A simple statistical model for prediction of acute coronary syndrome in chest pain patients in the emergency department期刊界 All Journals 搜尽天下杂志传播学术成果专业期刊搜索期刊信息化学术搜索

A simple statistical model for prediction of acute coronary syndrome in chest pain patients in the emergency department

Authors:	Jonas Björk Jakob L Forberg Mattias Ohlsson Lars Edenbrandt Hans Öhlin Ulf Ekelund

Affiliation:	1. Competence Center for Clinical Research, Lund University Hospital, Lund, Sweden 2. Department of Clinical Sciences, Section for Emergency Medicine, Lund University Hospital, Lund, Sweden 3. Department of Theoretical Physics, Lund University, Lund, Sweden 4. Department of Clinical Physiology, Malm? University Hospital, Malm?, Sweden 5. Department of Clinical Physiology, Sahlgrenska University Hospital, Gothenburg, Sweden 6. Department of Cardiology, Lund University Hospital, Lund, Sweden

Abstract:	Background Several models for prediction of acute coronary syndrome (ACS) among chest pain patients in the emergency department (ED) have been presented, but many models predict only the likelihood of acute myocardial infarction, or include a large number of variables, which make them less than optimal for implementation at a busy ED. We report here a simple statistical model for ACS prediction that could be used in routine care at a busy ED.

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