<![CDATA[Background: Coronary artery disease remains a major contributor to morbidity and mortality worldwide. Simple and accessible tools for estimating coronary angiographic disease burden may facilitate risk stratification, particularly in settings with limited resources.Objective: To develop and temporally internally validate a practical index for estimating coronary angiographic disease burden using routinely available clinical and metabolic parameters.Methods: We retrospectively analyzed medical records of 414 patients for model derivation and 166 patients for temporal internal validation, who underwent coronary angiography at Dr. Ramelan Naval Central Hospital between 2024 and 2025. Angiographic burden was classified as mild (Gensini score <11) or moderate-to-severe (≥11). Candidate predictors were evaluated using logistic regression, and model performance was assessed using receiver operating characteristic (ROC) analysis.Result: Older age, higher fasting blood glucose (FBG), and atherogenic index of plasma (AIP) were independently associated with greater CAD burden (all p < 0.05), and were incorporated into the Coronary Angiographic Burden Estimation (CABE) Index. The model demonstrated fair discrimination in the derivation cohort (AUC 0.726;60.5% sensitivity and 73.2% specificity at the predefined cutoff) and showed consistent performance in the temporal validation cohort (AUC 0.729). Conclusion: The CABE index is a simple, association-based tool that estimates the likelihood of higher coronary angiographic burden using routinely available clinical and metabolic parameters. . The index demonstrated fair discrimination and consistent temporal validation performance. Further external multicenter validation is required before its broader application in clinical decision-making.]]>
Copyrights © 2026
