Predicting cardiovascular outcomes in elderly patients with acute coronary syndrome: a nomogram approach

Background: Although ST Elevation Myocardial Infarction (STEMI) diagnosis and therapy have improved, high-risk categories like elderly persons still have a significant chance of MACE despite treatment. Objectives: This study attempts to construct a predictive nomogram for MACE incidence using clinical data from a STEMI registry. Methods: Tehran Heart Center's computerized record recognized all 65-year-old STEMI primary PCI patients consecutively. This retrospective study examined demographic, laboratory, clinical, and intra-procedural factors. Post-PCI univariate and multivariate analyses identified MACE risk variables. Decision curve analysis, ROC, and calibration plots validated predictive nomograms. R Studio and R used “tidyverse” and “rms” packages for all analyses. Results: The 1946 study included 70% training and 30% testing patients. Basic demographic and clinical variables were identical for both groups. The average follow-up was 17 months. 8 factors were selected for the nomogram after univariate and multivariate analysis: left-ventricular ejection fraction (LVEF), serum creatinine, hemoglobin, and fasting blood glucose levels, presence of valvular heart disease, post-PCI TIMI flow grade, diameter of the culprit lesion stent, and presence or absence of shock after PCI. The post-PCI MACE prediction AUC was 71%. Calibration plots showed that the nomogram model was well-calibrated and close to observed outcomes. Decision curve analysis also revealed that the model predicted MACE discriminatively. Conclusion: A nomogram successfully predicts MACE risk in older STEMI patients using laboratory, clinical, and procedural parameters. This algorithm may identify vulnerable high-risk patients for more aggressive preventative interventions. Clinical trial number: not applicable.