Clinical trial NCT06791447: AI-Driven Prediction of Dialysis Outcome With EHR
Official title: Predicting Clinical Outcomes in Dialysis Patients Using Electronic Health Records: An AI-Based Approach
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Dialysis Patients
Keywords: Dialysis Patients
AI-Assisted Prediction
Lead sponsor: The Eye Hospital of Wenzhou Medical University
Sponsor class: OTHER
First posted: 2025-01-24
Enrollment: 1000000
Sex: ALL
Minimum age (years): 20
Maximum age (years): 100
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: The study population consists of dialysis patients from the China Hemodialysis National Network Center, which includes a wide range of patients undergoing hemodialysis treatment at participating hospitals across China. Participants will be selected based on the availability of comprehensive electronic health records (EHR), including medical history, laboratory test results, dialysis treatment details, and clinical observations. The cohort will include both male and female patients, with varying degrees of health status, including those with comorbidities commonly associated with dialysis. The study aims to utilize this diverse group to assess and predict outcomes related to mortality and complications in dialysis patients.

Brief 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.

Detailed description: This study aims to develop an AI-assisted model to predict clinical outcomes in dialysis patients, focusing on both primary outcomes (e.g., mortality) and intermediate outcomes (e.g., anemia, blood pressure, nutritional status, and calcium-phosphate metabolism). The study will utilize patients' EHR data, including laboratory test results, medical history, dialysis treatment information, and clinical observations, to predict these health outcomes. The goal is to improve early identification of at-risk patients, enabling better clinical decision-making and personalized care strategies.

Eligibility criteria: Inclusion Criteria:

1. Patients who have been undergoing dialysis (either hemodialysis or peritoneal dialysis) for at least 3 months.
2. Complete and accessible EHR data, including medical history, laboratory test results, dialysis treatment details, and clinical observations.
3. Participants must provide informed consent for the use of their health data for research purposes.

Exclusion Criteria:

1. Patients with incomplete or missing critical EHR data, including medical history, laboratory results, dialysis data, or treatment details necessary for the study.
2. Patients who have been on dialysis for less than 3 months, to ensure stable data for outcome prediction.

Primary outcomes:
measure: Mortality Prediction Accuracy
timeFrame: 1 year
Secondary outcomes:
measure: Complications Prediction Accuracy
timeFrame: 1 year
Other outcomes:
Locations:
city: Beijing
country: China
facility: General Hospital of PLA
state: Beijing
Study officials:
References: