Accuracy of a neural diagnostic tree for the identification of acute coronary syndrome in patients with chest pain and no ST-segment elevation.
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. Predictive variables of acute coronary syndrome were: age > or =60 years (odds ratio [OR] = 2.3; P = 0.0016), previous history of coronary artery disease (OR = 2.9; P = 0.0008), diabetes (OR = 2.8; P = 0.0240), definite/probable angina-type chest pain (OR = 17.3; P = 0.0000) and ischemic electrocardiogram (ECG) changes on admission (OR = 3.5; P = 0.0002). The receiver operating characteristic curve of possible diagnostic decision rules of the regression model disclosed a C-index of 0.904 (95% confidence interval = 0.878 to 0.930) for acute coronary syndrome and 0.803 (95% confidence interval 0.757 to 0.849) for acute myocardial infarction. For both disorders, sensitivities of the neural tree were 99% and 93%, respectively, and negative predictive values were both 98%. 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.
Bassan
Roberto
R
Pro-Cardiaco Hospital/PROCEP, Rio de Janeiro, 22.280-020, Brazil. procep@procardiaco.com.br
Pimenta
Lucia
L
Scofano
Marcelo
M
Soares
José Francisco
JF