NCT06842927

Brief 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.

Trial Health

55
Monitor

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Trial has exceeded expected completion date
Enrollment
350

participants targeted

Target at P75+ for all trials

Timeline
Completed

Started Mar 2025

Geographic Reach
1 country

1 active site

Status
enrolling by invitation

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

First Submitted

Initial submission to the registry

February 2, 2025

Completed
22 days until next milestone

First Posted

Study publicly available on registry

February 24, 2025

Completed
7 days until next milestone

Study Start

First participant enrolled

March 3, 2025

Completed
12 months until next milestone

Primary Completion

Last participant's last visit for primary outcome

February 28, 2026

Completed
1 month until next milestone

Study Completion

Last participant's last visit for all outcomes

March 31, 2026

Completed
Last Updated

April 9, 2025

Status Verified

April 1, 2025

Enrollment Period

12 months

First QC Date

February 2, 2025

Last Update Submit

April 7, 2025

Conditions

End-Stage Kidney DiseaseEnd Stage Renal Disease (ESRD)End Stage Renal Disease on Dialysis (Diagnosis)End Stage Renal Failure on DialysisPeritoneal DialysisPeritoneal Dialysis Patients

Keywords

Peritoneal dialysisArtificial intelligenceDialysis adequacyPeritoneum transporter statusRenal replacement therapy

Outcome Measures

Primary Outcomes (8)

  • Peritoneal Equilibration Test (PET) Parameters

    Predictive Accuracy of AI Model for Peritoneal Equilibration Test (PET) Parameters Outcome: AI-predicted vs. actual 2-hour and 4-hour dialysate-to-plasma creatinine ratio (D/P Cr) Performance Metrics: Mean Absolute Error (MAE) Unit of Measure: Absolute error

    Measured at baseline during study enrollment

  • Peritoneal Equilibration Test (PET) Parameters

    Predictive Accuracy of AI Model for Peritoneal Equilibration Test (PET) Parameters Outcome: AI-predicted vs. actual dialysate-to-baseline dialysate glucose concentration ratio (D/D0 Glu) Performance Metrics: Mean Absolute Error (MAE) Unit of Measure: Absolute error

    Measured at baseline during study enrollment

  • Peritoneal Equilibration Test (PET) Parameters

    Predictive Accuracy of AI Model for Peritoneal Equilibration Test (PET) Parameters Outcome: AI-predicted vs. actual 2-hour and 4-hour dialysate-to-plasma creatinine ratio (D/P Cr) Performance Metrics: Mean Squared Error (MSE) Unit of Measure: Squared Error

    Measured at baseline during study enrollment

  • Peritoneal Equilibration Test (PET) Parameters

    Predictive Accuracy of AI Model for Peritoneal Equilibration Test (PET) Parameters Outcome: AI-predicted vs. actual dialysate-to-baseline dialysate glucose concentration ratio (D/D0 Glu) Performance Metrics: Mean Squared Error (MSE) Unit of Measure: Squared Error

    Measured at baseline during study enrollment

  • Peritoneal Equilibration Test (PET) Parameters

    Predictive Accuracy of AI Model for Peritoneal Equilibration Test (PET) Parameters Outcome: AI-predicted vs. actual 2-hour and 4-hour dialysate-to-plasma creatinine ratio (D/P Cr) Performance Metrics: Coefficient of Determination (R²) Unit of Measure: R² value (range: 0 to 1, higher values indicate better model performance)

    Measured at baseline during study enrollment

  • Peritoneal Equilibration Test (PET) Parameters

    Predictive Accuracy of AI Model for Peritoneal Equilibration Test (PET) Parameters Outcome: AI-predicted vs. actual dialysate-to-baseline dialysate glucose concentration ratio (D/D0 Glu) Performance Metrics: Coefficient of Determination (R²) Unit of Measure: R² value (range: 0 to 1, higher values indicate better model performance)

    Measured at baseline during study enrollment

  • Peritoneal Equilibration Test (PET) Parameters

    Predictive Accuracy of AI Model for Peritoneal Equilibration Test (PET) Parameters Outcome: AI-predicted vs. actual 2-hour and 4-hour dialysate-to-plasma creatinine ratio (D/P Cr) Performance Metrics: Intraclass Correlation Coefficient (ICC) Unit of Measure: ICC value (range: 0 to 1, higher values indicate better agreement)

