 337 junior medical officers, only 16% preferred to wear a white coat. Peer pressure seems to have something to do with this, as 70% say they don't wear a white coat because nobody else wears a white coat. This is indeed a compelling argument.

Of course, a better argument against wearing a white coat may be that it causes tension (at least in Japanese patients) and may cause white‐coat‐hypertension, resulting in the inappropriate diagnosis and treatment of elevated blood pressure. In Australia, however, it seems that wearing a white coat may make patients too relaxed. Wing et al.10 noted that in 21% to 45% of elderly patients, blood pressure was atypically low when checked in the physician's office as compared to mean ambulatory blood pressure. This reverse‐white‐coat‐hypertension could result in the omission of necessary blood pressure treatment.

In the United States, residentsour own version of the Australian junior medical officercommonly wear scrubs covered by a white coat. Scrub clothes are typically available without charge from the hospital, limit the amount of laundry a busy resident needs to do, and can be put on with little concern as to pressed pleats or matching colors. The overlying white coat adds a moderate degree of formality to what could otherwise be mistaken as pajamas, while providing convenient pockets for the aforementioned papers and miscellaneous equipment and souvenirs. This outfit is likely one of practicality rather than a desire to be most appealing to patients. But, what do you know? It seems that patients prefer their resident physicians to dress this way. Dr. A. Cha et al.11 at the Northeastern Ohio College of Medicine found that patients in an obstetrics and gynecology clinic overall felt that resident physicians dressed in surgical scrubs with a white coat made them feel more comfortable and confident than if dressed otherwise. On the question of a white coat specifically, the majority had no preference that their physician wear one.

So, it's very much unclear whether a white coat is a tension‐causing, blood‐pressure‐elevating, infection risk or a competence‐implying blood‐pressure‐lowering way to identify a physician. As a result, the jury is still out on whether physicians should wear white.

One thing I do know, however, is that patients shouldn't wear white. But they do. As an OtolaryngologistHead and Neck Surgeon, my clinical practice is split between surgical procedures and office visits. Commonly, patients with sinus or nasal surgery will require some form of cotton gauze or foam material within the nose in order to tamponade bleeding. Similarly, patients presenting to the emergency department or urgent care center with epistaxis may have their noses packed and then be told to see an otolaryngologist (eg, me) in 3 or 4 days to have the packing removed. I also commonly remove facial skin lesions, biopsy tongue masses, reduce nasal fractures, and otherwise engage in activities with an above average propensity to result in a mess. More often than happenstance will allow, patients come to see me for such visits in their white Sunday best. I truly care for my patients. I respect them as individuals and desire to do no harm. This includes not staining their shirts, ties, or pants. However, there is no amount of blue towels or gauze pads than can keep a white shirt clean when you have that first sneeze after removal of your nasal packing.12

So what is it that makes so many patients come to the office in a white shirt? Perhaps patients subconsciously associate healthcare with the color white since their doctors wear white coats and the nurses wear starched white dresses with tight white folded caps on top of their head. I've never seen a nurse in a white dress and hat, but believe television programs have shown this in the past.

Maybe the answer lies in an adaptation of data from another Australian study. In a survey of 180 oncology patients about white coats on physicians, the most common argument against wearing the white coat was that it represented a barrier between the physician and the patient.13 However, it is indeed the sane patient who desires to have a barrier between their physician and the removal of nasal packing, a skin lesion, or a tongue mass. Another possibility is that as fewer and fewer physicians wear white, patients are gravitating toward this color as a way of distinguishing themselves from the medical staff. Perhaps a person dressed in white is less likely to be grabbed in the hallway with a Doctor come quick! and more likely to be allowed to just sit peacefully in the waiting room with a 1997 issue of Ladies Home Journal or Senior Fisherman magazine.

Of course, perhaps patients believe the fashion experts who expound that white goes with everything. If so, they soon learn that white doesn't go so well with blotchy splattered red.

The truth is, I don't want my patients to wear white. Between making certain I project myself as approachable and easy to speak with, remembering to cover all the appropriate irrelevant parts of the history and physical to comply with billing requirements, entering data in our easy‐to‐navigate electronic medical record, and attempting to both diagnose the problem and discern an acceptable and effective treatment, the last thing I need is to worry about staining patient shirts! I believe that this phenomenon is widespread among medical practitioners and should be called white‐shirt‐hypertension.

Conclusion

After reviewing the available literature, I've determined that patients should not wear white. However, I'm still not certain how I should dress. For now, I'll stick with whatever is clean and professional and make sure my belt and shoes match. I may or may not wear a tie, since another study showed that 30% of patients believed their physician wore a tie even if they didn't.14 Of course, I'll put on the white coat for the semiannual meeting with the chairman, or if I'm having something messy for lunch and wore a tie that day.

I'll also wear my name badge. It says I'm an attending physician and not a resident. It opens doors around the hospital. Literally. It's got a magnetic stripe.

Physicians wear white coats. In many medical centers, the length of one's coat grows with seniority; medical students, interns, and residents wear short white coats, while attending staff graduate to long white coats with their names embroidered on the front. This traditional uniform serves a similar role to the stripes on a military sleeve. That is, by examining the length of a person's coat, a nurse or other hospital employee can rapidly determine the seniority, and theoretically the increased medical knowledge, of the person inside.

Of course, it isn't quite this simple. In many places, all residents wear long coats (with embroidered names). In other hospitals, attending staff wear short coats. The problem of distinguishing between a medical student, resident, and attending physician can be quite vexing, particularly after the summer months when the anxiety visible on the faces of new house staff and third‐year medical students fades away into the more seasoned look of fatigue and malaise. As hospital‐based practitioners, what are we to do?

To be certain there are clues one can use to identify one's rank in the medical profession. Often medical students wear a medical school pin bestowed upon them at a robing ceremony or other coming‐of‐age festivity to mark the transition to the clinical training years.1 (Little do they know that the primary utility of such adornments is to mark them, as though with a scarlet letter, for easy identification when one wishes to pimp the medical team.)2 Similarly, one can look for an arm patch. Just as a mother hen has the need to identify her own chicks, so too is it helpful for the residency director to have each of his or her own residents easily identifiable by the residency patch emblazoned upon the arm of their (long) white coat. The patch test can fail, though, for too often the residency emblem is merely a simple modification of the hospital or medical center logo, and thus not easily distinguishable.

When all else fails, of course, you can look to the pockets. As one's medical knowledge and training rank increases, the number of papers, pens, and instruments in the pockets of the white coat decreases. This inverse relationship provides some increased ability to identify medical students and junior house staff. For example, a short white coat, busting with oversized index cards held together by a large metal ring, several tattered and folded journal articles, and a worn spiral‐bound text suggests a medical student or intern. If they have an electrocardiogram (ECG), calipers, and tuning fork visible, safe bet is you've found a medical student. Conversely, if the white coat sports several free pens (with medication logos embossed on their stems) and has more than a few stains, chances are you've spotted an intern.

Unfortunately, none of this is of much utility in identifying a physician, as the initial premise that physicians wear white coats may be false. The problem is 2‐fold. First of all, not all physicians wear white coats (or any coat for that matter), and, many nonphysicians wear white coats. Commonly, phlebotomists, pharmacists, and respiratory technicians wear white coats; long white coats, in fact. So do nutritionists, speech pathologists, the clerk at the radiology file room, and even the cashiers in the cafeteria. And why not? Each of these persons has an important role to play in the operation of a modern medical center. The long white coat serves as professional uniform to identify the wearer as contributing to the mission of the medical center. It engenders confidence and suggests cleanliness and purity.

The problem remains, however, what should I, as an attending physician wear? You see, patients encounter so many persons in their visits to the hospital that it is not clear who their doctor is. (It's not statistically likely to be the man in a long white coat.) Being able to identify the attending physician is important. The attending physician is ultimately responsible for the patient's care.

There are many guidelines for how to dress. For example, don't wear white after Labor Day. The pleats on a cummerbund point so that the folds open pointing up (apparently it was originally meant to serve as a ticket holder, perhaps in the days before pockets?). Match your belt to your shoes. The list goes on. However, physicians are not commonly associated with natty attire, so fashion help for the MD is hard to find, though nonetheless necessary.

Even wearing white is questionable. White robes have been associated with purity and sanctity for centuries. Religious leaders have donned white for spiritual cleansing of their communities on the most holy of days. I like the idea of appearing pure and holy. Of course, I don't want to mislead anybody, either.

Brides have traditionally worn white dresses. But, while many believe this is to convey a sense of premarital purity, more likely the tradition stems from an ancient Roman practice of wearing white as a symbol of joyous celebration. Interestingly, in some parts of Asia, people at a funeral wear white while the deceased is dressed in red.

In some environments, the culture of the medical center prescribes appropriate apparel. The Mayo Clinic in Minnesota, for example, has had a tradition of having their physician staff dress in business attire. By this, they mean conservative sport coats or suits with ties for men, and similar appropriate women's business clothing. As noted by Leonard L. Berry and Neeli Bendapudi in their article Why Docs Don't Wear White Coats or Polo Shirts at the Mayo Clinic3 in the Harvard Business School publication Working Knowledge for Business Leaders, while some may consider this semiformal business dress pretentious, it should be considered no more pretentious than, say, the dress code for airline pilots. Airline passengers don't want to see their pilot in a polo shirt, and patients feel the same way about their doctors. The business attire is a uniform; it's a visible clue that communicates respect to patients and their families. But, isn't a white coat a uniform that conveys respect? Perhaps a white coat isn't safe if the physician wants to stand out to oncoming traffic in his snowy Minnesota environs.

Besides, is it true that patients don't want their physician to wear a polo shirt? Perhaps casual dress will break down 1 of the patient‐doctor barriers to communication and allow for improved comfort with greater honesty in patientphysician interactions? Prior to designing a prospective controlled randomized trial to answer this question myself, I reviewed the available literature.

It turns out, that an evaluation of polo‐shirt‐wearing physicians has been carried out. Drs. Barrett and Booth4 from the Birmingham Maternity Hospital in England questioned 203 groups of parents and children (406 individuals) about various levels of physician dress. Seventy percent of participants thought that how the doctor dressed was important. Among children, a male physician in a polo shirt was considered more friendly and gentle than the male physician in a white coat (who did get points for being more competent and more concerned). Women physicians in T‐shirts were also though to be friendlier than if in a white coat, but similarly less competent. Parents were more likely to prefer casually‐dressed physicians and were poor at predicting what their children would want.

So, a polo shirt makes me look friendly, gentle, and less competent? What about a polo shirt under a white coatis that the whole package? What about business attire, as per the Mayo Clinic requirements? These questions remain unanswered. So, back to the literature.

In the Journal of the American Medical Association, in 1987, Dunn et al.5 evaluated 200 medical patients in Boston and San Francisco regarding their preference for physician dress. Sixty‐five percent believed physicians should wear a white coat, 27% said no tennis shoes, one‐half said no blue jeans, and about one‐third thought male physicians should wear ties and female physicians should be in a skirt or dress. I suppose the conclusion here is to wear a white coat with or without jeans and most of the time without a tie, though almost always with proper shoes, or at least without tennis shoes. (I practice in Boston and trained partly in San Francisco so this advice seems particularly valid for me.)

