Risk prediction after myocardial infarction. Comparison of three multivariate methodologies

We predicted 30-day mortality and survival following acute myocardial infarction in two different hospital populations utilizing several multivariate statistical methodologies [linear discriminant analysis (LDA), logistic regression (LR), recursive partitioning (RP), and nearest neighbor]. Variables used were identified as predictive univariately from the base hospital and were obtained during the first 24 h after admission. LDA, LR, or RP all performed similarly within a given population; although each used the information contained in the prognostic variables differently. Application between different populations of prediction schemes based on LDA and LR was shown to be feasible but prior validation is essential.