Faculty Bibliography

Background: Type 2 myocardial infarction (MI) is defined as myocardial necrosis due to an imbalance in supply and demand. Clinical characteristics predisposing to Type 2 MI and medical therapy use remain uncertain. Methods: Charts of patients admitted to NYU Langone Medical Center in 2013 with a diagnosis of secondary myocardial ischemia (ICD9 411.89) or non-primary diagnosis of non-ST-elevation MI (ICD9 410.71) were retrospectively reviewed, following hospital standardization of acute MI ICD9 coding. Cases with suspected/confirmed Type 1 MI or without rise and fall of troponin were excluded. Results: Charts of 104 inpatients with Type 2 MI have been reviewed to date, with evaluation of additional cases ongoing. Conditions associated with and possibly provoking Type 2 MI included sepsis (defined as SIRS with an infectious source, 39%), surgery (37%), anemia (Hgb < 7 mg/dL), bleeding, or transfusion >1 PRBCs (34%), respiratory failure (28%), tachyarrhythmia (21%), hypotension (17%), hypertensive crisis (8%), and bradycardia (2%). Multiple provoking conditions were identified in 74% of cases. See Table for risk factors, procedure use and results and in-hospital outcomes. Inpatient mortality was 3%. Among 92 patients discharged alive and not to hospice, medical regimens included aspirin (65%), statin (66%), ACE inhibition (ACEi) (38%), and beta blocker (65%). Patients with a peak troponin >1.0 ng/mL (35%) were more likely to be discharged on aspirin (p=0.004) and beta-blocker (p=0.027), but not statin or ACEi. Conclusions: Type 2 MI occurs most frequently in the setting of sepsis, surgery, and/or anemia in patients with cardiovascular risk factors, but mechanisms of Type 2 MI remain poorly understood. Rates of outpatient antiplatelet and statin prescription are low at hospital discharge, reflecting physician uncertainty about the role of secondary prevention. Further research into mechanisms is needed to inform management of patients with Type 2 MI

BACKGROUND: Debate exists regarding the efficacy of a-blockers in myocardial infarction and their required duration of usage in contemporary practice. METHODS: We conducted a MEDLINE/EMBASE/CENTRAL search for randomized trials evaluating a-blockers in myocardial infarction enrolling at least 100 patients. The primary outcome was all-cause mortality. Analysis was performed stratifying trials into reperfusion era (>50% undergoing reperfusion and/or receiving aspirin/statin) or pre-reperfusion era trials. RESULTS: Sixty trials with 102003 patients satisfied the inclusion criteria. In the acute myocardial infarction trials, a significant interaction (Pinteraction=0.02) was noted such that a-blockers reduced mortality in the pre-reperfusion[Incident Rate Ratio (IRR)=0.86, 95% CI 0.79-0.94] but not in the reperfusion era(IRR=0.98, 95% CI 0.92-1.05). In the pre-reperfusion era, a-blockers reduced cardiovascular mortality(IRR=0.87, 95% CI 0.78-0.98), myocardial infarction(IRR=0.78, 95% CI 0.62-0.97), and angina(IRR=0.88, 95% CI 0.82-0.95) with no difference for other outcomes. In the reperfusion era, a-blockers reduced myocardial infarction(IRR=0.72, 95% CI 0.62-0.83) (NNTB=209) and angina(IRR=0.80, 95% CI 0.65-0.98) (NNTB=26) at the expense of increase in heart failure(IRR=1.10, 95% CI 1.05-1.16) (NNTH=79), cardiogenic shock(IRR=1.29, 95% CI 1.18-1.41) (NNTH=90) and drug discontinuation(IRR=1.64, 95% CI 1.55-1.73) with no benefit for other outcomes. Benefits for recurrent myocardial infarction and angina in the reperfusion era appeared to be short-term (30-days). CONCLUSIONS: In contemporary practice of treatment of myocardial infarction, a-blockers have no mortality benefit but reduce recurrent myocardial infarction and angina (short-term) at the expense of increase in heart failure, cardiogenic shock and drug discontinuation. The guidelines should reconsider the strength of recommendations for a-blockers post myocardial infarction.

