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 Conclusion: The established MACCE risk nomogram prediction model for elderly patients with CHD could effectively identify high-risk elderly patients with CHD.