It may be more obvious what to do in Japan. Ikusaka et al.6 evaluated the experience of patients at a university clinic seen by a consulting physician in either a white coat, or private clothes. To me, private clothes imply pajamas and a bathrobe, but we must assume this means some form of professional dress lacking a white coat. It turns out that 71% of the Japanese patients seeing a doctor in a white coat preferred a white coat, though more patients seeing a physician in a white coat (vs. private clothes) felt tense during their consultation. The researchers stress that the presence of a white coat did not increase satisfaction with the consultation. They conclude, that while patients may say they prefer a white coat, maybe it would be better not to wear one since it makes patients feel tense.

In addition to feeling tense, white coats may cause hypertension. The phenomenon of elevated blood pressure when in the presence of the physician (or other hospital staff in a white coat) has been long documented. This white coat hypertension can be found in more than 15% of the population who have a measured blood pressure in the office of over 140/90 mmHg with normal daytime mean ambulatory blood pressure readings (when not around a white‐coat‐wearing stress‐inducing medical worker).7 Older adults, females, and nonsmokers were more likely to have white coat hypertension than other persons.

And yet, older adults prefer white coats. The Japanese study (Ikusaka et al.6) concluded that elderly patients prefer a white coat to other attire. Similarly, a study from the Royal Free Hospital, London, showed that white coats were twice as popular with patients as they were with physicians.8 Specifically, patients found the white coats made doctors easier to identify. In an article by the British Broadcasting Corporation (BBC) on the subject, it was noted that the elderly largely preferred physicians in white coats, while children preferred physicians without white coats. British children must prefer a friendly doctor to a competent one.

The article further suggests that only 1 in 8 physicians wears a white coat, complaining that they are too hot and uncomfortable, and may carry the risk of transmitting infections. The white coat, the symbol of cleanliness and purity, a source of infection? To add hypocrisy to the equation, one‐half of physicians who thought white coats should be worn admitted to never actually wearing a white coat. In fact, only 7 of 86 physicians surveyed wore their white coat on a daily basis. The BBC goes on to note that in Australia, the white coat is gaining momentum as there seems to be a movement towards rediscovering the white coat as a symbol of purpose and pride as a profession.8

Really? Let's consult the literature! According to Dr. D.A. Watson,9 White coats have largely disappeared from Australian teaching hospitals and the majority of junior doctors in Australia oppose the wearing of white coats. In a survey of 337 junior medical officers, only 16% preferred to wear a white coat. Peer pressure seems to have something to do with this, as 70% say they don't wear a white coat because nobody else wears a white coat. This is indeed a compelling argument.

Of course, a better argument against wearing a white coat may be that it causes tension (at least in Japanese patients) and may cause white‐coat‐hypertension, resulting in the inappropriate diagnosis and treatment of elevated blood pressure. In Australia, however, it seems that wearing a white coat may make patients too relaxed. Wing et al.10 noted that in 21% to 45% of elderly patients, blood pressure was atypically low when checked in the physician's office as compared to mean ambulatory blood pressure. This reverse‐white‐coat‐hypertension could result in the omission of necessary blood pressure treatment.

In the United States, residentsour own version of the Australian junior medical officercommonly wear scrubs covered by a white coat. Scrub clothes are typically available without charge from the hospital, limit the amount of laundry a busy resident needs to do, and can be put on with little concern as to pressed pleats or matching colors. The overlying white coat adds a moderate degree of formality to what could otherwise be mistaken as pajamas, while providing convenient pockets for the aforementioned papers and miscellaneous equipment and souvenirs. This outfit is likely one of practicality rather than a desire to be most appealing to patients. But, what do you know? It seems that patients prefer their resident physicians to dress this way. Dr. A. Cha et al.11 at the Northeastern Ohio College of Medicine found that patients in an obstetrics and gynecology clinic overall felt that resident physicians dressed in surgical scrubs with a white coat made them feel more comfortable and confident than if dressed otherwise. On the question of a white coat specifically, the majority had no preference that their physician wear one.

So, it's very much unclear whether a white coat is a tension‐causing, blood‐pressure‐elevating, infection risk or a competence‐implying blood‐pressure‐lowering way to identify a physician. As a result, the jury is still out on whether physicians should wear white.

One thing I do know, however, is that patients shouldn't wear white. But they do. As an OtolaryngologistHead and Neck Surgeon, my clinical practice is split between surgical procedures and office visits. Commonly, patients with sinus or nasal surgery will require some form of cotton gauze or foam material within the nose in order to tamponade bleeding. Similarly, patients presenting to the emergency department or urgent care center with epistaxis may have their noses packed and then be told to see an otolaryngologist (eg, me) in 3 or 4 days to have the packing removed. I also commonly remove facial skin lesions, biopsy tongue masses, reduce nasal fractures, and otherwise engage in activities with an above average propensity to result in a mess. More often than happenstance will allow, patients come to see me for such visits in their white Sunday best. I truly care for my patients. I respect them as individuals and desire to do no harm. This includes not staining their shirts, ties, or pants. However, there is no amount of blue towels or gauze pads than can keep a white shirt clean when you have that first sneeze after removal of your nasal packing.12

So what is it that makes so many patients come to the office in a white shirt? Perhaps patients subconsciously associate healthcare with the color white since their doctors wear white coats and the nurses wear starched white dresses with tight white folded caps on top of their head. I've never seen a nurse in a white dress and hat, but believe television programs have shown this in the past.

Maybe the answer lies in an adaptation of data from another Australian study. In a survey of 180 oncology patients about white coats on physicians, the most common argument against wearing the white coat was that it represented a barrier between the physician and the patient.13 However, it is indeed the sane patient who desires to have a barrier between their physician and the removal of nasal packing, a skin lesion, or a tongue mass. Another possibility is that as fewer and fewer physicians wear white, patients are gravitating toward this color as a way of distinguishing themselves from the medical staff. Perhaps a person dressed in white is less likely to be grabbed in the hallway with a Doctor come quick! and more likely to be allowed to just sit peacefully in the waiting room with a 1997 issue of Ladies Home Journal or Senior Fisherman magazine.

Of course, perhaps patients believe the fashion experts who expound that white goes with everything. If so, they soon learn that white doesn't go so well with blotchy splattered red.

The truth is, I don't want my patients to wear white. Between making certain I project myself as approachable and easy to speak with, remembering to cover all the appropriate irrelevant parts of the history and physical to comply with billing requirements, entering data in our easy‐to‐navigate electronic medical record, and attempting to both diagnose the problem and discern an acceptable and effective treatment, the last thing I need is to worry about staining patient shirts! I believe that this phenomenon is widespread among medical practitioners and should be called white‐shirt‐hypertension.

Conclusion

After reviewing the available literature, I've determined that patients should not wear white. However, I'm still not certain how I should dress. For now, I'll stick with whatever is clean and professional and make sure my belt and shoes match. I may or may not wear a tie, since another study showed that 30% of patients believed their physician wore a tie even if they didn't.14 Of course, I'll put on the white coat for the semiannual meeting with the chairman, or if I'm having something messy for lunch and wore a tie that day.

I'll also wear my name badge. It says I'm an attending physician and not a resident. It opens doors around the hospital. Literally. It's got a magnetic stripe.

Physicians wear white coats. In many medical centers, the length of one's coat grows with seniority; medical students, interns, and residents wear short white coats, while attending staff graduate to long white coats with their names embroidered on the front. This traditional uniform serves a similar role to the stripes on a military sleeve. That is, by examining the length of a person's coat, a nurse or other hospital employee can rapidly determine the seniority, and theoretically the increased medical knowledge, of the person inside.

Of course, it isn't quite this simple. In many places, all residents wear long coats (with embroidered names). In other hospitals, attending staff wear short coats. The problem of distinguishing between a medical student, resident, and attending physician can be quite vexing, particularly after the summer months when the anxiety visible on the faces of new house staff and third‐year medical students fades away into the more seasoned look of fatigue and malaise. As hospital‐based practitioners, what are we to do?

To be certain there are clues one can use to identify one's rank in the medical profession. Often medical students wear a medical school pin bestowed upon them at a robing ceremony or other coming‐of‐age festivity to mark the transition to the clinical training years.1 (Little do they know that the primary utility of such adornments is to mark them, as though with a scarlet letter, for easy identification when one wishes to pimp the medical team.)2 Similarly, one can look for an arm patch. Just as a mother hen has the need to identify her own chicks, so too is it helpful for the residency director to have each of his or her own residents easily identifiable by the residency patch emblazoned upon the arm of their (long) white coat. The patch test can fail, though, for too often the residency emblem is merely a simple modification of the hospital or medical center logo, and thus not easily distinguishable.

When all else fails, of course, you can look to the pockets. As one's medical knowledge and training rank increases, the number of papers, pens, and instruments in the pockets of the white coat decreases. This inverse relationship provides some increased ability to identify medical students and junior house staff. For example, a short white coat, busting with oversized index cards held together by a large metal ring, several tattered and folded journal articles, and a worn spiral‐bound text suggests a medical student or intern. If they have an electrocardiogram (ECG), calipers, and tuning fork visible, safe bet is you've found a medical student. Conversely, if the white coat sports several free pens (with medication logos embossed on their stems) and has more than a few stains, chances are you've spotted an intern.

Unfortunately, none of this is of much utility in identifying a physician, as the initial premise that physicians wear white coats may be false. The problem is 2‐fold. First of all, not all physicians wear white coats (or any coat for that matter), and, many nonphysicians wear white coats. Commonly, phlebotomists, pharmacists, and respiratory technicians wear white coats; long white coats, in fact. So do nutritionists, speech pathologists, the clerk at the radiology file room, and even the cashiers in the cafeteria. And why not? Each of these persons has an important role to play in the operation of a modern medical center. The long white coat serves as professional uniform to identify the wearer as contributing to the mission of the medical center. It engenders confidence and suggests cleanliness and purity.

The problem remains, however, what should I, as an attending physician wear? You see, patients encounter so many persons in their visits to the hospital that it is not clear who their doctor is. (It's not statistically likely to be the man in a long white coat.) Being able to identify the attending physician is important. The attending physician is ultimately responsible for the patient's care.

There are many guidelines for how to dress. For example, don't wear white after Labor Day. The pleats on a cummerbund point so that the folds open pointing up (apparently it was originally meant to serve as a ticket holder, perhaps in the days before pockets?). Match your belt to your shoes. The list goes on. However, physicians are not commonly associated with natty attire, so fashion help for the MD is hard to find, though nonetheless necessary.

Even wearing white is questionable. White robes have been associated with purity and sanctity for centuries. Religious leaders have donned white for spiritual cleansing of their communities on the most holy of days. I like the idea of appearing pure and holy. Of course, I don't want to mislead anybody, either.

Brides have traditionally worn white dresses. But, while many believe this is to convey a sense of premarital purity, more likely the tradition stems from an ancient Roman practice of wearing white as a symbol of joyous celebration. Interestingly, in some parts of Asia, people at a funeral wear white while the deceased is dressed in red.

