Predicting 1-Year Mortality in Patients with Non-ST Elevation Myocardial Infarction (NSTEMI) Using Survival Models and Aortic Pressure Signals Recorded During Cardiac Catheterization

Despite successful revascularization, patients with non-ST elevation myocardial infarction (NSTEMI) remain at higher risk of mortality and morbidity. Accurately predicting mortality risk in this cohort can improve outcomes through timely interventions. This study for the first time predicts 1-year all-cause mortality in an NSTEMI cohort using features extracted primarily from the aortic pressure (AP) signal recorded during cardiac catheterization. We analyzed data from 497 NSTEMI patients (66.3 ± 12.9 years, 187 (37.6%) females) retrospectively. We developed three survival models, the multivariate Cox proportional hazards, DeepSurv, and random survival forest, to predict mortality. Then, used Shapley additive explanations (SHAP) to interpret the decision-making process of the best survival model. Using 5-fold stratified cross-validation, DeepSurv achieved an average C-index of 0.935, an IBS of 0.028, and a mean time-dependent AUC of 0.939, outperforming the other models. Ejection systolic time, ejection systolic period, the difference between systolic blood pressure and dicrotic notch pressure (DesP), skewness, the age-modified shock index, and myocardial oxygen supply/demand ratio were identified by SHAP as the most characteristic AP features. In conclusion, AP signal features offer valuable prognostic insight for predicting 1-year all-cause mortality in the NSTEMI population, leading to enhanced risk stratification and clinical decision-making.