AI-Driven Prediction of Dialysis Outcome With EHR
Predicting Clinical Outcomes in Dialysis Patients Using Electronic Health Records: An AI-Based Approach
The Eye Hospital of Wenzhou Medical University
1,000,000 participants
Jan 1, 2023
OBSERVATIONAL
Conditions
Summary
This is a multi-center, clinical study designed to evaluate the application and effectiveness of an AI-assisted predictive model for outcome of dialysis patients, leveraging multimodal health data.
Eligibility
Inclusion Criteria3
- Patients who have been undergoing dialysis (either hemodialysis or peritoneal dialysis) for at least 3 months.
- Complete and accessible EHR data, including medical history, laboratory test results, dialysis treatment details, and clinical observations.
- Participants must provide informed consent for the use of their health data for research purposes.
Exclusion Criteria2
- Patients with incomplete or missing critical EHR data, including medical history, laboratory results, dialysis data, or treatment details necessary for the study.
- Patients who have been on dialysis for less than 3 months, to ensure stable data for outcome prediction.
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Interventions
This study utilizes an AI-assisted predictive model that analyzes multimodal data from electronic health records, including medical history, laboratory results, dialysis treatment details, and clinical observations, to predict outcomes for dialysis patients. The model employs deep learning algorithms to predict mortality risk, intermediate outcomes such as anemia, blood pressure control, nutrition, and calcium-phosphate metabolism, and helps identify early signs of deterioration. The intervention is not a direct treatment or procedure but aims to develop a tool for predicting patient outcomes and optimizing treatment strategies to improve overall health and survival rates for dialysis patients.
Locations(1)
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NCT06791447