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Investigating the Impact of AI on Shared Decision Making in Post-kidney Transplant Care

NCT06056518 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 76

Last updated 2026-05-15

No results posted yet for this study

Summary

This study aims to analyze the effects of AI-based risk prediction for graft loss on the frequency of conversations about the treatment after graft loss, as well as the associated shared decision making process in post-kidney transplant care in a German kidney transplant center (KTC), as perceived by the patient, their support person and the clinician/physician. Second, it aims to explore changes in patient and support person recall at 12 months follow-up. Implementation barriers and enablers will also be assessed. The protocol was amended so that the initially planned 24 months observation timeframe was removed from the study and it ended after 12 months due to high attrition and funding restrictions.

Conditions

  • Kidney Transplant Failure

Interventions

OTHER

AI-based risk prediction for kidney graft loss

Implementation of AI-based risk prediction tool for the 1-year risk of kidney graft loss.

Sponsors & Collaborators

  • Charite University, Berlin, Germany

    lead OTHER

Principal Investigators

  • Klemens Budde, MD · Charite University, Berlin, Germany

Study Design

Allocation
RANDOMIZED
Purpose
OTHER
Masking
NONE
Model
PARALLEL

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2024-01-19
Primary Completion
2025-10-21
Completion
2025-10-21

Countries

  • Germany

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 NCT06056518 on ClinicalTrials.gov