    Measured at baseline during study enrollment

  • Peritoneal Equilibration Test (PET) Parameters

    Predictive Accuracy of AI Model for Peritoneal Equilibration Test (PET) Parameters Outcome: AI-predicted vs. actual dialysate-to-baseline dialysate glucose concentration ratio (D/D0 Glu) Performance Metrics: Intraclass Correlation Coefficient (ICC) Unit of Measure: ICC value (range: 0 to 1, higher values indicate better agreement)

    Measured at baseline during study enrollment

Secondary Outcomes (12)

  • Dialysis Adequacy (Kt/V) parameters

    Measured at baseline during study enrollment

  • Dialysis Adequacy (Kt/V) parameters

    Measured at baseline during study enrollment

  • Dialysis Adequacy (Kt/V) parameters

    Measured at baseline during study enrollment

  • Dialysis Adequacy (Kt/V) parameters

    Measured at baseline during study enrollment

  • Discriminative Ability of AI Model

    Measured at baseline during study enrollment

  • +7 more secondary outcomes

Study Arms (2)

Training/Validation

Participants in training/validation arm will receive the same standard investigations and care as part of their routine PD management, including clinical evaluations, biochemical testing, and measurements of peritoneal transporter status via the Peritoneal Equilibrium Test (PET) and dialysis adequacy (Kt/V).

Other: data collection

Test

Participants in training/validation arm will receive the same standard investigations and care as part of their routine PD management, including clinical evaluations, biochemical testing, and measurements of peritoneal transporter status via the Peritoneal Equilibrium Test (PET) and dialysis adequacy (Kt/V).

Other: data report

Interventions

data collectionOTHER

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.

Also known as: model training
Training/Validation
data reportOTHER

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

Also known as: model testing
Test

Eligibility Criteria

Age18 Years+
Sexall
Healthy VolunteersNo
Age GroupsAdult (18-64), Older Adult (65+)
Sampling MethodNon-Probability Sample
Study Population

End-stage renal failure patients requiring peritoneal dialysis as renal replacement therapy

You may qualify if:

  • Age 18 years or older
  • Diagnosis of end-stage renal failure requiring peritoneal dialysis as renal replacement therapy
  • Ability to give informed consent and comply with study procedures.

You may not qualify if:

  • History of hernia or peritoneal leak, including pleuroperitoneal fistula (PPF), patent processus vaginalis (PPV) and retroperitoneal leak
  • Ongoing PD peritonitis with or without antibiotic therapy
  • Just finished PD peritonitis antibiotic treatment within recent 4 weeks
  • Pregnancy
  • Patient refusal

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

Tuen Mun Hospital

Tuenmen, Hong Kong

Location

Related Publications (12)

  • Riley RD, Ensor J, Snell KIE, Harrell FE Jr, Martin GP, Reitsma JB, Moons KGM, Collins G, van Smeden M. Calculating the sample size required for developing a clinical prediction model. BMJ. 2020 Mar 18;368:m441. doi: 10.1136/bmj.m441. No abstract available.

    PMID: 32188600BACKGROUND

  • Szeto CC, Wong TY, Chow KM, Leung CB, Li PK. Dialysis adequacy and transport test for characterization of peritoneal transport type in Chinese peritoneal dialysis patients receiving three daily exchanges. Am J Kidney Dis. 2002 Jun;39(6):1287-99. doi: 10.1053/ajkd.2002.33405.

    PMID: 12046043BACKGROUND

  • SPRINT Research Group; Wright JT Jr, Williamson JD, Whelton PK, Snyder JK, Sink KM, Rocco MV, Reboussin DM, Rahman M, Oparil S, Lewis CE, Kimmel PL, Johnson KC, Goff DC Jr, Fine LJ, Cutler JA, Cushman WC, Cheung AK, Ambrosius WT. A Randomized Trial of Intensive versus Standard Blood-Pressure Control. N Engl J Med. 2015 Nov 26;373(22):2103-16. doi: 10.1056/NEJMoa1511939. Epub 2015 Nov 9.

    PMID: 26551272BACKGROUND

  • Chen CA, Lin SH, Hsu YJ, Li YC, Wang YF, Chiu JS. Neural network modeling to stratify peritoneal membrane transporter in predialytic patients. Intern Med. 2006;45(9):663-4. doi: 10.2169/internalmedicine.45.1419. Epub 2006 Jun 1. No abstract available.