In some environments, the culture of the medical center prescribes appropriate apparel. The Mayo Clinic in Minnesota, for example, has had a tradition of having their physician staff dress in business attire. By this, they mean conservative sport coats or suits with ties for men, and similar appropriate women's business clothing. As noted by Leonard L. Berry and Neeli Bendapudi in their article Why Docs Don't Wear White Coats or Polo Shirts at the Mayo Clinic3 in the Harvard Business School publication Working Knowledge for Business Leaders, while some may consider this semiformal business dress pretentious, it should be considered no more pretentious than, say, the dress code for airline pilots. Airline passengers don't want to see their pilot in a polo shirt, and patients feel the same way about their doctors. The business attire is a uniform; it's a visible clue that communicates respect to patients and their families. But, isn't a white coat a uniform that conveys respect? Perhaps a white coat isn't safe if the physician wants to stand out to oncoming traffic in his snowy Minnesota environs.

Besides, is it true that patients don't want their physician to wear a polo shirt? Perhaps casual dress will break down 1 of the patient‐doctor barriers to communication and allow for improved comfort with greater honesty in patientphysician interactions? Prior to designing a prospective controlled randomized trial to answer this question myself, I reviewed the available literature.

It turns out, that an evaluation of polo‐shirt‐wearing physicians has been carried out. Drs. Barrett and Booth4 from the Birmingham Maternity Hospital in England questioned 203 groups of parents and children (406 individuals) about various levels of physician dress. Seventy percent of participants thought that how the doctor dressed was important. Among children, a male physician in a polo shirt was considered more friendly and gentle than the male physician in a white coat (who did get points for being more competent and more concerned). Women physicians in T‐shirts were also though to be friendlier than if in a white coat, but similarly less competent. Parents were more likely to prefer casually‐dressed physicians and were poor at predicting what their children would want.

So, a polo shirt makes me look friendly, gentle, and less competent? What about a polo shirt under a white coatis that the whole package? What about business attire, as per the Mayo Clinic requirements? These questions remain unanswered. So, back to the literature.

In the Journal of the American Medical Association, in 1987, Dunn et al.5 evaluated 200 medical patients in Boston and San Francisco regarding their preference for physician dress. Sixty‐five percent believed physicians should wear a white coat, 27% said no tennis shoes, one‐half said no blue jeans, and about one‐third thought male physicians should wear ties and female physicians should be in a skirt or dress. I suppose the conclusion here is to wear a white coat with or without jeans and most of the time without a tie, though almost always with proper shoes, or at least without tennis shoes. (I practice in Boston and trained partly in San Francisco so this advice seems particularly valid for me.)

It may be more obvious what to do in Japan. Ikusaka et al.6 evaluated the experience of patients at a university clinic seen by a consulting physician in either a white coat, or private clothes. To me, private clothes imply pajamas and a bathrobe, but we must assume this means some form of professional dress lacking a white coat. It turns out that 71% of the Japanese patients seeing a doctor in a white coat preferred a white coat, though more patients seeing a physician in a white coat (vs. private clothes) felt tense during their consultation. The researchers stress that the presence of a white coat did not increase satisfaction with the consultation. They conclude, that while patients may say they prefer a white coat, maybe it would be better not to wear one since it makes patients feel tense.

In addition to feeling tense, white coats may cause hypertension. The phenomenon of elevated blood pressure when in the presence of the physician (or other hospital staff in a white coat) has been long documented. This white coat hypertension can be found in more than 15% of the population who have a measured blood pressure in the office of over 140/90 mmHg with normal daytime mean ambulatory blood pressure readings (when not around a white‐coat‐wearing stress‐inducing medical worker).7 Older adults, females, and nonsmokers were more likely to have white coat hypertension than other persons.

And yet, older adults prefer white coats. The Japanese study (Ikusaka et al.6) concluded that elderly patients prefer a white coat to other attire. Similarly, a study from the Royal Free Hospital, London, showed that white coats were twice as popular with patients as they were with physicians.8 Specifically, patients found the white coats made doctors easier to identify. In an article by the British Broadcasting Corporation (BBC) on the subject, it was noted that the elderly largely preferred physicians in white coats, while children preferred physicians without white coats. British children must prefer a friendly doctor to a competent one.

The article further suggests that only 1 in 8 physicians wears a white coat, complaining that they are too hot and uncomfortable, and may carry the risk of transmitting infections. The white coat, the symbol of cleanliness and purity, a source of infection? To add hypocrisy to the equation, one‐half of physicians who thought white coats should be worn admitted to never actually wearing a white coat. In fact, only 7 of 86 physicians surveyed wore their white coat on a daily basis. The BBC goes on to note that in Australia, the white coat is gaining momentum as there seems to be a movement towards rediscovering the white coat as a symbol of purpose and pride as a profession.8

Really? Let's consult the literature! According to Dr. D.A. Watson,9 White coats have largely disappeared from Australian teaching hospitals and the majority of junior doctors in Australia oppose the wearing of white coats. In a survey of 337 junior medical officers, only 16% preferred to wear a white coat. Peer pressure seems to have something to do with this, as 70% say they don't wear a white coat because nobody else wears a white coat. This is indeed a compelling argument.

Of course, a better argument against wearing a white coat may be that it causes tension (at least in Japanese patients) and may cause white‐coat‐hypertension, resulting in the inappropriate diagnosis and treatment of elevated blood pressure. In Australia, however, it seems that wearing a white coat may make patients too relaxed. Wing et al.10 noted that in 21% to 45% of elderly patients, blood pressure was atypically low when checked in the physician's office as compared to mean ambulatory blood pressure. This reverse‐white‐coat‐hypertension could result in the omission of necessary blood pressure treatment.

In the United States, residentsour own version of the Australian junior medical officercommonly wear scrubs covered by a white coat. Scrub clothes are typically available without charge from the hospital, limit the amount of laundry a busy resident needs to do, and can be put on with little concern as to pressed pleats or matching colors. The overlying white coat adds a moderate degree of formality to what could otherwise be mistaken as pajamas, while providing convenient pockets for the aforementioned papers and miscellaneous equipment and souvenirs. This outfit is likely one of practicality rather than a desire to be most appealing to patients. But, what do you know? It seems that patients prefer their resident physicians to dress this way. Dr. A. Cha et al.11 at the Northeastern Ohio College of Medicine found that patients in an obstetrics and gynecology clinic overall felt that resident physicians dressed in surgical scrubs with a white coat made them feel more comfortable and confident than if dressed otherwise. On the question of a white coat specifically, the majority had no preference that their physician wear one.

So, it's very much unclear whether a white coat is a tension‐causing, blood‐pressure‐elevating, infection risk or a competence‐implying blood‐pressure‐lowering way to identify a physician. As a result, the jury is still out on whether physicians should wear white.

One thing I do know, however, is that patients shouldn't wear white. But they do. As an OtolaryngologistHead and Neck Surgeon, my clinical practice is split between surgical procedures and office visits. Commonly, patients with sinus or nasal surgery will require some form of cotton gauze or foam material within the nose in order to tamponade bleeding. Similarly, patients presenting to the emergency department or urgent care center with epistaxis may have their noses packed and then be told to see an otolaryngologist (eg, me) in 3 or 4 days to have the packing removed. I also commonly remove facial skin lesions, biopsy tongue masses, reduce nasal fractures, and otherwise engage in activities with an above average propensity to result in a mess. More often than happenstance will allow, patients come to see me for such visits in their white Sunday best. I truly care for my patients. I respect them as individuals and desire to do no harm. This includes not staining their shirts, ties, or pants. However, there is no amount of blue towels or gauze pads than can keep a white shirt clean when you have that first sneeze after removal of your nasal packing.12

So what is it that makes so many patients come to the office in a white shirt? Perhaps patients subconsciously associate healthcare with the color white since their doctors wear white coats and the nurses wear starched white dresses with tight white folded caps on top of their head. I've never seen a nurse in a white dress and hat, but believe television programs have shown this in the past.

Maybe the answer lies in an adaptation of data from another Australian study. In a survey of 180 oncology patients about white coats on physicians, the most common argument against wearing the white coat was that it represented a barrier between the physician and the patient.13 However, it is indeed the sane patient who desires to have a barrier between their physician and the removal of nasal packing, a skin lesion, or a tongue mass. Another possibility is that as fewer and fewer physicians wear white, patients are gravitating toward this color as a way of distinguishing themselves from the medical staff. Perhaps a person dressed in white is less likely to be grabbed in the hallway with a Doctor come quick! and more likely to be allowed to just sit peacefully in the waiting room with a 1997 issue of Ladies Home Journal or Senior Fisherman magazine.

Of course, perhaps patients believe the fashion experts who expound that white goes with everything. If so, they soon learn that white doesn't go so well with blotchy splattered red.

The truth is, I don't want my patients to wear white. Between making certain I project myself as approachable and easy to speak with, remembering to cover all the appropriate irrelevant parts of the history and physical to comply with billing requirements, entering data in our easy‐to‐navigate electronic medical record, and attempting to both diagnose the problem and discern an acceptable and effective treatment, the last thing I need is to worry about staining patient shirts! I believe that this phenomenon is widespread among medical practitioners and should be called white‐shirt‐hypertension.

Conclusion

After reviewing the available literature, I've determined that patients should not wear white. However, I'm still not certain how I should dress. For now, I'll stick with whatever is clean and professional and make sure my belt and shoes match. I may or may not wear a tie, since another study showed that 30% of patients believed their physician wore a tie even if they didn't.14 Of course, I'll put on the white coat for the semiannual meeting with the chairman, or if I'm having something messy for lunch and wore a tie that day.

I'll also wear my name badge. It says I'm an attending physician and not a resident. It opens doors around the hospital. Literally. It's got a magnetic stripe.

A 59‐year‐old white female, with a 3‐year history of Port‐A‐Cath (PAC) placement for abdominal mesothelioma, presented with 2 episodes of cardiac palpitations. The onset of palpitations occurred 2 days prior to admission, following 15 minutes of vigorous but failed attempts to access the PAC with normal saline and tissue plasminogen activator at her oncologist's office. Although asymptomatic at the time of manipulation, each episode was triggered by subsequent exertion, lasting for about 1 minute, and not associated with chest pain. Electrocardiogram showed normal sinus rhythm and occasional premature ventricular contractions. A chest x‐ray showed a catheter fragment spanning the right atrium and ventricle (Figure 1). Computed tomography (CT) scan confirmed a 10‐cm dislodged catheter (Figure 2). Following emergent catheter retrieval via right‐sided heart catheterization, the patient's symptoms resolved. At least 42 cases of catheter embolization have been reported in the recent literature.1 Of these cases, only 7% had palpitations. Although rare, catheter fracture should be considered in patients with palpitations and history of indwelling venous catheter.

Figure 1

Figure 2

A 59‐year‐old white female, with a 3‐year history of Port‐A‐Cath (PAC) placement for abdominal mesothelioma, presented with 2 episodes of cardiac palpitations. The onset of palpitations occurred 2 days prior to admission, following 15 minutes of vigorous but failed attempts to access the PAC with normal saline and tissue plasminogen activator at her oncologist's office. Although asymptomatic at the time of manipulation, each episode was triggered by subsequent exertion, lasting for about 1 minute, and not associated with chest pain. Electrocardiogram showed normal sinus rhythm and occasional premature ventricular contractions. A chest x‐ray showed a catheter fragment spanning the right atrium and ventricle (Figure 1). Computed tomography (CT) scan confirmed a 10‐cm dislodged catheter (Figure 2). Following emergent catheter retrieval via right‐sided heart catheterization, the patient's symptoms resolved. At least 42 cases of catheter embolization have been reported in the recent literature.1 Of these cases, only 7% had palpitations. Although rare, catheter fracture should be considered in patients with palpitations and history of indwelling venous catheter.

