Abstract
BACKGROUND: Patients with chronic limb threatening ischemia (CLTI) are at risk for major adverse cardiovascular events (MACE), yet few tools exist for risk stratification. OBJECTIVES: The purpose of this study was to derive and validate a CLTI MACE risk prediction model. METHODS: Participants in the BEST-CLI (Best Endovascular vs. Best Surgical Therapy for Patients with Critical Limb Ischemia) trial were randomly split 80%/20% into derivation and validation cohorts. A parsimonious multivariable model to predict 1-year MACE was developed. External validation was performed in the observational BEST Registry with 1-year outcomes conducted at a subset of 40 BEST-CLI trial sites. RESULTS: Among 1,780 patients, the average age was 67.2 years, 28.3% were female, and 20.2% were Black. Hypertension (87.1%), hyperlipidemia (73.9%), diabetes (69.2%), and coronary artery disease (44.9%) were prevalent. The 1-year cumulative incidence of MACE was 17.33% (95% CI: 15.59%-19.24%). Overall model discrimination (C-statistic = 0.669) and calibration (calibration slope = 0.884) were good. Model performance was driven by nonmodifiable risk factors: prior coronary artery disease (HR: 2.22 [95% CI: 1.72-2.89]; P < 0.0001), congestive heart failure (HR: 1.93 [95% CI: 1.35-2.75]; P = 0.0003), stage 3 or greater chronic kidney disease (HR: 1.46 [95% CI: 1.14-1.87]; P = 0.0025). Statin use was protective (HR: 0.7 [95% CI: 0.54-0.91]; P = 0.007) but mode of revascularization was not. External validation in the BEST Registry yielded a C-statistic of 0.66 and a calibration slope of 0.78. CONCLUSIONS: The BEST-CLI MACE model predicts 1-year MACE in CLTI, is not influenced by mode of revascularization, and highlights the importance of statin therapy. Further work is needed to determine if this model may be helpful in guiding therapeutic decision-making in CLTI patients.