See if a computer program can help diagnose cholestasis in newborns using parent-provided stool images
Official title: The Dirty Nappy Study: Development and Evaluation of a Machine Learning Algorithm for the Early Detection of Cholestasis and Biliary Atresia From Parent-Provided Images of Dirty Nappies
Run by Birmingham Women's and Children's NHS Foundation Trust · NCT07697872 · Data updated 2026-11-12
A computer program is being tested to see if it can correctly identify cholestasis and biliary atresia in newborns by analyzing stool images provided by parents.
Quick facts
| Study type | Observational |
|---|---|
| Ages | Any age to 11 Years |
| Sex | All |
| Enrollment | 5350 (estimated) |
| Sponsor | Birmingham Women's and Children's NHS Foundation Trust Academic / other |
| Locations | 1 site (Birmingham) |
| Status | Recruiting |
| Started | April 1, 2025 |
| Main results expected | September 30, 2026 |
| Study ends | September 30, 2026 |
| Registry record updated | July 13, 2026 |
| Trial ID | NCT07697872 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Infants under 6 months referred for suspected cholestasis, including those in prospective and retrospective arms, and healthy newborns in the non-cholestasis arm.
✕Probably not a fit
Some infants may not benefit if the algorithm misclassifies cases or if stool image quality is insufficient for analysis.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This observational study tests a machine-learning algorithm designed to diagnose neonatal cholestasis, including biliary atresia, using parent-submitted stool images. It combines retrospective data and two prospective arms to evaluate diagnosis accuracy and the feasibility of stool-image screening. The study recruits infants from birth at four UK hospitals and compares the algorithm’s sensitivity and specificity against confirmed clinical diagnoses. Data collection includes both real-time image capture and historical images with corresponding medical records. The approach aims to determine whether a noninvasive, parent-driven screening method could aid early detection.
Why it matters
Potential benefit: If successful, the approach could enable earlier, noninvasive screening for cholestasis in newborns, potentially speeding diagnosis and treatment.
How similar studies have gone: Similar machine-learning approaches using noninvasive data have shown promise in pilot studies, but this exact stool-image method is exploratory.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: All Arms: Informed Consent: Parents/guardians can give informed consent for their child's participation in the study and can understand written English. 1. Retrospective Cholestasis Arm: All infants, of any gestation, male and female who were referred to Birmingham Liver Unit from any hospital for investigation of suspected cholestasis within the previous 10 years before the study launch. At the time of the referral to Birmingham Liver Unit the children were under the age of 6 months and the children were referred before the start date of the study. 2. Prospective Cholestasis Arm: All infants, of any gestation, male and female who were referred to Birmingham Liver Unit from any hospital for investigation of suspected cholestasis after the study launch. At the time of the referral to Birmingham Liver Unit the children were under the age of 6 months. 3. Prospective Non-Cholestasis Arm All infants, of any gestation, male and female \& aged less than 28 days, not thought to be cholestatic at the time of recruitment \& with the birth registered at any of the participating hospital trusts. Exclusion Criteria: If the inclusion criteria as outlined are met, there is no exclusion criteria.
Where it's running
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Birmingham Women's and Children's NHS Foundation Trust
Birmingham, United Kingdom Recruiting
Similar studies
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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.