Figure 1

Figure 2

A 59‐year‐old white female, with a 3‐year history of Port‐A‐Cath (PAC) placement for abdominal mesothelioma, presented with 2 episodes of cardiac palpitations. The onset of palpitations occurred 2 days prior to admission, following 15 minutes of vigorous but failed attempts to access the PAC with normal saline and tissue plasminogen activator at her oncologist's office. Although asymptomatic at the time of manipulation, each episode was triggered by subsequent exertion, lasting for about 1 minute, and not associated with chest pain. Electrocardiogram showed normal sinus rhythm and occasional premature ventricular contractions. A chest x‐ray showed a catheter fragment spanning the right atrium and ventricle (Figure 1). Computed tomography (CT) scan confirmed a 10‐cm dislodged catheter (Figure 2). Following emergent catheter retrieval via right‐sided heart catheterization, the patient's symptoms resolved. At least 42 cases of catheter embolization have been reported in the recent literature.1 Of these cases, only 7% had palpitations. Although rare, catheter fracture should be considered in patients with palpitations and history of indwelling venous catheter.

Figure 1

Figure 2

Focal bacterial infections (FBIs), including otitis media (OM), cellulitis, and lymphadenitis, can occur at any age and are usually treated with oral antibiotics. When patients with focal infections present as a young infant, healthcare providers often worry about the risk of coexisting or concomitant systemic infections (CSIs), often termed serious bacterial infections (SBIs) in the published literature.1, 2 Risk of CSI becomes more worrisome when young infants have fever as part of their presentation, especially within the traditional rule‐out sepsis age range of less than 2 months. Often, these patients are well‐appearing and lack prenatal and neonatal risk factors for systemic infections, but are assumed to be at high risk for CSI based on the presence of focal bacterial infection.1, 3, 4

FBIs have been the subject of multiple studies, especially OM and cellulitis. However, few investigations have looked specifically at infants less than 60 days of age, lending uncertainty to medical decision‐making for both community and emergency physicians. Therefore, no standardized evidence‐based practice exists for treating young infants with FBIs. While some clinicians treat these infections using systemic antibiotics without performing laboratory tests, others opt for a full diagnostic evaluation for CSI; including serum blood counts, blood cultures, lumbar punctures (LPs), and bladder catheterizations. Also, some clinicians opt for treatment with oral antibiotics at home, while others choose intravenous (IV) antibiotics and hospitalization.

These decisions are likely due to studies of febrile infants under 60 days of age who present to an emergency department (ED), appear well, and have no focal source of infection on exam, yet are known to have a risk of systemic or occult bacterial infection of roughly 10%.310 There are no such studies documenting the risk of CSI in well‐appearing, afebrile patients, as fever is regarded as the main risk factor for CSI in this age.

Based on our clinical experience and review of the literature, we felt that afebrile, well‐appearing infants less than 60 days of age with an FBI on exam would have a very low risk of CSI. The primary objectives of this study were to determine the risk of CSI when presented with a well‐appearing infant who has an FBI on exam and to examine that risk in relation to the presence of fever. Other objectives were to describe the clinical presentation of FBIs in well‐appearing infants in this age group and to describe the current management and resource utilization of such infections in the ED.

Patients and Methods

Results

Secondary Study OutcomeCurrent Management of FBI in the ED: Resource Utilization

Febrile patients underwent significantly more diagnostic testing procedures than afebrile infants. Specifically, CBCs, peripheral blood cultures, urine analyses with cultures, LPs, and radiographic imaging were performed more often in infants with fever (Figure 1). Fifty‐seven infants had urine cultures performed: 32 of 158 afebrile infants and 25 of 39 febrile infants. Among these selected infants, again 3 UTIs occurred: 1 of 32 tested (3.1%) in the afebrile group and 2 of 25 tested (8%) in the febrile group. A total of 115 infants had blood cultures performed: 82 of the 158 afebrile infants and 33 of the 39 febrile infants. Among these selected infants, again 1 positive blood culture occurred: 0 of 82 tested (0%) in the afebrile group and 1 of 33 tested (3%) in the febrile group. Fifty‐five infants had LP performed: 35 of 158 afebrile infants and 30 of 39 febrile infants. No case of meningitis occurred in these selected infants. Twenty infants had diagnostic radiographs performed, 10 in the febrile group and 10 in the afebrile group. None of the radiographs showed signs of pneumonia on final radiology attending reading.

Figure 1

Overall, 33 of 39 febrile infants had cultures drawn and/or radiographs performed, with 3 CSIs discovered, and 87 of 158 afebrile infants had cultures drawn and/or radiographs performed, with 1 CSI discovered (Table 3). This means that 77 infants diagnosed with FBIs did not have any diagnostic testing for CSI performed while in the ED. The overall risk of CSI in patients who were tested was 3.3%. Comparing febrile and afebrile patients who had diagnostic workups performed, febrile infants had a trend toward increased risk of CSI (OR, 8.6; 95% CI, 0.8613‐85.8686).

Table 3.Presence of CSI in Patients Who Underwent Diagnostic Workups

	CSI	No CSI	Risk (%)
Abbreviation: CSI, concomitant systemic infection.
Febrile (n = 33)	3	30	9.1
Afebrile (n = 87)	1	86	1.1
Totals (n = 120)	4	116	3.3

No significant differences existed in the use of consultants, use of IV antibiotics, or admission rate. Sixty‐six (42%) of the 158 afebrile infants were admitted. The average length of stay for these infants was 2.59 days (range, 1‐22 days). This included a 22‐day‐old female with mastitis who required multiple surgeries and a protracted hospital course. Sixteen (41%) of the febrile infants were admitted and had an average stay of 2.87 days (range, 1‐6 days).

Discussion

This study is the first to investigate the risk of CSI specifically in well‐appearing infants under 60 days of age presenting with FBI. Inclusion criteria were not limited to 1 specific infection, ie, OM, but included all FBI. This study demonstrated that the risk of CSI in afebrile infants is small (0.6%), which is similar to what has been shown in the OM literature.19, 20 However, the risk of CSI among febrile infants is not negligible (7.7%), and is similar to the risk of SBIs among young infants presenting with a fever of unknown source.57

Limitations

The main limitation of our study was the retrospective design. A research assistant utilizing a computerized database program of ED patients performed the initial query based upon search criteria. A local expert using an established list of International Statistical Classification of Diseases and Related Health Problems (ICD) codes for any and all of the FBIs performed the chart review. Secondary diagnoses may have been omitted as a result of limited physician charting, which could have resulted in missed patients. CCHMC is currently transitioning from paper records to electronic medical records, which may explain why 12 charts were not found, despite exhaustive searches for them. Ultimately, 94% of all the eligible patients were found. Yet, with so few CSI diagnosed, 1 or 2 could conceivably change our results. As noted above, focal infections in infants under 2 months of age seem to be uncommon, not only in the ED setting, but also in a large cohort of primary care patients.35 With only a small number FBIs present over 6 years and so few having CSIs, we were limited to a univariate analysis, which limited our potential results and conclusions. Performing this study prospectively would have addressed these limitations, but would have required years of recruitment or multicenter collaboration.

Another potential limitation was the search strategy to identify eligible infants. Specifically, we did not search the records for infants diagnosed with UTI, bacteremia, or meningitis. Infants with these more serious conditions may have been coded as the primary or only problem, even if other problems such as OM were also present. Therefore, we may have underestimated the occurrence of systemic bacterial complications in a systematic way. This form of spectrum bias was a potential limitation. We approached this clinical question from the eye of the emergency department practitioner and thus used a search strategy based on the discharge diagnosis from the ED. If we were to look back to see if any patients discharged from the hospital with CSI also had FBI, we doubt our retrospective design would have allowed identification of patients with FBIs.

Other limitations may be our definition of CSI and the potential for missed CSIs. We defined meningitis, bacteremia, and UTI as a positive CSF, blood, or urine culture, respectively. Many studies are now defining culture‐negative meningitis or UTI based on WBC findings on a screening cell count or urine microscopy. However, because no patients were pretreated with antibiotics, we felt that a positive culture from a sterile site was a reasonable definition. Also, not all of the enrolled patients received full diagnostic workups to screen for CSI. In the smaller cohort of infants who received diagnostic testing, febrile infants still seemed to be at higher risk for CSI. To capture all possible CSIs, one would have needed to perform blood culture, suprapubic bladder aspiration, or catheterization for urine culture, LP, and chest radiograph on all patients with an FBI. Given the low risk of CSI in the United States, the previous literature's hinting at low risk for CSI in afebrile patients, and the presence of multiple clinical trials defining low risk characteristics for CSI, such a protocol would not receive support as being standard clinical practice and have difficulty being permitted by an institutional review board.

Another limitation of our study was follow‐up. Ideally, every patient would have been contacted to ensure reliable outcomes measurement. Patients may have been seen after their initial evaluation at their primary care provider's office or at another healthcare facility and had more diagnostic studies performed. However, because our institution is the sole admitting pediatric center in the area, particularly in infants, and most CSIs in this age group require admission; we feel that a reasonable degree of reliability for the outcomes of interest was maintained.

Last, we could not establish the rationale of clinical decision making, as our study was retrospective. For example, staff physicians may have foregone diagnostic testing if they had committed to a therapeutic course of antibiotics and felt diagnostic cultures would not change management. Also, we cannot ensure that interpretation of culture results was consistent with national standards. As described previously, 1 afebrile infant in our study potentially had a CSI that was clinically felt to be a contaminant by the inpatient healthcare team. This 11‐day‐old female was admitted with mastitis and had a negative urinalysis, but grew E. coli on urine culture. This was treated as a contaminant by the ward team, despite her age.

Conclusions

CSI is very uncommon in afebrile, well‐appearing infants under 2 months of age with an FBI. However, febrile infants have a greater risk of CSI. UTI is the most common CSI in well‐appearing infants less than 2 months of age with an FBI found on examination. Prospective, multicentered studies need to be performed to determine whether diagnostic evaluation should change the management of well‐appearing infants with an FBI found on examination.

Focal bacterial infections (FBIs), including otitis media (OM), cellulitis, and lymphadenitis, can occur at any age and are usually treated with oral antibiotics. When patients with focal infections present as a young infant, healthcare providers often worry about the risk of coexisting or concomitant systemic infections (CSIs), often termed serious bacterial infections (SBIs) in the published literature.1, 2 Risk of CSI becomes more worrisome when young infants have fever as part of their presentation, especially within the traditional rule‐out sepsis age range of less than 2 months. Often, these patients are well‐appearing and lack prenatal and neonatal risk factors for systemic infections, but are assumed to be at high risk for CSI based on the presence of focal bacterial infection.1, 3, 4

FBIs have been the subject of multiple studies, especially OM and cellulitis. However, few investigations have looked specifically at infants less than 60 days of age, lending uncertainty to medical decision‐making for both community and emergency physicians. Therefore, no standardized evidence‐based practice exists for treating young infants with FBIs. While some clinicians treat these infections using systemic antibiotics without performing laboratory tests, others opt for a full diagnostic evaluation for CSI; including serum blood counts, blood cultures, lumbar punctures (LPs), and bladder catheterizations. Also, some clinicians opt for treatment with oral antibiotics at home, while others choose intravenous (IV) antibiotics and hospitalization.

