Nomograms based on pre-operative parametric for prediction of short-term mortality in acute myocardial infarction patients treated invasively

Abstract

Objective Our aim was to develop and independently validate nomograms to predict short-term mortality in acute myocardial infarction (AMI) patients. Results There were 1229 AMI patients enrolled in this study. In the training cohort (n=534), 69 deaths occurred during a median follow-up period of 375 days. The C-index for 1-year mortality in the training group and the validation cohort was 0.826 (95%CI: 0.780 - 0.872) and 0.775 (95%CI: 0.695 - 0.855), respectively. Integrated Discrimination Improvement (IDI) and net reclassification improvement (NRI) also showed a significant improvement in the accuracy of the new model compared with the Global Registry of Acute Coronary Events (GRACE) risk score. Furthermore, C-index of the prospective cohort (n=309) achieved 0.817 (95%CI: 0.754 - 0.880) for 30-day mortality and 0.790 (95%CI: 0.718 - 0.863) for 1-year mortality. Conclusions Collectively, our simple-to-use nomogram effectively predicts short-term mortality in AMI patients. Methods AMI patients who had undergone invasive intervention between January 2013 and Jan 2018 were enrolled. Cox regression analysis was used on the training cohort to develop nomograms for predicting 30-day and 1-year mortality. Model performance was then evaluated in the validation cohort and another independent prospective cohort.