Using AI feedback to improve diagnostic reasoning in kidney medicine
Reasoning Enhancement With Feedback From a Generative AI in Nephrology (REFINe): A Randomized Evaluation of Generative AI Support in Nephrology Diagnosis
This test sees if an advanced AI language model can help medical students, residents, fellows, and physicians make more accurate and confident kidney-related diagnoses using online clinical cases.
Quick facts
| Phase | Not applicable |
|---|---|
| Study type | Interventional |
| Enrollment | 100 (estimated) |
| Ages | 18 Years and up |
| Sex | All |
| Sponsor | University Hospital, Lille Academic / other |
| Locations | 1 site (Lille) |
| Trial ID | NCT07352475 on ClinicalTrials.gov |
What this trial studies
Clinicians are randomized to either receive real-time diagnostic suggestions from a high-reasoning GPT-5-class model or to complete cases without AI support, and each participant completes up to 10 nephrology clinical vignettes presented in English or French. The research team previously benchmarked multiple state-of-the-art models and selected GPT-5 (high-reasoning) based on diagnostic performance, stability, and interpretability. Participants create an account, provide demographic information, consent to data use, and complete vignettes online without backtracking while completion time and responses are recorded. Analysis compares diagnostic accuracy, confidence, and decision-making between the AI-supported and control arms with stratified randomization by professional status.
Who should consider this trial
Good fit: Ideal participants are adults with at least basic medical training (medical students, residents, fellows, or practicing clinicians) who can read English or French and have internet access.
Not a fit: People without medical training, those under 18, or anyone unable to complete online procedures or who lacks English/French ability or internet access are unlikely to benefit from participating.
Why it matters
Potential benefit: If successful, clinicians could arrive at correct nephrology diagnoses more often and with greater confidence, which may translate into faster or more appropriate patient care.
How similar studies have performed: Previous vignette and reader studies using earlier large language models and decision-support tools have sometimes improved diagnostic accuracy but have produced mixed results, so this application is promising but not yet proven.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: Adults aged 18 years or older. Able to read and answer clinical vignettes in English or French. Access to a computer or smartphone with an internet connection. Provides informed consent online. Participants are expected to have at least basic medical training (e.g., medical students, residents, fellows, or practicing clinicians), although no formal verification is required. Exclusion Criteria: Individuals under 18 years of age. Inability to complete online study procedures. Prior involvement in the design, development, or evaluation of the AI system used in this study.
Where this trial is running
Lille
- Lille University Hospital (online study) — Lille, France (Recruiting)
Study contacts
- Study coordinator: Raphaël BENTEGEAC, MD, MPH
- Email: raphael.bentegeac@univ-lille.fr
- Phone: +33651204000
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.