These decisions are likely due to studies of febrile infants under 60 days of age who present to an emergency department (ED), appear well, and have no focal source of infection on exam, yet are known to have a risk of systemic or occult bacterial infection of roughly 10%.310 There are no such studies documenting the risk of CSI in well‐appearing, afebrile patients, as fever is regarded as the main risk factor for CSI in this age.

Based on our clinical experience and review of the literature, we felt that afebrile, well‐appearing infants less than 60 days of age with an FBI on exam would have a very low risk of CSI. The primary objectives of this study were to determine the risk of CSI when presented with a well‐appearing infant who has an FBI on exam and to examine that risk in relation to the presence of fever. Other objectives were to describe the clinical presentation of FBIs in well‐appearing infants in this age group and to describe the current management and resource utilization of such infections in the ED.

Patients and Methods

Results

Secondary Study OutcomeCurrent Management of FBI in the ED: Resource Utilization

Febrile patients underwent significantly more diagnostic testing procedures than afebrile infants. Specifically, CBCs, peripheral blood cultures, urine analyses with cultures, LPs, and radiographic imaging were performed more often in infants with fever (Figure 1). Fifty‐seven infants had urine cultures performed: 32 of 158 afebrile infants and 25 of 39 febrile infants. Among these selected infants, again 3 UTIs occurred: 1 of 32 tested (3.1%) in the afebrile group and 2 of 25 tested (8%) in the febrile group. A total of 115 infants had blood cultures performed: 82 of the 158 afebrile infants and 33 of the 39 febrile infants. Among these selected infants, again 1 positive blood culture occurred: 0 of 82 tested (0%) in the afebrile group and 1 of 33 tested (3%) in the febrile group. Fifty‐five infants had LP performed: 35 of 158 afebrile infants and 30 of 39 febrile infants. No case of meningitis occurred in these selected infants. Twenty infants had diagnostic radiographs performed, 10 in the febrile group and 10 in the afebrile group. None of the radiographs showed signs of pneumonia on final radiology attending reading.

Figure 1

Overall, 33 of 39 febrile infants had cultures drawn and/or radiographs performed, with 3 CSIs discovered, and 87 of 158 afebrile infants had cultures drawn and/or radiographs performed, with 1 CSI discovered (Table 3). This means that 77 infants diagnosed with FBIs did not have any diagnostic testing for CSI performed while in the ED. The overall risk of CSI in patients who were tested was 3.3%. Comparing febrile and afebrile patients who had diagnostic workups performed, febrile infants had a trend toward increased risk of CSI (OR, 8.6; 95% CI, 0.8613‐85.8686).

Table 3.Presence of CSI in Patients Who Underwent Diagnostic Workups

	CSI	No CSI	Risk (%)
Abbreviation: CSI, concomitant systemic infection.
Febrile (n = 33)	3	30	9.1
Afebrile (n = 87)	1	86	1.1
Totals (n = 120)	4	116	3.3

No significant differences existed in the use of consultants, use of IV antibiotics, or admission rate. Sixty‐six (42%) of the 158 afebrile infants were admitted. The average length of stay for these infants was 2.59 days (range, 1‐22 days). This included a 22‐day‐old female with mastitis who required multiple surgeries and a protracted hospital course. Sixteen (41%) of the febrile infants were admitted and had an average stay of 2.87 days (range, 1‐6 days).

Discussion

This study is the first to investigate the risk of CSI specifically in well‐appearing infants under 60 days of age presenting with FBI. Inclusion criteria were not limited to 1 specific infection, ie, OM, but included all FBI. This study demonstrated that the risk of CSI in afebrile infants is small (0.6%), which is similar to what has been shown in the OM literature.19, 20 However, the risk of CSI among febrile infants is not negligible (7.7%), and is similar to the risk of SBIs among young infants presenting with a fever of unknown source.57

Limitations

The main limitation of our study was the retrospective design. A research assistant utilizing a computerized database program of ED patients performed the initial query based upon search criteria. A local expert using an established list of International Statistical Classification of Diseases and Related Health Problems (ICD) codes for any and all of the FBIs performed the chart review. Secondary diagnoses may have been omitted as a result of limited physician charting, which could have resulted in missed patients. CCHMC is currently transitioning from paper records to electronic medical records, which may explain why 12 charts were not found, despite exhaustive searches for them. Ultimately, 94% of all the eligible patients were found. Yet, with so few CSI diagnosed, 1 or 2 could conceivably change our results. As noted above, focal infections in infants under 2 months of age seem to be uncommon, not only in the ED setting, but also in a large cohort of primary care patients.35 With only a small number FBIs present over 6 years and so few having CSIs, we were limited to a univariate analysis, which limited our potential results and conclusions. Performing this study prospectively would have addressed these limitations, but would have required years of recruitment or multicenter collaboration.

Another potential limitation was the search strategy to identify eligible infants. Specifically, we did not search the records for infants diagnosed with UTI, bacteremia, or meningitis. Infants with these more serious conditions may have been coded as the primary or only problem, even if other problems such as OM were also present. Therefore, we may have underestimated the occurrence of systemic bacterial complications in a systematic way. This form of spectrum bias was a potential limitation. We approached this clinical question from the eye of the emergency department practitioner and thus used a search strategy based on the discharge diagnosis from the ED. If we were to look back to see if any patients discharged from the hospital with CSI also had FBI, we doubt our retrospective design would have allowed identification of patients with FBIs.

Other limitations may be our definition of CSI and the potential for missed CSIs. We defined meningitis, bacteremia, and UTI as a positive CSF, blood, or urine culture, respectively. Many studies are now defining culture‐negative meningitis or UTI based on WBC findings on a screening cell count or urine microscopy. However, because no patients were pretreated with antibiotics, we felt that a positive culture from a sterile site was a reasonable definition. Also, not all of the enrolled patients received full diagnostic workups to screen for CSI. In the smaller cohort of infants who received diagnostic testing, febrile infants still seemed to be at higher risk for CSI. To capture all possible CSIs, one would have needed to perform blood culture, suprapubic bladder aspiration, or catheterization for urine culture, LP, and chest radiograph on all patients with an FBI. Given the low risk of CSI in the United States, the previous literature's hinting at low risk for CSI in afebrile patients, and the presence of multiple clinical trials defining low risk characteristics for CSI, such a protocol would not receive support as being standard clinical practice and have difficulty being permitted by an institutional review board.

Another limitation of our study was follow‐up. Ideally, every patient would have been contacted to ensure reliable outcomes measurement. Patients may have been seen after their initial evaluation at their primary care provider's office or at another healthcare facility and had more diagnostic studies performed. However, because our institution is the sole admitting pediatric center in the area, particularly in infants, and most CSIs in this age group require admission; we feel that a reasonable degree of reliability for the outcomes of interest was maintained.

Last, we could not establish the rationale of clinical decision making, as our study was retrospective. For example, staff physicians may have foregone diagnostic testing if they had committed to a therapeutic course of antibiotics and felt diagnostic cultures would not change management. Also, we cannot ensure that interpretation of culture results was consistent with national standards. As described previously, 1 afebrile infant in our study potentially had a CSI that was clinically felt to be a contaminant by the inpatient healthcare team. This 11‐day‐old female was admitted with mastitis and had a negative urinalysis, but grew E. coli on urine culture. This was treated as a contaminant by the ward team, despite her age.

Conclusions

CSI is very uncommon in afebrile, well‐appearing infants under 2 months of age with an FBI. However, febrile infants have a greater risk of CSI. UTI is the most common CSI in well‐appearing infants less than 2 months of age with an FBI found on examination. Prospective, multicentered studies need to be performed to determine whether diagnostic evaluation should change the management of well‐appearing infants with an FBI found on examination.

Focal bacterial infections (FBIs), including otitis media (OM), cellulitis, and lymphadenitis, can occur at any age and are usually treated with oral antibiotics. When patients with focal infections present as a young infant, healthcare providers often worry about the risk of coexisting or concomitant systemic infections (CSIs), often termed serious bacterial infections (SBIs) in the published literature.1, 2 Risk of CSI becomes more worrisome when young infants have fever as part of their presentation, especially within the traditional rule‐out sepsis age range of less than 2 months. Often, these patients are well‐appearing and lack prenatal and neonatal risk factors for systemic infections, but are assumed to be at high risk for CSI based on the presence of focal bacterial infection.1, 3, 4

FBIs have been the subject of multiple studies, especially OM and cellulitis. However, few investigations have looked specifically at infants less than 60 days of age, lending uncertainty to medical decision‐making for both community and emergency physicians. Therefore, no standardized evidence‐based practice exists for treating young infants with FBIs. While some clinicians treat these infections using systemic antibiotics without performing laboratory tests, others opt for a full diagnostic evaluation for CSI; including serum blood counts, blood cultures, lumbar punctures (LPs), and bladder catheterizations. Also, some clinicians opt for treatment with oral antibiotics at home, while others choose intravenous (IV) antibiotics and hospitalization.

These decisions are likely due to studies of febrile infants under 60 days of age who present to an emergency department (ED), appear well, and have no focal source of infection on exam, yet are known to have a risk of systemic or occult bacterial infection of roughly 10%.310 There are no such studies documenting the risk of CSI in well‐appearing, afebrile patients, as fever is regarded as the main risk factor for CSI in this age.

Based on our clinical experience and review of the literature, we felt that afebrile, well‐appearing infants less than 60 days of age with an FBI on exam would have a very low risk of CSI. The primary objectives of this study were to determine the risk of CSI when presented with a well‐appearing infant who has an FBI on exam and to examine that risk in relation to the presence of fever. Other objectives were to describe the clinical presentation of FBIs in well‐appearing infants in this age group and to describe the current management and resource utilization of such infections in the ED.

Patients and Methods

Results

Secondary Study OutcomeCurrent Management of FBI in the ED: Resource Utilization

Febrile patients underwent significantly more diagnostic testing procedures than afebrile infants. Specifically, CBCs, peripheral blood cultures, urine analyses with cultures, LPs, and radiographic imaging were performed more often in infants with fever (Figure 1). Fifty‐seven infants had urine cultures performed: 32 of 158 afebrile infants and 25 of 39 febrile infants. Among these selected infants, again 3 UTIs occurred: 1 of 32 tested (3.1%) in the afebrile group and 2 of 25 tested (8%) in the febrile group. A total of 115 infants had blood cultures performed: 82 of the 158 afebrile infants and 33 of the 39 febrile infants. Among these selected infants, again 1 positive blood culture occurred: 0 of 82 tested (0%) in the afebrile group and 1 of 33 tested (3%) in the febrile group. Fifty‐five infants had LP performed: 35 of 158 afebrile infants and 30 of 39 febrile infants. No case of meningitis occurred in these selected infants. Twenty infants had diagnostic radiographs performed, 10 in the febrile group and 10 in the afebrile group. None of the radiographs showed signs of pneumonia on final radiology attending reading.

