Myocardial ischemia associated with clenbuterol abuse: report of two cases.

BACKGROUND: Clenbuterol is an orally administered long-acting beta-2 adrenergic agonist closely related to albuterol that, in recent years, has become a substance of abuse in the bodybuilding and athletic community. OBJECTIVES: We report two cases of acute myocardial ischemia associated with clenbuterol abuse in two healthy young male body builders. CASE REPORT: Two male bodybuilders, ages 18 and 22 years, presented to the Emergency Department with palpitations, nausea, vomiting, chest pain, diaphoresis, and tachycardia shortly after ingesting clenbuterol. Both patients experienced prolonged sinus tachycardia that, in one patient, was relatively resistant to both beta- and calcium channel blockade. Both patients were found to have elevated troponin levels, the first patient as high as 4.71 ng/mL (normal<0.04 ng/mL). Further investigation revealed normal coronary arteries at catheterization and normal cardiac magnetic resonance imaging in the first patient, and normal echocardiograms for both patients. The tachycardia gradually resolved and both patients recovered uneventfully. The etiology of cardiac ischemia in these patients is uncertain. CONCLUSIONS: Emergency physicians should be aware of the clinical presentation of clenbuterol abuse and overdose, and the possibility of related cardiac ischemia and rhythm disturbances. Suggested treatment includes intravenous fluids, oxygen, aspirin, beta-blockers, and benzodiazepines, although efficacy remains unproven.

Generalizability of a simple approach for predicting hospital admission from an emergency department.

OBJECTIVES: The objective was to test the generalizability, across a range of hospital sizes and demographics, of a previously developed method for predicting and aggregating, in real time, the probabilities that emergency department (ED) patients will be admitted to a hospital inpatient unit. METHODS: Logistic regression models were developed that estimate inpatient admission probabilities of each patient upon entering an ED. The models were based on retrospective development (n = 4,000 to 5,000 ED visits) and validation (n = 1,000 to 2,000 ED visits) data sets from four heterogeneous hospitals. Model performance was evaluated using retrospective test data sets (n = 1,000 to 2,000 ED visits). For one hospital the developed model also was applied prospectively to a test data set (n = 910 ED visits) coded by triage nurses in real time, to compare results to those from the retrospective single investigator-coded test data set. RESULTS: The prediction models for each hospital performed reasonably well and typically involved just a few simple-to-collect variables, which differed for each hospital. Areas under receiver operating characteristic curves (AUC) ranged from 0.80 to 0.89, R(2) correlation coefficients between predicted and actual daily admissions ranged from 0.58 to 0.90, and Hosmer-Lemeshow goodness-of-fit statistics of model accuracy had p > 0.01 with one exception. Data coded prospectively by triage nurses produced comparable results. CONCLUSIONS: The accuracy of regression models to predict ED patient admission likelihood was shown to be generalizable across hospitals of different sizes, populations, and administrative structures. Each hospital used a unique combination of predictive factors that may reflect these differences. This approach performed equally well when hospital staff coded patient data in real time versus the research team retrospectively.