A clinical nomogram for predicting major adverse cardiovascular and cerebrovascular events in elderly Chinese patients with acute coronary syndrome undergoing percutaneous coronary intervention: development and validation in a real-world cohort

As the global population ages, the number of elderly patients with acute coronary syndrome (ACS) rises. However, prognostic assessment tools for elderly patients with ACS remain lacking, particularly in the Chinese population. This study aimed to develop and validate a nomogram to predict 2-year major adverse cardiovascular and cerebrovascular events (MACCE) in elderly Chinese patients with ACS.

A retrospective analysis was conducted using two independent cohorts of ACS patients aged ≥ 65 years who underwent percutaneous coronary intervention: the derivation cohort (n = 1674) and the validation cohort (n = 2333). Candidate predictors were selected using multivariable Cox proportional hazards regression and the Akaike information criterion. A final nomogram incorporating ten variables was constructed. Model performance was evaluated in terms of discrimination [concordance index (C-index) and area under the receiver operating characteristic curve (AUC)] and calibration (calibration plots).

The 2-year incidence of MACCE was 12.5% (n = 210) in the derivation cohort and 15.6% (n = 364) in the validation cohort. The nomogram demonstrated good discrimination, with C-index values of 0.727 and 0.661 and AUCs of 0.723 and 0.699 in the derivation cohort and the validation cohort, respectively; significantly outperforming the GRACE risk score (P < 0.001). Calibration plots showed good agreement between the predicted and observed outcomes. Patients classified as the high-risk group by the nomogram had a significantly higher MACCE incidence compared to that of the low-risk group (log-rank P < 0.001).

This newly developed nomogram provides a reliable tool for individualized prediction of the 2-year MACCE risk in elderly Chinese patients with ACS who underwent percutaneous coronary intervention. It outperformed the GRACE score in both discrimmination and calibration and may help improve clinical decision-making and personalized risk stratification in this vulnerable population.