Figure 1

Overall, 33 of 39 febrile infants had cultures drawn and/or radiographs performed, with 3 CSIs discovered, and 87 of 158 afebrile infants had cultures drawn and/or radiographs performed, with 1 CSI discovered (Table 3). This means that 77 infants diagnosed with FBIs did not have any diagnostic testing for CSI performed while in the ED. The overall risk of CSI in patients who were tested was 3.3%. Comparing febrile and afebrile patients who had diagnostic workups performed, febrile infants had a trend toward increased risk of CSI (OR, 8.6; 95% CI, 0.8613‐85.8686).

Table 3.Presence of CSI in Patients Who Underwent Diagnostic Workups

	CSI	No CSI	Risk (%)
Abbreviation: CSI, concomitant systemic infection.
Febrile (n = 33)	3	30	9.1
Afebrile (n = 87)	1	86	1.1
Totals (n = 120)	4	116	3.3

No significant differences existed in the use of consultants, use of IV antibiotics, or admission rate. Sixty‐six (42%) of the 158 afebrile infants were admitted. The average length of stay for these infants was 2.59 days (range, 1‐22 days). This included a 22‐day‐old female with mastitis who required multiple surgeries and a protracted hospital course. Sixteen (41%) of the febrile infants were admitted and had an average stay of 2.87 days (range, 1‐6 days).

Discussion

This study is the first to investigate the risk of CSI specifically in well‐appearing infants under 60 days of age presenting with FBI. Inclusion criteria were not limited to 1 specific infection, ie, OM, but included all FBI. This study demonstrated that the risk of CSI in afebrile infants is small (0.6%), which is similar to what has been shown in the OM literature.19, 20 However, the risk of CSI among febrile infants is not negligible (7.7%), and is similar to the risk of SBIs among young infants presenting with a fever of unknown source.57

Limitations

The main limitation of our study was the retrospective design. A research assistant utilizing a computerized database program of ED patients performed the initial query based upon search criteria. A local expert using an established list of International Statistical Classification of Diseases and Related Health Problems (ICD) codes for any and all of the FBIs performed the chart review. Secondary diagnoses may have been omitted as a result of limited physician charting, which could have resulted in missed patients. CCHMC is currently transitioning from paper records to electronic medical records, which may explain why 12 charts were not found, despite exhaustive searches for them. Ultimately, 94% of all the eligible patients were found. Yet, with so few CSI diagnosed, 1 or 2 could conceivably change our results. As noted above, focal infections in infants under 2 months of age seem to be uncommon, not only in the ED setting, but also in a large cohort of primary care patients.35 With only a small number FBIs present over 6 years and so few having CSIs, we were limited to a univariate analysis, which limited our potential results and conclusions. Performing this study prospectively would have addressed these limitations, but would have required years of recruitment or multicenter collaboration.

Another potential limitation was the search strategy to identify eligible infants. Specifically, we did not search the records for infants diagnosed with UTI, bacteremia, or meningitis. Infants with these more serious conditions may have been coded as the primary or only problem, even if other problems such as OM were also present. Therefore, we may have underestimated the occurrence of systemic bacterial complications in a systematic way. This form of spectrum bias was a potential limitation. We approached this clinical question from the eye of the emergency department practitioner and thus used a search strategy based on the discharge diagnosis from the ED. If we were to look back to see if any patients discharged from the hospital with CSI also had FBI, we doubt our retrospective design would have allowed identification of patients with FBIs.

Other limitations may be our definition of CSI and the potential for missed CSIs. We defined meningitis, bacteremia, and UTI as a positive CSF, blood, or urine culture, respectively. Many studies are now defining culture‐negative meningitis or UTI based on WBC findings on a screening cell count or urine microscopy. However, because no patients were pretreated with antibiotics, we felt that a positive culture from a sterile site was a reasonable definition. Also, not all of the enrolled patients received full diagnostic workups to screen for CSI. In the smaller cohort of infants who received diagnostic testing, febrile infants still seemed to be at higher risk for CSI. To capture all possible CSIs, one would have needed to perform blood culture, suprapubic bladder aspiration, or catheterization for urine culture, LP, and chest radiograph on all patients with an FBI. Given the low risk of CSI in the United States, the previous literature's hinting at low risk for CSI in afebrile patients, and the presence of multiple clinical trials defining low risk characteristics for CSI, such a protocol would not receive support as being standard clinical practice and have difficulty being permitted by an institutional review board.

Another limitation of our study was follow‐up. Ideally, every patient would have been contacted to ensure reliable outcomes measurement. Patients may have been seen after their initial evaluation at their primary care provider's office or at another healthcare facility and had more diagnostic studies performed. However, because our institution is the sole admitting pediatric center in the area, particularly in infants, and most CSIs in this age group require admission; we feel that a reasonable degree of reliability for the outcomes of interest was maintained.

Last, we could not establish the rationale of clinical decision making, as our study was retrospective. For example, staff physicians may have foregone diagnostic testing if they had committed to a therapeutic course of antibiotics and felt diagnostic cultures would not change management. Also, we cannot ensure that interpretation of culture results was consistent with national standards. As described previously, 1 afebrile infant in our study potentially had a CSI that was clinically felt to be a contaminant by the inpatient healthcare team. This 11‐day‐old female was admitted with mastitis and had a negative urinalysis, but grew E. coli on urine culture. This was treated as a contaminant by the ward team, despite her age.

Conclusions

CSI is very uncommon in afebrile, well‐appearing infants under 2 months of age with an FBI. However, febrile infants have a greater risk of CSI. UTI is the most common CSI in well‐appearing infants less than 2 months of age with an FBI found on examination. Prospective, multicentered studies need to be performed to determine whether diagnostic evaluation should change the management of well‐appearing infants with an FBI found on examination.

If you wish to receive credit for this activity, which beginson the next page, please refer to the website: www.blackwellpublishing.com/cme.

Accreditation and Designation Statement

Blackwell Futura Media Services designates this educational activity for a 1 AMA PRA Category 1 Credit. Physicians should only claim credit commensurate with the extent of their participation in the activity.

Blackwell Futura Media Services is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.

Educational Objectives

Continuous participation in the Journal of Hospital Medicine CME program will enable learners to be better able to:

• Interpret clinical guidelines and their applications for higher quality and more efficient care for all hospitalized patients.

• Describe the standard of care for common illnesses and conditions treated in the hospital; such as pneumonia, COPD exacerbation, acute coronary syndrome, HF exacerbation, glycemic control, venous thromboembolic disease, stroke, etc.

• Discuss evidence‐based recommendations involving transitions of care, including the hospital discharge process.

• Gain insights into the roles of hospitalists as medical educators, researchers, medical ethicists, palliative care providers, and hospital‐based geriatricians.

• Incorporate best practices for hospitalist administration, including quality improvement, patient safety, practice management, leadership, and demonstrating hospitalist value.

• Identify evidence‐based best practices and trends for both adult and pediatric hospital medicine.

Instructions on Receiving Credit

For information on applicability and acceptance of continuing medical education credit for this activity, please consult your professional licensing board.

This activity is designed to be completed within the time designated on the title page; physicians should claim only those credits that reflect the time actually spent in the activity. To successfully earn credit, participants must complete the activity during the valid credit period that is noted on the title page.

Follow these steps to earn credit:

• Log on to www.blackwellpublishing.com/cme.

• Read the target audience, learning objectives, and author disclosures.

• Read the article in print or online format.

• Reflect on the article.

• Access the CME Exam, and choose the best answer to each question.

• Complete the required evaluation component of the activity.

If you wish to receive credit for this activity, which beginson the next page, please refer to the website: www.blackwellpublishing.com/cme.

Accreditation and Designation Statement

Blackwell Futura Media Services designates this educational activity for a 1 AMA PRA Category 1 Credit. Physicians should only claim credit commensurate with the extent of their participation in the activity.

Blackwell Futura Media Services is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.

Educational Objectives

Continuous participation in the Journal of Hospital Medicine CME program will enable learners to be better able to:

• Interpret clinical guidelines and their applications for higher quality and more efficient care for all hospitalized patients.

• Describe the standard of care for common illnesses and conditions treated in the hospital; such as pneumonia, COPD exacerbation, acute coronary syndrome, HF exacerbation, glycemic control, venous thromboembolic disease, stroke, etc.

• Discuss evidence‐based recommendations involving transitions of care, including the hospital discharge process.

• Gain insights into the roles of hospitalists as medical educators, researchers, medical ethicists, palliative care providers, and hospital‐based geriatricians.

• Incorporate best practices for hospitalist administration, including quality improvement, patient safety, practice management, leadership, and demonstrating hospitalist value.

• Identify evidence‐based best practices and trends for both adult and pediatric hospital medicine.

Instructions on Receiving Credit

For information on applicability and acceptance of continuing medical education credit for this activity, please consult your professional licensing board.

This activity is designed to be completed within the time designated on the title page; physicians should claim only those credits that reflect the time actually spent in the activity. To successfully earn credit, participants must complete the activity during the valid credit period that is noted on the title page.

Follow these steps to earn credit:

• Log on to www.blackwellpublishing.com/cme.

• Read the target audience, learning objectives, and author disclosures.

• Read the article in print or online format.

• Reflect on the article.

• Access the CME Exam, and choose the best answer to each question.

• Complete the required evaluation component of the activity.

If you wish to receive credit for this activity, which beginson the next page, please refer to the website: www.blackwellpublishing.com/cme.

Accreditation and Designation Statement

Blackwell Futura Media Services designates this educational activity for a 1 AMA PRA Category 1 Credit. Physicians should only claim credit commensurate with the extent of their participation in the activity.

Blackwell Futura Media Services is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.

Educational Objectives

Continuous participation in the Journal of Hospital Medicine CME program will enable learners to be better able to:

• Interpret clinical guidelines and their applications for higher quality and more efficient care for all hospitalized patients.

• Describe the standard of care for common illnesses and conditions treated in the hospital; such as pneumonia, COPD exacerbation, acute coronary syndrome, HF exacerbation, glycemic control, venous thromboembolic disease, stroke, etc.

• Discuss evidence‐based recommendations involving transitions of care, including the hospital discharge process.

• Gain insights into the roles of hospitalists as medical educators, researchers, medical ethicists, palliative care providers, and hospital‐based geriatricians.

• Incorporate best practices for hospitalist administration, including quality improvement, patient safety, practice management, leadership, and demonstrating hospitalist value.

• Identify evidence‐based best practices and trends for both adult and pediatric hospital medicine.

Instructions on Receiving Credit

For information on applicability and acceptance of continuing medical education credit for this activity, please consult your professional licensing board.

This activity is designed to be completed within the time designated on the title page; physicians should claim only those credits that reflect the time actually spent in the activity. To successfully earn credit, participants must complete the activity during the valid credit period that is noted on the title page.

Follow these steps to earn credit:

• Log on to www.blackwellpublishing.com/cme.

• Read the target audience, learning objectives, and author disclosures.

• Read the article in print or online format.

• Reflect on the article.

• Access the CME Exam, and choose the best answer to each question.

• Complete the required evaluation component of the activity.

