Long‐Term Mortality Predictors Using a Machine‐Learning Approach in Patients With Chronic Limb‐Threatening Ischemia After Peripheral Vascular Intervention

Patients with chronic limb-threatening ischemia (CLTI) face a high long-term mortality risk. Identifying novel mortality predictors and risk profiles would enable individual health care plan design and improved survival. We aimed to leverage a random survival forest machine-learning algorithm to identify long-term all-cause mortality predictors in patients with CLTI undergoing peripheral vascular intervention.