Predicting bowel leaks after colorectal surgery with a computer model and surgeon input
Official title: SURGUT - Surgeon's Intuition and Risk Prediction of Anastomotic Leakage: A Prospective Validation Study of a Machine Learning Algorithm
Run by University Hospital, Basel, Switzerland · NCT07888478 · Data updated 2026-11-12
This study tests a computer model that predicts anastomotic leaks after colorectal surgery, and sees if adding surgeons’ intuition improves the predictions.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 4300 (estimated) |
| Sponsor | University Hospital, Basel, Switzerland Academic / other |
| Locations | 2 sites (Liestal, Basel-Landschaft and 1 other locations) |
| Status | Recruiting |
| Started | October 1, 2026 |
| Main results expected | December 31, 2028 |
| Study ends | January 31, 2029 |
| Registry record updated | October 22, 2026 |
| Trial ID | NCT07888478 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Adults 18 years or older undergoing colorectal resection with creation of an anastomosis.
✕Probably not a fit
Patients whose data do not fit the model or who have very low risk may not gain predictive benefit.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
SURGUT is an international observational study that prospectively validates a machine-learning model for predicting anastomotic leakage within 30 days after colorectal resection with anastomosis. It also evaluates whether surgeons’ preoperative and immediate postoperative risk judgments add information beyond the model. Data from multiple centers across countries will include clinical and operative details, model predictions, and surgeons’ assessments, with outcomes tracked for 30 days. The primary outcome is the model’s discrimination (AUC) for leak prediction, reported with confidence intervals. No changes to standard care will be made.
Why it matters
Potential benefit: If successful, the approach could improve personalized risk estimation for leaks and inform intraoperative decision-making.
How similar studies have gone: Previous machine-learning models for AL have shown promise but require prospective validation and integration with clinician judgment.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Age 18 years or older. * Undergoing colorectal surgery with creation of an anastomosis. * Indication for surgery: malignancy or suspected malignancy, diverticulitis, ischemia, perforation, bleeding, volvulus, stenosis or obstruction, iatrogenic injury, or inflammatory bowel disease. * Availability of general informed consent. Exclusion Criteria: * Age younger than 18 years. * Refusal to participate in the study. * Incomplete datasets
Where it's running
-
Kantonsspital Baselland (KSBL)
Liestal, Basel-Landschaft, Switzerland Recruiting -
Clarunis Universitäres Bauchzentrum Basel
Basel, Canton of Basel-City, Switzerland Recruiting
Study contacts
- Principal investigator: Stephanie G Taha-Mehlitz, MD — Universitätsspital Basel - Bauchzentrum
- Study coordinator: Stephanie G Taha-Mehlitz, MD
- Email: stephanie.taha@usb.ch
- Phone: +4161 777 73 09
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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.