OBJECTIVE: The purpose of this study was to evaluate the association of physician continuity of care with length of stay, likelihood of weekend discharge, in-hospital mortality and 30-day readmission. DESIGN: A cohort study of hospitalized medical patients. The primary exposure was the weekend usual provider continuity (UPC) over the initial weekend of care. This metric was adapted from an outpatient continuity of care index. Regression models were developed to determine the association between UPC and outcomes. SETTING: An academic medical center. MAIN OUTCOME MEASURE: Length of stay which was calculated as the number of days from the first Saturday of the hospitalization to the day of discharge. RESULTS: Of the 3391 patients included in this study, the prevalence of low, moderate and high UPC for the initial weekend of hospitalization was 58.7, 22.3 and 19.1%, respectively. When compared with low continuity of care, both moderate and high continuity of care were associated with reduced length of stay, with adjusted rate ratios of 0.92 (95% CI 0.86-1.00) and 0.64 (95% CI 0.53-0.76), respectively. High continuity of care was associated with likelihood of weekend discharge (adjusted odds ratio 2.84, 95% CI 2.11-3.83) but was not significantly associated with mortality (adjusted odds ratio 0.72, 95% CI 0.29-1.80) or readmission (adjusted odds ratio 0.88, 95% CI 0.68-1.14) when compared with low continuity of care. CONCLUSIONS: Increased weekend continuity of care is associated with reduced length of stay. Improvement in weekend cross-coverage and patient handoffs may be useful to improve clinical outcomes.

OBJECTIVES: Emergency physician threshold to test for acute coronary syndrome (ACS) is directly related to ACS diagnosis rate and inversely related to ACS missed diagnosis rate. Feedback to emergency physicians of information on their prior patients whose ACS diagnosis was not identified may improve physician diagnostic performance. METHODS: A critical pathway for evaluation of patients for ACS was modified to include feedback to physicians on their cases who had a return visit and did not have their ACS diagnosis identified at their prior emergency department visit. Feedback included case-specific details, discussion of the case at the monthly Morbidity and Mortality conference, and a yearly a report to each physician comparing their performance to their peers (ACS evaluation rate, ACS diagnosis rate, and ACS missed diagnosis rate). Cases were identified, and physician-specific performance was calculated from a computerized encounter database at 2 community teaching hospitals. RESULTS: During the study period, 29 emergency physicians evaluated 295,758 patients and identified 6472 ACS cases. During the study, the yearly ACS evaluation rate for individual physician ranged from 19% to 70% (average 40.3%; 95% confidence interval [CI], 39.5%-41.1%), the yearly ACS diagnosis rate for individual physician ranged from 1.1% to 4.2% (average 1.7%; 95% CI, 1.65%-1.75%), and the yearly missed ACS diagnosis rate for individual physician ranged from 0% to 17% (average 2.8%; 95% CI, 2.3%-3.3%). Individual physician ACS evaluation rate was directly related to physician ACS diagnosis rate (r 0.76, P = 0.00012) and was inversely related to that physician missed ACS rate (r 0.45, P = 0.001). During the study, implementation of the critical pathway increased the ACS evaluation rate from 30% to 48% and decreased the ACS missed diagnosis rate from 1.5% to 0.3%. CONCLUSIONS: Emergency physicians with lower threshold for ACS evaluation more frequently diagnose patients with ACS and less frequently miss the diagnosis of ACS. Feedback to emergency physicians of information on their patient's return visits and their own diagnostic performance may improve outcome for patients with ACS.

