Novel Risk Model to Predict Emergency Department Associated Mortality for Patients Supported With a Ventricular Assist Device: The Emergency Department–Ventricular Assist Device Risk Score

Autor: Jonathan B. Edelson, Jonathan J. Edwards, Hannah Katcoff, Antara Mondal, Feiyan Chen, Nosheen Reza, Thomas C. Hanff, Heather Griffis, Jeremy A. Mazurek, Joyce Wald, Danielle S. Burstein, Pavan Atluri, Matthew J. O’Connor, Lee R. Goldberg, Payman Zamani, Peter W. Groeneveld, Joseph W. Rossano, Kimberly Y. Lin, Edo Y. Birati
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease, Vol 11, Iss 2 (2022)
Druh dokumentu: article
ISSN: 2047-9980
DOI: 10.1161/JAHA.121.020942
Popis: Background The past decade has seen tremendous growth in patients with ambulatory ventricular assist devices. We sought to identify patients that present to the emergency department (ED) at the highest risk of death. Methods and Results This retrospective analysis of ED encounters from the Nationwide Emergency Department Sample includes 2010 to 2017. Using a random sampling of patient encounters, 80% were assigned to development and 20% to validation cohorts. A risk model was derived from independent predictors of mortality. Each patient encounter was assigned to 1 of 3 groups based on risk score. A total of 44 042 ED ventricular assist device patient encounters were included. The majority of patients were male (73.6%),
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