Wcn24-1075 a Machine Learning-Predictive Model to Identify Factors Associated With Death in Dialysis Patients

Chronic Kidney Disease (CKD) is a significant global health concern, and dialysis patients have a higher mortality rate from cardiovascular disease (CVD) compared to the general population. The use of Machine Learning (ML) and Artificial Intelligence in medicine has grown exponentially over the past few decades. However, few studies have focused on predictive models for determining factors associated with death in dialysis patients, with a predominant focus on the hemodialysis (HD) population. The primary objective of this study was to identify mortality-related factors in patients undergoing both hemodialysis (HD) and peritoneal dialysis (PD), encompassing both planned and urgent starts.