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Dialysis Efficiency and Transporter Evaluation Computational Tool in Peritoneal Dialysis

NCT06842927 · Status: ENROLLING_BY_INVITATION · Type: OBSERVATIONAL · Enrollment: 350

Last updated 2025-04-09

No results posted yet for this study

Summary

The goal of this prospective diagnostic test (correlation) study is to develop and investigate the performance of artificial intelligence in predicting peritoneum transporter status and dialysis efficiency in adult patients undergoing peritoneal dialysis (PD).

The main questions it aims to answer are:

Can artificial intelligence predict peritoneal transporter status based on simple clinical and biochemical measurements? Can artificial intelligence predict dialysis adequacy (Kt/V) using these features?

Researchers will compare the performance of the AI model with the gold standard Peritoneal Equilibration Test (PET) and Kt/V to evaluate its accuracy and reliability.

Participants will:

Provide peritoneal dialysate and spot urine samples for biochemical analysis. Undergo routine dialysis adequacy and peritoneal equilibration testing (PET). Have clinical and laboratory data collected for AI model training and validation.

The study will recruit approximately 350 peritoneal dialysis patients, with 280 participants in the training/validation arm and 70 participants in the test arm. The study duration is 12 months following enrollment.

Conditions

  • End-Stage Kidney Disease
  • End Stage Renal Disease (ESRD)
  • End Stage Renal Disease on Dialysis (Diagnosis)
  • End Stage Renal Failure on Dialysis
  • Peritoneal Dialysis
  • Peritoneal Dialysis Patients

Interventions

OTHER

data collection

An additional collection of peritoneal dialysate and spot urine samples will be collected. Participants randomized to the training/validation arm will have their data used for model development, including the training and validation phases.

OTHER

data report

An additional collection of peritoneal dialysate and spot urine samples will be collected. Participants randomized to the test arm will have their data isolated and reserved exclusively for evaluating the performance of the final AI model

Sponsors & Collaborators

  • Tuen Mun Hospital

    lead OTHER_GOV

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-03-03
Primary Completion
2026-02-28
Completion
2026-03-31

Countries

  • Hong Kong

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06842927 on ClinicalTrials.gov