Using AI and Electronic Health Records to Predict Outcomes for Adults on Dialysis

What this Trial Is About

Researchers are investigating an AI-assisted predictive model designed to forecast clinical outcomes for patients undergoing dialysis. The study focuses on predicting both primary outcomes, such as mortality, and intermediate outcomes including anemia, blood pressure control, nutritional status, and calcium-phosphate metabolism. By using electronic health records EHR data, the study aims to identify patients at higher risk early and support personalized care decisions. The study uses an AI-assisted model that analyzes various data from patients EHRs, such as medical history, lab results, dialysis treatment information, and clinical observations. Participants are categorized into two groups based on the AI prediction those with a high risk of mortality and those with a low risk. The study compares these groups to assess how well early intervention strategies might work. Participants will have their health records reviewed and analyzed to predict outcomes over a one-year period. Researchers will evaluate the accuracy of mortality and complication predictions using the AI model. The study requires patients to have been on dialysis for at least three months with complete medical data available. Participation involves consenting to the use of health data and monitoring of clinical outcomes through EHRs, with the goal of improving care for dialysis patients.

AI-Driven Prediction of Dialysis Outcome With EHR