Automatic detection of patients eligible for the RAUC augmented rehabilitation program
Official title: Automatic Detection of Eligible Patients to RAUC Protocol (RAUCISABLE): a Retrospective Monocentric Pilot Study on Big-data
Run by Centre Hospitalier Universitaire, Amiens · NCT07037719 · Data updated 2026-11-12
This project will see if an AI-driven system can automatically identify adult emergency department patients who are eligible for the RAUC augmented rehabilitation program after digestive emergency surgery.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 300000 (estimated) |
| Sponsor | Centre Hospitalier Universitaire, Amiens Academic / other |
| Locations | 1 site (Amiens) |
| Status | Recruiting |
| Started | January 17, 2025 |
| Main results expected | January 17, 2026 |
| Study ends | January 17, 2026 |
| Registry record updated | June 25, 2025 |
| Trial ID | NCT07037719 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Ideal candidates are adults (age 17+) who present to the emergency department, especially those undergoing or considered for emergency digestive surgery at CHU Amiens-Picardie.
✕Probably not a fit
Patients who object to use of their clinical data, children, those treated outside CHU Amiens-Picardie, or patients undergoing elective (non-emergency) procedures are unlikely to benefit from this project.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
RAUCisable is an observational program at CHU Amiens-Picardie that uses hospital records, workflow signals, and potentially connected device data to automatically flag patients who meet inclusion criteria for the RAUC augmented rehabilitation pathway. The effort aims to optimize and speed up patient inclusion without altering clinical care by comparing automated detection against current manual processes. Machine learning models will be refined using local data to improve predictive accuracy for patient management. Participation respects patient data objections and follows applicable privacy safeguards.
Why it matters
Potential benefit: If successful, this could speed identification and enrollment of eligible patients so more people can access optimized postoperative rehabilitation and potentially recover faster.
How similar studies have gone: AI-based patient-identification tools have shown promise in other hospital settings, but their application to emergency digestive surgery inclusion workflows is relatively new.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Adults (age 17+), all ED patients Exclusion Criteria: * Patients who object to data use
Where it's running
-
CHU Amiens-Picardie
Amiens, France Recruiting
Study contacts
- Principal investigator: Jean-Marc REGIMBEAU, MD — CHU Amiens-Picardie
- Study coordinator: Jean-Marc REGIMBEAU, MD
- Email: regimbeau.jean-marc@chu-amiens.fr
- Phone: +33 3 22 08 80 00
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.