Historically, the milk‐alkali syndrome developed as an adverse reaction to the Sippy regimen of frequent feedings of milk, cream, and alkaline powders as treatment for peptic ulcer disease.1 The classic description includes hypercalcemia, metabolic alkalosis, and renal failure. This syndrome seemingly disappeared when modern acid suppression therapies such as histamine‐2 blockers and proton pump inhibitors improved dyspepsia treatment. Over the past 20 years, milk‐alkali syndrome has had a resurgence, as consumption of supplements containing calcium has increased.2 Calcium carbonate supplements are a popular over‐the‐counter treatment for osteoporosis, dyspepsia, hypocalcemia, and hyperphosphatemia; these supplements provide both the calcium and alkali required for the development of milk‐alkali syndrome.

A 46‐year‐old man presented to the emergency department after his physician ordered outpatient laboratory tests to evaluate his fatigue. The patient was found to have acute renal failure and hypercalcemia. His serum creatinine was 3.6 mg/dL, increased from his baseline of 1.1 mg/dL several months prior, and his serum calcium was 14.9 mg/dL. Ten days prior to admission he developed increasing fatigue, decreased appetite, and decreased urine output, which he attributed to recent manual labor during summer. He reported taking an occasional calcium carbonate (Tums) for dyspepsia. He did not report pain or other complaints.

His medical history included hypertension and hyperlipidemia. He had a colonoscopy 1 year prior to presentation that was significant for a high‐grade dysplastic polyp and was currently due for repeat colonoscopy. His medications included clonidine, lisinopril, and aspirin. He had no recent medication changes. He had a 30 pack/year history of cigarette smoking and drank occasionally.

On physical exam, his temperature was 99.8F, blood pressure 97/48 mmHg, heart rate 89 beats per minute, respirations 20 breaths per minute, with a room air saturation of 97%. He had dry mucus membranes and the remainder of the physical exam was unremarkable.

In the emergency department laboratory testing revealed a creatinine of 4.6 mg/dL, serum total calcium of 15.9 mg/dL, serum bicarbonate level of 26 mmol/L, phosphate of 3.9 mg/dL, albumin of 4.4 gm/dL, and alkaline phosphatase of 92 IU/L. The urine specific gravity was 1.019 gm/mL (see Table 1 for the patient's complete admission laboratory values).

His intact parathyroid (PTH) hormone was 18.8 pg/mL (normal, 15‐65). PTH hormone‐related peptide (PTHrP) was 2.5 pmol/L. After reviewing these laboratory test results, we proceeded with further questioning, during which he admitted to taking approximately 15 to 20 Tums (>7.5 gm of calcium carbonate) daily for dyspepsia rather than the occasional Tums he had originally reported. Over the next 3 days, his calcium decreased to 8.4 mg/dL and his creatinine decreased to 1.6 mg/dL with intravenous hydration. His fatigue improved. His 25‐hydroxy vitamin D (25‐OH‐Vitamin D) level was 23 ng/mL (normal, 16‐74 ng/mL).

At his 1 week follow‐up, his calcium was 8.1 mg/dL, and his creatinine had returned to normal at 0.9 mg/dL. His intact PTH level was elevated at 240 pg/mL.

Discussion

Milk‐alkali syndrome is now believed to be the third most common reason for hypercalcemia hospital admission.2, 3 Malignancy and primary hyperparathyroidism are the only 2 causes of hypercalcemia more common than milk‐alkali syndrome in hospitalized patients; these must be excluded before making a definitive diagnosis of milk‐alkali syndrome. The differential diagnosis for hypercalcemia also includes other less common etiologies such as medications (hydrochlorothiazide and lithium), as well as familial hypocalciuric hypercalcemia, hyperthyroidism, Addison's disease, acromegaly, tertiary hyperparathyroidism, and vitamin D intoxication. Physicians often discover hypercalcemia incidentally on routine laboratory tests, and diagnostic workup should include a thorough history and physical examination, as well as further laboratory evaluation.

The diagnosis of milk‐alkali syndrome requires a history of increased calcium and alkali intake, but is otherwise a diagnosis of exclusion. Given the increasing consumption of nonprescribed calcium supplements, one should have a high index of suspicion for the diagnosis of milk‐alkali syndrome, as patients may not consider calcium carbonate to be hazardous or even a medication and thus may not report calcium carbonate consumption. Patients often view calcium carbonate as a benign treatment for dyspepsia. Its over‐the‐counter availability and economical price make it a common self‐treatment for minor dyspepsia or as prevention of osteoporosis. Calcium supplementation is increasingly added to many products, making it easy for patients to consume large quantities of calcium unknowingly. Of note, without the absorbable alkali supplied by the carbonate in calcium carbonate (Tums), milk‐alkali syndrome does not occur. The amount of calcium carbonate necessary to cause milk‐alkali syndrome is not well known, though it is speculated to be as little as 5 to 10 g of calcium in the form of calcium carbonate, especially in those with other risk factors for hypercalcemia such as chronic renal insufficiency or vomiting.2 Workup of hypercalcemia should entail careful questioning about medications, as well as over‐the‐counter supplements, vitamins, and foods.

Manifestations of the milk‐alkali syndrome include renal failure, metabolic alkalosis, and volume contraction. Normally, the kidneys prevent hypercalcemia by excretion of excess calcium. Hypercalcemia can cause tubular damage and vasoconstriction of the renal afferent arteriole leading to acute renal failure.2, 4 Hypercalcemia can also cause nephrogenic diabetes insipidus, causing impaired renal concentrating ability, leading to increased sodium excretion and volume contraction.2 In addition, alkalosis further impairs calciuresis.2 Laboratory values usually reveal suppressed PTH and vitamin D levels due to hypercalcemia caused by exogenous intake of calcium.5 Hypercalcemia causes suppression of PTH, which can lead to hyperphosphatemia, as well as decreased conversion of vitamin D to the active 1,25‐dihyroxyvitamin‐D form.

The management of hypercalcemia due to milk‐alkali syndrome is supportive and includes saline hydration as well as withholding calcium carbonate. Management of hypercalcemia due to malignancy and hyperparathyroidism includes bisphosphonates with the addition of calcitonin if symptoms are severe.6, 7 There is no evidence that supports the use of bisphosphonates in the treatment of milk‐alkali syndrome. Loop diuretics are sometimes used to promote calciuresis, though evidence is lacking to support this, and it may worsen renal failure.6

In this case, a middle‐aged man took greater than the recommended dose of calcium carbonate for dyspepsia, which led to the development of acute renal failure and hypercalcemia. At first, the patient did not provide an accurate history of the extent of his calcium carbonate ingestion, leading us to focus on hyperparathyroidism or malignancy. With aggressive hydration and cessation of calcium carbonate, his renal function and serum calcium returned to baseline. Because we initially assumed occult malignancy as the most likely diagnosis, we gave the patient pamidronate. The patient did not have a significant alkalemia (serum bicarbonate level was normal). This was thought to be due to the patient's degree of renal failure causing a concomitant metabolic acidosis. The patient's follow‐up elevated PTH level may be explained by bisphosphonate administration or underlying primary hyperparathyroidism. Of note, decreasing calcium levels have also been speculated to be a cause of high PTH levels.8

In conclusion, physicians should have a high index of suspicion for milk‐alkali syndrome in patients with hypercalcemia. Calcium carbonate is responsible for most cases of milk‐alkali syndrome, and clinicians should inquire about the use of this supplement in all patients with hypercalcemia. Milk‐alkali syndrome is no longer a merely a historical curiosity; it is currently the third most common cause of hospital admissions for hypercalcemia.

Historically, the milk‐alkali syndrome developed as an adverse reaction to the Sippy regimen of frequent feedings of milk, cream, and alkaline powders as treatment for peptic ulcer disease.1 The classic description includes hypercalcemia, metabolic alkalosis, and renal failure. This syndrome seemingly disappeared when modern acid suppression therapies such as histamine‐2 blockers and proton pump inhibitors improved dyspepsia treatment. Over the past 20 years, milk‐alkali syndrome has had a resurgence, as consumption of supplements containing calcium has increased.2 Calcium carbonate supplements are a popular over‐the‐counter treatment for osteoporosis, dyspepsia, hypocalcemia, and hyperphosphatemia; these supplements provide both the calcium and alkali required for the development of milk‐alkali syndrome.

A 46‐year‐old man presented to the emergency department after his physician ordered outpatient laboratory tests to evaluate his fatigue. The patient was found to have acute renal failure and hypercalcemia. His serum creatinine was 3.6 mg/dL, increased from his baseline of 1.1 mg/dL several months prior, and his serum calcium was 14.9 mg/dL. Ten days prior to admission he developed increasing fatigue, decreased appetite, and decreased urine output, which he attributed to recent manual labor during summer. He reported taking an occasional calcium carbonate (Tums) for dyspepsia. He did not report pain or other complaints.

His medical history included hypertension and hyperlipidemia. He had a colonoscopy 1 year prior to presentation that was significant for a high‐grade dysplastic polyp and was currently due for repeat colonoscopy. His medications included clonidine, lisinopril, and aspirin. He had no recent medication changes. He had a 30 pack/year history of cigarette smoking and drank occasionally.

On physical exam, his temperature was 99.8F, blood pressure 97/48 mmHg, heart rate 89 beats per minute, respirations 20 breaths per minute, with a room air saturation of 97%. He had dry mucus membranes and the remainder of the physical exam was unremarkable.

In the emergency department laboratory testing revealed a creatinine of 4.6 mg/dL, serum total calcium of 15.9 mg/dL, serum bicarbonate level of 26 mmol/L, phosphate of 3.9 mg/dL, albumin of 4.4 gm/dL, and alkaline phosphatase of 92 IU/L. The urine specific gravity was 1.019 gm/mL (see Table 1 for the patient's complete admission laboratory values).

His intact parathyroid (PTH) hormone was 18.8 pg/mL (normal, 15‐65). PTH hormone‐related peptide (PTHrP) was 2.5 pmol/L. After reviewing these laboratory test results, we proceeded with further questioning, during which he admitted to taking approximately 15 to 20 Tums (>7.5 gm of calcium carbonate) daily for dyspepsia rather than the occasional Tums he had originally reported. Over the next 3 days, his calcium decreased to 8.4 mg/dL and his creatinine decreased to 1.6 mg/dL with intravenous hydration. His fatigue improved. His 25‐hydroxy vitamin D (25‐OH‐Vitamin D) level was 23 ng/mL (normal, 16‐74 ng/mL).

At his 1 week follow‐up, his calcium was 8.1 mg/dL, and his creatinine had returned to normal at 0.9 mg/dL. His intact PTH level was elevated at 240 pg/mL.

Discussion

Milk‐alkali syndrome is now believed to be the third most common reason for hypercalcemia hospital admission.2, 3 Malignancy and primary hyperparathyroidism are the only 2 causes of hypercalcemia more common than milk‐alkali syndrome in hospitalized patients; these must be excluded before making a definitive diagnosis of milk‐alkali syndrome. The differential diagnosis for hypercalcemia also includes other less common etiologies such as medications (hydrochlorothiazide and lithium), as well as familial hypocalciuric hypercalcemia, hyperthyroidism, Addison's disease, acromegaly, tertiary hyperparathyroidism, and vitamin D intoxication. Physicians often discover hypercalcemia incidentally on routine laboratory tests, and diagnostic workup should include a thorough history and physical examination, as well as further laboratory evaluation.

