A nomogram model in elderly patients with coronary heart disease for predicting prognosis: research based on a real-world registry in China

Purpose Coronary heart disease (CHD) is closely associated with aging and has become the leading cause of death in the elderly (≥65 years). This study aimed to identify independent risk factors for 2-year major adverse cardiovascular and cerebrovascular events (MACCE) in elderly patients with CHD, construct a nomogram model for predicting MACCE risk, and validate its performance to assist in identifying high-risk patients and optimizing secondary prevention strategies. Methods Patients aged ≥65 years diagnosed with CHD were included. The primary outcome of the study was MACCE. The secondary outcomes included cardiovascular death and cardiovascular readmission. A nomogram model was constructed. Patients were divided into low-risk, medium-risk, and high-risk groups according to the tertiles of the nomogram model scores, and the primary and secondary outcomes of patients with different risks were compared. Results This study finally included 8,340 elderly patients with CHD. MACCE occurred in 523 patients during the follow-up period, with an incidence rate of 6.3%. The Least Absolute Shrinkage and Selection Operator (LASSO) regression method was used to screen 11 independent factors associated with MACCE within 2 years. The model had a good predictive value for MACCE, with a C-statistic of 0.765 (95% CI: 0.743–0.788). The MACCE rates ranged from low risk 1.6%, medium risk 4.2% to high risk 12.6%, indicating that the nomogram model can effectively distinguish high risk patients (Log-rank P < 0.001). Conclusion The established MACCE risk nomogram prediction model for elderly patients with CHD could effectively identify high-risk elderly patients with CHD.