Critical pathways in cardiology
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Identifying acute coronary syndrome is a difficult task in the emergency department because symptoms may be atypical and the electrocardiogram has low sensitivity. In this prospective cohort study done in a tertiary community emergency hospital, we developed and tested a neural diagnostic tree in 566 consecutive patients with chest pain and no ST-segment elevation for the diagnosis of acute coronary syndrome. Multivariate regression and recursive partitioning analysis allowed the construction of decision rules and of a neural tree for the diagnosis of acute myocardial infarction and acute coronary syndrome. ⋯ Negative likelihood ratios were 0.02 and 0.1, respectively. It is concluded that this simple and easy-to-use neural diagnostic tree was very accurate in the identification of non-ST segment elevation chest pain patients without acute coronary syndrome. Patients identified as low probability of disease could receive immediate stress testing and be discharged if the test is negative.