The Seattle Post Myocardial Infarction Model (SPIM): prediction of mortality after acute myocardial infarction with left ventricular dysfunction. Issue 1 (March 2014)

• Record Type: Journal Article
• Authors: Ketchum, Eric S; Dickstein, Kenneth; Kjekshus, John; Pitt, Bertram; Wong, Meagan F; Linker, David T; Levy, Wayne C
• Is Part Of: European heart journal. Volume 3:Issue 1(2014:Mar.)
• Page Start: 46
• Page End: 55
• Publication Date: 2014-03
• Subjects: Myocardial infarction -- risk model -- survival; 616.1205
• DOI: 10.1177/2048872613502283
• Languages: English
• ISSNs: 2048-8726

Abstract

Aims: Ischemic heart disease is a leading worldwide cause of death. The Seattle Post Myocardial Infarction Model (SPIM) was developed to predict survival 6 months to 2 years after an acute myocardial infarction with evidence of left ventricular dysfunction. Methods and Results: A total of 6632 subjects from the EPHESUS trial were used to derive the predictive model, while 5477 subjects from the OPTIMAAL trial were used to validate the model. Cox proportional hazards modeling was used to develop a multivariate risk score predictive of all-cause mortality. The SPIM risk score integrated lab and vital parameters, Killip class, reperfusion or revascularization, the number of cardiac evidence-based medicines (aspirin, statin, β blocker, ACEI/ARB, aldosterone blocker), and the number of cardiac risk factors. The model was predictive of all-cause mortality after myocardial infarction, with an AUC of 0.75 at 6 months and 0.75 at 2 years in the derivation cohort and 0.77 and 0.78 for the same time points in the validation cohort. Model predicted versus Kaplan-Meier observed survival was excellent in the derivation cohort. It remained so in the validation cohort—84.9% versus 85.0% at 2 years. The 10% of subjects with the highest predicted risk had approximately 25 times higher mortality at 2 years than the 10% of subjects with the lowest predicted risk. Conclusion: The SPIM score was a powerful predictor of outcomes after myocardial infarction with left ventricular dysfunction. Its highly accurate predictions should improve patient and physician understanding of survival and may prove a useful tool in post-infarct risk stratification.