BACKGROUND: The 2013 American College of Cardiology Foundation/American Heart Association ST-segment elevation myocardial infarction (STEMI) guidelines have shifted focus from door-to-balloon (D2B) time to the time from first medical contact to device activation (contact-to-device time [C2D] ). HYPOTHESIS: This study investigates the impact of prehospital wireless electrocardiogram transmission (PHT) on reperfusion times to assess the impact of the new guidelines. METHODS: From January 2009 to December 2012, data were collected on STEMI patients who received percutaneous coronary interventions; 245 patients were included for analysis. The primary outcome was median C2D time in the PHT group and the secondary outcome was D2B time. RESULTS: Prehospital wireless electrocardiogram transmission was associated with reduced C2D times vs no PHT: 80 minutes (interquartile range [IQR], 64-94) vs 96 minutes (IQR, 79-118), respectively, P < 0.0001. The median D2B time was lower in the PHT group vs the no-PHT group: 45 minutes (IQR, 34-56) vs 63 minutes (IQR, 49-81), respectively, P < 0.0001. Multivariate analysis showed PHT to be the strongest predictor of a C2D time of <90 minutes (odds ratio: 3.73, 95% confidence interval: 1.65-8.39, P = 0.002). Female sex was negatively predictive of achieving a C2D time <90 minutes (odds ratio: 0.23, 95% confidence interval: 0.07-0.73, P = 0.01). CONCLUSIONS: In STEMI patients, PHT was associated with significantly reduced C2D and D2B times and was an independent predictor of achieving a target C2D time. As centers adapt to the new guidelines emphasizing C2D time, targeting a shorter D2B time (<50 minutes) is ideal to achieve a C2D time of <90 minutes.

BACKGROUND: Previous studies have suggested that weekend hospital care is inferior to weekday care and that this difference may be related to diminished care intensity. The purpose of this study was to determine whether a metric for measuring intensity of hospital care based on utilization of the electronic health record (EHR) was associated with patient-level outcomes. METHODS: We performed a cohort study of hospitalizations at an academic medical center. Intensity of care was defined as the hourly number of provider accessions of the electronic health record, termed "EHR interactions." Hospitalizations were categorized based on the mean difference in EHR interactions between the first Friday and Saturday of hospitalization. We used regression models to determine the association of these categories with patient outcomes after adjusting for covariates. RESULTS: EHR interactions decreased from Friday to Saturday in 77% of the 9,051 hospitalizations included in the study. As compared to hospitalizations with no change in Friday to Saturday EHR interactions, the relative lengths of stay for hospitalizations with a small, moderate, and large decrease in EHR interactions were 1.05 (95% CI 1.00-1.10), 1.11 (95% CI 1.05-1.17), and 1.25 (95% CI 1.15-1.35), respectively. Although a large decrease in EHR interactions was associated with in-hospital mortality, these findings were not significant after risk adjustment (odds ratio 1.74, 95% CI 0.93-3.25). CONCLUSIONS: Intensity of inpatient care, measured by EHR interactions, significantly diminished from Friday to Saturday, and this decrease was associated with length of stay. Hospitals should consider monitoring and correcting temporal fluctuations in care intensity.

BACKGROUND: Given that 4 million individuals in the United States have atrial fibrillation, understanding the epidemiology of this disease is crucial. We sought to identify and characterize the impact of age on national atrial fibrillation hospitalization patterns. METHODS: The study sample was drawn from the 2009-2010 Nationwide Inpatient Sample. Patients hospitalized with a principal International Classification of Diseases, 9th Revision discharge diagnosis of atrial fibrillation were included. Patients were categorized as "older" (>/=65 years) or "younger" (<65 years) for the purposes of analysis. The outcomes measured included hospitalization rate, length of stay, in-hospital mortality, and discharge status. RESULTS: We identified 192,846 atrial fibrillation hospitalizations. There was significant geographic variation in hospitalizations for both younger and older age groups. States with high hospitalizations differed from those states known to have high stroke mortality. Younger patients (33% of the sample) were more likely to be obese (21% vs 8%, P < .001) and to use alcohol (8% vs 2%, P < .001). Older patients were more likely to have kidney disease (14% vs 7%, P < .001). Both age groups had high rates of hypertension and diabetes. Older patients had higher in-hospital mortality and were more likely to be discharged to a nursing or intermediate care facility. CONCLUSIONS: Younger patients account for a substantial minority of atrial fibrillation hospitalizations in contemporary practice. Younger patients are healthier, with a different distribution of risk factors, than older patients who have higher associated morbidity and mortality.

