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- Margaret Lin, Richard E Wolfe, Nathan I Shapiro, Victor Novack, Yotam Lior, and Shamai A Grossman.
- Department of Emergency Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School Boston, MA. Electronic address: mjlin@bidmc.harvard.edu.
- Am J Emerg Med. 2015 Nov 1; 33 (11): 1684-6.
BackgroundRising health care costs demands justifying prolonged hospitalization for syncope, yet predictors of shorter length of stay (LOS) have not been identified.ObjectiveThe objective of this study is to identify independent predictors of LOS for syncope patients presenting to the emergency department (ED).MethodsWe performed an analysis of a prospectively collected cohort of ED syncope patients. We examined risk factors from the patient's ED presentation and workup and used Spearman rank correlation to evaluate the relationship between these risk factors and LOS in a logistic regression model for prediction of hospitalization less than 1 day.ResultsOf 568 total syncope patients, 350 (61.6%) were admitted and comprise the study cohort. Mean age was 57 years (SD, ±25 years); 39.6% were male. Length of hospitalization was less than or equal to 1 in 179 patients (51.1%). The number of risk factors was associated with LOS (P < .001). Most hospitalized patients with less than 1 predictor were hospitalized for less than 1 day (152/272; 55.9%). In multivariate logistic regression analysis, clear vasovagal etiology was positively correlated with LOS less than 1 day (odds ratio [OR], 1.92), whereas dysrhythmia (OR, 0.3), coronary artery disease (OR, 0.33), abnormal vital signs (OR, 0.35), implantable defibrillator/pacemaker (OR, 0.29), anemia/gastrointestinal bleeding (OR, 0.34), and central nervous system abnormalities (OR, 0.09; P < .05 for all) were negatively correlated with LOS less than 1 day. Area under the curve for model accuracy was moderate: 0.70 (95% confidence interval, 0.65-0.76).ConclusionPatients with less than 1 predictor of prolonged stay, who present to the ED with syncope, are unlikely to require hospitalization of more than 1 day. A set of predictors may help define which patients are appropriate for 24-hour observation rather than full hospitalization.Copyright © 2015 Elsevier Inc. All rights reserved.
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