A novel risk model combining clinical and intravascular ultrasound-based calcific features to predict adverse outcomes in patients with severe coronary artery calcification undergoing percutaneous coronary intervention: the mACEF- Ca model

Severe coronary artery calcification (CAC) significantly complicates percutaneous coronary intervention (PCI), leading to increased procedural challenges and adverse outcomes. Existing clinical risk models such as the age, creatinine and ejection fraction (ACEF) score often lack lesion-specific anatomical data, limiting their predictive performance in high-risk cohorts. This retrospective study enrolled patients with intravascular ultrasound (IVUS)-confirmed severe CAC who underwent non-emergent PCI with drug-eluting stent implantation. Independent predictors of major adverse cardiovascular events (MACE) over a median 2-year follow-up were identified using multivariate Cox regression. A novel modified ACEF score (mACEF) incorporating calcific features (mACEF-Ca) was constructed based on the original mACEF, presence of calcified nodule (CN), and a maximum calcium arc of 360°. Of the 785 included patients, 121 (15.4%) experienced MACE during the 2-year follow-up. Presence of a 360° calcium arc and CN were identified as independent predictors of MACE (HR = 1.63 and 2.61, respectively; both P < 0.001). The simplified mACEF-Ca formula was: mACEF + 1 (if maximum calcium arc = 360°) + 1 (if CN present). This model demonstrated superior discrimination (AUC = 0.778) compared to traditional ACEF-based models (all P < 0.05 by DeLong test). Kaplan–Meier analysis confirmed significantly poorer event-free survival in patients with higher mACEF-Ca scores (log-rank P < 0.001). The mACEF-Ca score, combining clinical and IVUS-derived calcification parameters, enhances risk stratification in patients with severe CAC undergoing PCI. It offers a practical and effective tool for identifying high-risk individuals, guiding procedural planning, and informing post-procedural management strategies.