OBJECTIVES: The study sought to assess the quality of care for heart failure patients who are hospitalized for all causes. BACKGROUND: Performance measures for heart failure target patients with a principal diagnosis of heart failure. However, patients with heart failure are commonly hospitalized for other causes and may benefit from treatments such as angiotensin-converting enzyme (ACE) inhibitors for left ventricular (LV) systolic dysfunction. METHODS: We assessed rates of compliance with care measures for patients hospitalized with acute or chronic heart failure in the ARIC (Atherosclerosis Risk In Communities) study surveillance catchment area from 2005 to 2009. Rates of compliance were compared between patients with a principal discharge diagnosis of heart failure and those with another principal discharge diagnosis. RESULTS: Of 4,345 hospitalizations of heart failure patients, 39.6% carried a principal diagnosis of heart failure. Patients with a principal heart failure diagnosis had higher rates of LV function assessment (89.1% vs. 82.5%; adjusted prevalence ratio [aPR]: 1.07; 95% confidence interval [CI]: 1.04 to 1.10) and discharge ACE inhibitor/angiotensin receptor blocker (ARB) in LV dysfunction (64.1% vs. 56.3%; aPR: 1.11; 95% CI: 1.03 to 1.20) as compared to patients hospitalized for another cause. LV assessment and ACE inhibitor/ARB use were associated with reductions in 1-year post-discharge mortality (adjusted odds ratio: 0.66, 95% CI: 0.51 to 0.85; adjusted odds ratio: 0.72, 95% CI: 0.54 to 0.96, respectively) that did not differ for patients with versus without a principal heart failure diagnosis. CONCLUSIONS: Compared with individuals hospitalized with a principal diagnosis of heart failure, heart failure patients hospitalized for other causes were less likely to receive guideline recommended care. Quality initiatives may improve care by targeting hospitalizations with either principal or secondary heart failure diagnoses.

BACKGROUND: Hospital care on weekends has been associated with reduced quality and poor clinical outcomes, suggesting that decreases in overall intensity of care may have important clinical effects. We describe a new measure of hospital intensity of care based on utilization of the electronic health record (EHR). METHODS: We measured global intensity of care at our academic medical center by monitoring the use of the EHR in 2011. Our primary measure, termed EHR interactions, was the number of accessions of a patient's electronic record by a clinician, adjusted for hospital census, per unit of time. Our secondary measure was percent of total available central processing unit (CPU) power used to access EHR servers at a given time. RESULTS: EHR interactions were lower on weekend days as compared to weekdays at every hour (P < 0.0001), and the daytime peak in intensity noted each weekday was blunted on weekends. The relative rate and 95% confidence interval (CI) of census-adjusted record accessions per patient on weekdays compared with weekends were: 1.76 (95% CI: 1.74-1.77), 1.52 (95% CI: 1.50-1.55), and 1.14 (95% CI: 1.12-1.17) for day, morning/evening, and night hours, respectively. Percent CPU usage correlated closely with EHR interactions (r = 0.90). CONCLUSIONS: EHR usage is a valid and easily reproducible measure of intensity of care in the hospital. Using this measure we identified large, hour-specific differences between weekend and weekday intensity. EHR interactions may serve as a useful measure for tracking and improving temporal variations in care that are common, and potentially deleterious, in hospital systems. Journal of Hospital Medicine 2013;8:513-518. (c) 2013 Society of Hospital Medicine.