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

Background: 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.

Association of Health Status Scores With Cardiovascular and Limb Outcomes in Patients With Symptomatic Peripheral Artery Disease: Insights From the EUCLID (Examining Use of Ticagrelor in Symptomatic Peripheral Artery Disease) Trial.

Background There are limited data on health status instruments in patients with peripheral artery disease and cardiovascular and limb events. We evaluated the relationship between health status changes and cardiovascular and limb events. Methods and Results In an analysis of the EUCLID (Examining Use of Ticagrelor in Symptomatic Peripheral Artery Disease) trial, we examined the characteristics of 13 801 patients by tertile of health status instrument scores collected in the trial (EuroQol 5-Dimensions [EQ-5D], EQ visual analog scale [VAS], and peripheral artery questionnaire).