Unsupervised Phenomapping of Perioperative Risk in Stable Coronary Artery Disease: Revealing Limitations of the Revised Cardiac Risk Index

Abstract Aims To derive unsupervised clinical phenotypes in patients with stable coronary artery disease (CAD) undergoing elective non-cardiac surgery and evaluate phenotype-stratified performance of the Revised Cardiac Risk Index (RCRI) and laboratory-augmented CHALSA score for perioperative major adverse cardiovascular events (MACE). Methods This single-center retrospective cohort included 9,171 patients with stable CAD undergoing elective non-cardiac surgery between 2013 and 2023. Unsupervised machine learning identified clusters using 22 preoperative variables. Discrimination, calibration, and clinical utility were evaluated overall and within each phenotype. Results Overall, 514 (5.6%) patients experienced perioperative MACE. Six clinically interpretable phenotypes were identified, with MACE incidence ranging from 1.0% to 16.4%. CHALSA showed higher overall discrimination than RCRI (AUROC 0.816 vs 0.711; P0.001). RCRI discrimination varied substantially across phenotypes and was non-significant in three phenotypes accounting for 60% of MACE burden. The greatest incremental discrimination was observed in Non-revascularized Ischemia (ΔAUROC 0.221), Severe Metabolic Burden (ΔAUROC 0.264), and Stable Revascularized (ΔAUROC 0.205), while CHALSA also showed incremental discrimination in Low-Risk (ΔAUROC 0.172), Ischemic HF (ΔAUROC 0.086), and Elderly Frailty (ΔAUROC 0.142). Across phenotypes, CHALSA showed more stable performance, particularly where RCRI underperformed. Conclusion Perioperative risk in stable CAD is phenotype-dependent. In this single-center cohort, RCRI performance varied by phenotype and may misclassify risk in clinically important high-risk phenotypes, particularly those characterized by occult ischemia or metabolic dysregulation. CHALSA showed more stable performance across phenotypes, but external validation is needed before broader clinical adoption.