Why the study?
Does early risk stratification using 7 clinical variables predict short-term mortality in patients with acute myocardial infarction?
Does early risk stratification using 7 clinical variables predict short-term mortality in patients with acute myocardial infarction?
A simple discriminant function using 7 routinely collected clinical variables can accurately predict short-term mortality in patients with acute myocardial infarction.
May support early AMI mortality prediction with routine variables; hypothesis-generating and requires prospective validation before practice change.
The value of non-invasive, clinical variables in predicting short-term outcome after acute myocardial infarction has been prospectively studied using multivariate analysis in a learning population of 1724 patients and a validation sample of 588 cases. Early risk stratification of CCU mortality could be made with 89.4% accuracy by using 7 simple clinical variables (Killip class, systolic blood pressure, heart rate, age, intraventricular conduction disturbance, localization of infarction and obesity index) recorded on admission. A discriminant function formula could also be constructed resulting in a maximal classification of 89.3% and predictive values of 91.8% and 77.9%, respectively, for 28-day survival and early death prediction in the learning population. Accuracy figures dropped only slightly (1 to 5%) in the independent test set. Predictions could be made with a high degree of accuracy, especially in the upper and lower ranges of the discriminant risk score. This investigation demonstrates that a fairly good estimation of prognosis can be made by means of discriminant analysis of clinical findings gathered routinely in most CCU's.
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WlLLEMS et al. (1984) studied this question.
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