The diagnosis of milk‐alkali syndrome requires a history of increased calcium and alkali intake, but is otherwise a diagnosis of exclusion. Given the increasing consumption of nonprescribed calcium supplements, one should have a high index of suspicion for the diagnosis of milk‐alkali syndrome, as patients may not consider calcium carbonate to be hazardous or even a medication and thus may not report calcium carbonate consumption. Patients often view calcium carbonate as a benign treatment for dyspepsia. Its over‐the‐counter availability and economical price make it a common self‐treatment for minor dyspepsia or as prevention of osteoporosis. Calcium supplementation is increasingly added to many products, making it easy for patients to consume large quantities of calcium unknowingly. Of note, without the absorbable alkali supplied by the carbonate in calcium carbonate (Tums), milk‐alkali syndrome does not occur. The amount of calcium carbonate necessary to cause milk‐alkali syndrome is not well known, though it is speculated to be as little as 5 to 10 g of calcium in the form of calcium carbonate, especially in those with other risk factors for hypercalcemia such as chronic renal insufficiency or vomiting.2 Workup of hypercalcemia should entail careful questioning about medications, as well as over‐the‐counter supplements, vitamins, and foods.

Manifestations of the milk‐alkali syndrome include renal failure, metabolic alkalosis, and volume contraction. Normally, the kidneys prevent hypercalcemia by excretion of excess calcium. Hypercalcemia can cause tubular damage and vasoconstriction of the renal afferent arteriole leading to acute renal failure.2, 4 Hypercalcemia can also cause nephrogenic diabetes insipidus, causing impaired renal concentrating ability, leading to increased sodium excretion and volume contraction.2 In addition, alkalosis further impairs calciuresis.2 Laboratory values usually reveal suppressed PTH and vitamin D levels due to hypercalcemia caused by exogenous intake of calcium.5 Hypercalcemia causes suppression of PTH, which can lead to hyperphosphatemia, as well as decreased conversion of vitamin D to the active 1,25‐dihyroxyvitamin‐D form.

The management of hypercalcemia due to milk‐alkali syndrome is supportive and includes saline hydration as well as withholding calcium carbonate. Management of hypercalcemia due to malignancy and hyperparathyroidism includes bisphosphonates with the addition of calcitonin if symptoms are severe.6, 7 There is no evidence that supports the use of bisphosphonates in the treatment of milk‐alkali syndrome. Loop diuretics are sometimes used to promote calciuresis, though evidence is lacking to support this, and it may worsen renal failure.6

In this case, a middle‐aged man took greater than the recommended dose of calcium carbonate for dyspepsia, which led to the development of acute renal failure and hypercalcemia. At first, the patient did not provide an accurate history of the extent of his calcium carbonate ingestion, leading us to focus on hyperparathyroidism or malignancy. With aggressive hydration and cessation of calcium carbonate, his renal function and serum calcium returned to baseline. Because we initially assumed occult malignancy as the most likely diagnosis, we gave the patient pamidronate. The patient did not have a significant alkalemia (serum bicarbonate level was normal). This was thought to be due to the patient's degree of renal failure causing a concomitant metabolic acidosis. The patient's follow‐up elevated PTH level may be explained by bisphosphonate administration or underlying primary hyperparathyroidism. Of note, decreasing calcium levels have also been speculated to be a cause of high PTH levels.8

In conclusion, physicians should have a high index of suspicion for milk‐alkali syndrome in patients with hypercalcemia. Calcium carbonate is responsible for most cases of milk‐alkali syndrome, and clinicians should inquire about the use of this supplement in all patients with hypercalcemia. Milk‐alkali syndrome is no longer a merely a historical curiosity; it is currently the third most common cause of hospital admissions for hypercalcemia.

Historically, the milk‐alkali syndrome developed as an adverse reaction to the Sippy regimen of frequent feedings of milk, cream, and alkaline powders as treatment for peptic ulcer disease.1 The classic description includes hypercalcemia, metabolic alkalosis, and renal failure. This syndrome seemingly disappeared when modern acid suppression therapies such as histamine‐2 blockers and proton pump inhibitors improved dyspepsia treatment. Over the past 20 years, milk‐alkali syndrome has had a resurgence, as consumption of supplements containing calcium has increased.2 Calcium carbonate supplements are a popular over‐the‐counter treatment for osteoporosis, dyspepsia, hypocalcemia, and hyperphosphatemia; these supplements provide both the calcium and alkali required for the development of milk‐alkali syndrome.

A 46‐year‐old man presented to the emergency department after his physician ordered outpatient laboratory tests to evaluate his fatigue. The patient was found to have acute renal failure and hypercalcemia. His serum creatinine was 3.6 mg/dL, increased from his baseline of 1.1 mg/dL several months prior, and his serum calcium was 14.9 mg/dL. Ten days prior to admission he developed increasing fatigue, decreased appetite, and decreased urine output, which he attributed to recent manual labor during summer. He reported taking an occasional calcium carbonate (Tums) for dyspepsia. He did not report pain or other complaints.

His medical history included hypertension and hyperlipidemia. He had a colonoscopy 1 year prior to presentation that was significant for a high‐grade dysplastic polyp and was currently due for repeat colonoscopy. His medications included clonidine, lisinopril, and aspirin. He had no recent medication changes. He had a 30 pack/year history of cigarette smoking and drank occasionally.

On physical exam, his temperature was 99.8F, blood pressure 97/48 mmHg, heart rate 89 beats per minute, respirations 20 breaths per minute, with a room air saturation of 97%. He had dry mucus membranes and the remainder of the physical exam was unremarkable.

In the emergency department laboratory testing revealed a creatinine of 4.6 mg/dL, serum total calcium of 15.9 mg/dL, serum bicarbonate level of 26 mmol/L, phosphate of 3.9 mg/dL, albumin of 4.4 gm/dL, and alkaline phosphatase of 92 IU/L. The urine specific gravity was 1.019 gm/mL (see Table 1 for the patient's complete admission laboratory values).

His intact parathyroid (PTH) hormone was 18.8 pg/mL (normal, 15‐65). PTH hormone‐related peptide (PTHrP) was 2.5 pmol/L. After reviewing these laboratory test results, we proceeded with further questioning, during which he admitted to taking approximately 15 to 20 Tums (>7.5 gm of calcium carbonate) daily for dyspepsia rather than the occasional Tums he had originally reported. Over the next 3 days, his calcium decreased to 8.4 mg/dL and his creatinine decreased to 1.6 mg/dL with intravenous hydration. His fatigue improved. His 25‐hydroxy vitamin D (25‐OH‐Vitamin D) level was 23 ng/mL (normal, 16‐74 ng/mL).

At his 1 week follow‐up, his calcium was 8.1 mg/dL, and his creatinine had returned to normal at 0.9 mg/dL. His intact PTH level was elevated at 240 pg/mL.

Discussion

Milk‐alkali syndrome is now believed to be the third most common reason for hypercalcemia hospital admission.2, 3 Malignancy and primary hyperparathyroidism are the only 2 causes of hypercalcemia more common than milk‐alkali syndrome in hospitalized patients; these must be excluded before making a definitive diagnosis of milk‐alkali syndrome. The differential diagnosis for hypercalcemia also includes other less common etiologies such as medications (hydrochlorothiazide and lithium), as well as familial hypocalciuric hypercalcemia, hyperthyroidism, Addison's disease, acromegaly, tertiary hyperparathyroidism, and vitamin D intoxication. Physicians often discover hypercalcemia incidentally on routine laboratory tests, and diagnostic workup should include a thorough history and physical examination, as well as further laboratory evaluation.

The diagnosis of milk‐alkali syndrome requires a history of increased calcium and alkali intake, but is otherwise a diagnosis of exclusion. Given the increasing consumption of nonprescribed calcium supplements, one should have a high index of suspicion for the diagnosis of milk‐alkali syndrome, as patients may not consider calcium carbonate to be hazardous or even a medication and thus may not report calcium carbonate consumption. Patients often view calcium carbonate as a benign treatment for dyspepsia. Its over‐the‐counter availability and economical price make it a common self‐treatment for minor dyspepsia or as prevention of osteoporosis. Calcium supplementation is increasingly added to many products, making it easy for patients to consume large quantities of calcium unknowingly. Of note, without the absorbable alkali supplied by the carbonate in calcium carbonate (Tums), milk‐alkali syndrome does not occur. The amount of calcium carbonate necessary to cause milk‐alkali syndrome is not well known, though it is speculated to be as little as 5 to 10 g of calcium in the form of calcium carbonate, especially in those with other risk factors for hypercalcemia such as chronic renal insufficiency or vomiting.2 Workup of hypercalcemia should entail careful questioning about medications, as well as over‐the‐counter supplements, vitamins, and foods.

Manifestations of the milk‐alkali syndrome include renal failure, metabolic alkalosis, and volume contraction. Normally, the kidneys prevent hypercalcemia by excretion of excess calcium. Hypercalcemia can cause tubular damage and vasoconstriction of the renal afferent arteriole leading to acute renal failure.2, 4 Hypercalcemia can also cause nephrogenic diabetes insipidus, causing impaired renal concentrating ability, leading to increased sodium excretion and volume contraction.2 In addition, alkalosis further impairs calciuresis.2 Laboratory values usually reveal suppressed PTH and vitamin D levels due to hypercalcemia caused by exogenous intake of calcium.5 Hypercalcemia causes suppression of PTH, which can lead to hyperphosphatemia, as well as decreased conversion of vitamin D to the active 1,25‐dihyroxyvitamin‐D form.

The management of hypercalcemia due to milk‐alkali syndrome is supportive and includes saline hydration as well as withholding calcium carbonate. Management of hypercalcemia due to malignancy and hyperparathyroidism includes bisphosphonates with the addition of calcitonin if symptoms are severe.6, 7 There is no evidence that supports the use of bisphosphonates in the treatment of milk‐alkali syndrome. Loop diuretics are sometimes used to promote calciuresis, though evidence is lacking to support this, and it may worsen renal failure.6

In this case, a middle‐aged man took greater than the recommended dose of calcium carbonate for dyspepsia, which led to the development of acute renal failure and hypercalcemia. At first, the patient did not provide an accurate history of the extent of his calcium carbonate ingestion, leading us to focus on hyperparathyroidism or malignancy. With aggressive hydration and cessation of calcium carbonate, his renal function and serum calcium returned to baseline. Because we initially assumed occult malignancy as the most likely diagnosis, we gave the patient pamidronate. The patient did not have a significant alkalemia (serum bicarbonate level was normal). This was thought to be due to the patient's degree of renal failure causing a concomitant metabolic acidosis. The patient's follow‐up elevated PTH level may be explained by bisphosphonate administration or underlying primary hyperparathyroidism. Of note, decreasing calcium levels have also been speculated to be a cause of high PTH levels.8

In conclusion, physicians should have a high index of suspicion for milk‐alkali syndrome in patients with hypercalcemia. Calcium carbonate is responsible for most cases of milk‐alkali syndrome, and clinicians should inquire about the use of this supplement in all patients with hypercalcemia. Milk‐alkali syndrome is no longer a merely a historical curiosity; it is currently the third most common cause of hospital admissions for hypercalcemia.