    PMID: 16755101BACKGROUND

  • Gu J, Bai E, Ge C, Winograd J, Shah AD. Peritoneal equilibration testing: Your questions answered. Perit Dial Int. 2023 Sep;43(5):361-373. doi: 10.1177/08968608221133629. Epub 2022 Nov 9.

    PMID: 36350033BACKGROUND

  • Morelle J, Stachowska-Pietka J, Oberg C, Gadola L, La Milia V, Yu Z, Lambie M, Mehrotra R, de Arteaga J, Davies S. ISPD recommendations for the evaluation of peritoneal membrane dysfunction in adults: Classification, measurement, interpretation and rationale for intervention. Perit Dial Int. 2021 Jul;41(4):352-372. doi: 10.1177/0896860820982218. Epub 2021 Feb 10.

    PMID: 33563110BACKGROUND

  • Blake PG, Bargman JM, Brimble KS, Davison SN, Hirsch D, McCormick BB, Suri RS, Taylor P, Zalunardo N, Tonelli M; Canadian Society of Nephrology Work Group on Adequacy of Peritoneal Dialysis. Clinical Practice Guidelines and Recommendations on Peritoneal Dialysis Adequacy 2011. Perit Dial Int. 2011 Mar-Apr;31(2):218-39. doi: 10.3747/pdi.2011.00026. No abstract available.

    PMID: 21427259BACKGROUND

  • Chen JB, Lam KK, Su YJ, Lee WC, Cheng BC, Kuo CC, Wu CH, Lin E, Wang YC, Chen TC, Liao SC. Relationship between Kt/V urea-based dialysis adequacy and nutritional status and their effect on the components of the quality of life in incident peritoneal dialysis patients. BMC Nephrol. 2012 Jun 14;13:39. doi: 10.1186/1471-2369-13-39.

    PMID: 22697882BACKGROUND

  • Lin YL, Lee YC, Lee CC, Wu MH. Role of Peritoneal Equilibration Test in Assessing Folate Transport During Peritoneal Dialysis. J Ren Nutr. 2024 Sep;34(5):463-468. doi: 10.1053/j.jrn.2024.02.003. Epub 2024 Mar 13.

    PMID: 38490516BACKGROUND

  • Cnossen TT, Smit W, Konings CJ, Kooman JP, Leunissen KM, Krediet RT. Quantification of free water transport during the peritoneal equilibration test. Perit Dial Int. 2009 Sep-Oct;29(5):523-7.

    PMID: 19776045BACKGROUND

  • Twardowski ZJ. Clinical value of standardized equilibration tests in CAPD patients. Blood Purif. 1989;7(2-3):95-108. doi: 10.1159/000169582.

    PMID: 2663040BACKGROUND

  • Bello AK, Okpechi IG, Osman MA, Cho Y, Cullis B, Htay H, Jha V, Makusidi MA, McCulloch M, Shah N, Wainstein M, Johnson DW. Epidemiology of peritoneal dialysis outcomes. Nat Rev Nephrol. 2022 Dec;18(12):779-793. doi: 10.1038/s41581-022-00623-7. Epub 2022 Sep 16.

    PMID: 36114414BACKGROUND

MeSH Terms

Conditions

Kidney Failure, ChronicDisease

Interventions

Data CollectionResearch Design

Condition Hierarchy (Ancestors)

Renal Insufficiency, ChronicRenal InsufficiencyKidney DiseasesUrologic DiseasesFemale Urogenital DiseasesFemale Urogenital Diseases and Pregnancy ComplicationsUrogenital DiseasesMale Urogenital DiseasesChronic DiseaseDisease AttributesPathologic ProcessesPathological Conditions, Signs and Symptoms

Intervention Hierarchy (Ancestors)

Epidemiologic MethodsInvestigative TechniquesHealth Care Evaluation MechanismsQuality of Health CareHealth Care Quality, Access, and EvaluationPublic HealthEnvironment and Public HealthMethods

Study Design

Study Type
observational
Observational Model
COHORT
Time Perspective
PROSPECTIVE
Sponsor Type
OTHER GOV
Responsible Party
PRINCIPAL INVESTIGATOR
PI Title
Resident Specialist

Study Record Dates

First Submitted

February 2, 2025

First Posted

February 24, 2025

Study Start

March 3, 2025

Primary Completion

February 28, 2026

Study Completion

March 31, 2026

Last Updated

April 9, 2025

Record last verified: 2025-04

Locations

HK(1)