[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100053278":3},{"organization":4,"armGroups":7,"interventions":10,"overallOfficials":10,"centralContacts":10,"locations":18,"responsibleParty":41,"collaborators":43,"id":47,"slug":48,"hasResults":49,"nctId":50,"briefTitle":51,"officialTitle":52,"acronym":10,"eligibilityCriteria":53,"healthyVolunteers":54,"sex":55,"minAge":10,"maxAge":56,"enrollmentInfo":57,"targetDuration":10,"studyType":60,"phases":10,"briefSummary":61,"conditions":62,"keywords":66,"overallStatus":20,"whyStopped":10,"lastUpdateSubmitDate":75,"lastUpdatePostDateStruct":76,"startDateStruct":79,"completionDateStruct":81,"leadSponsor":83,"locationsCount":84},{"fullName":5,"class":6},"Birmingham Women's and Children's NHS Foundation Trust","OTHER",[8,12,15],{"label":9,"type":10,"description":11,"interventionNames":10},"Retrospective Cholestasis Cohort",null,"This group includes infants who were referred to a specialist paediatric liver unit for suspected cholestasis within the past 10 years. This cohort provides historical data to evaluate the machine-learning algorithm's performance using existing images and clinical outcomes. No new interventions or prospective data collection occur in this group.",{"label":13,"type":10,"description":14,"interventionNames":10},"Prospective Cholestasis Cohort","This group includes infants who are newly referred for cholestasis investigation to a specialist paediatric liver unit during the study period. Parents will provide stool images at 14, 21, and 28 days of life, 3 months, and 6 months using a smartphone. These images will be analysed by a machine-learning algorithm to assess whether early stool image screening can help detect cholestasis, including biliary atresia. Participants will also share feedback on their experience with this screening method. This cohort provides real-time prospective data to train and validate the algorithm.",{"label":16,"type":10,"description":17,"interventionNames":10},"Prospective Non-Cholestasis Cohort","This group consists of newborns born at specified hospitals who are the time of recruitment are not thought to be cholestatic. Parents will submit stool images at 14, 21, and 28 days of life, 3 months, and 6 months to provide a large dataset of normal stool images. This cohort serves as a control group, ensuring that the algorithm can distinguish between healthy and abnormal stool patterns.",[19],{"facility":5,"status":20,"city":21,"state":10,"zip":10,"country":22,"countryCode":23,"cosmosGeoPoint":24,"geoPoint":29,"contacts":30},"RECRUITING","Birmingham","United Kingdom","UK",{"type":25,"coordinates":26},"Point",[27,28],-1.89983,52.48142,{"lat":28,"lon":27},[31,36,39],{"name":32,"role":33,"phone":34,"phoneExt":10,"email":35},"Girish Gupte","CONTACT","+44 121 333 9999","girishgupte@nhs.net",{"name":37,"role":33,"phone":10,"phoneExt":10,"email":38},"Suzanne Peters","suzanne.peters2@nhs.net",{"name":32,"role":40,"phone":10,"phoneExt":10,"email":10},"PRINCIPAL_INVESTIGATOR",{"type":42,"investigatorFullName":10,"investigatorTitle":10,"investigatorAffiliation":10,"oldNameTitle":10,"oldOrganization":10},"SPONSOR",[44],{"name":45,"class":46},"Elixir AI","INDUSTRY","100053278","the-dirty-nappy-study-100053278",false,"NCT07697872","The Dirty Nappy Study","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","Inclusion Criteria:\n\nAll Arms:\n\nInformed Consent: Parents\u002Fguardians can give informed consent for their child's participation in the study and can understand written English.\n\n1. Retrospective Cholestasis Arm:\n\n   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.\n2. Prospective Cholestasis Arm:\n\n   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.\n3. 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.\n\nExclusion Criteria:\n\nIf the inclusion criteria as outlined are met, there is no exclusion criteria.",true,"ALL","11 Years",{"count":58,"type":59},5350,"ESTIMATED","OBSERVATIONAL","This observational study evaluates whether a machine-learning algorithm, a computer program that learns patterns from data, can accurately diagnose cholestasis in newborns. Cholestasis refers to reduced or blocked bile flow from the liver, which can lead to liver damage. A severe form of cholestasis is biliary atresia, a condition where the bile ducts are damaged or absent, requiring early treatment to prevent long-term harm.\n\nThe study involves infants from birth, both healthy and those potentially affected by cholestasis, recruited from four UK hospitals. It addresses two primary aims:\n\n* Accuracy of Diagnosis: Can the machine-learning algorithm accurately identify cholestasis and biliary atresia using parent-provided stool images? This will be assessed by measuring sensitivity (the ability to correctly detect true cases) and specificity (the ability to correctly identify infants without the condition).\n* Feasibility of Screening: Is using parent-provided images a feasible and acceptable screening method for early detection?\n\nTo evaluate these aims, researchers will compare two groups:\n\n* Infants with abnormal stool images who are subsequently diagnosed with cholestasis or biliary atresia.\n* Infants with normal stool images who do not develop biliary atresia.\n\nThis comparison will help determine the algorithm's ability to distinguish between infants with and without these conditions.\n\nParents will:\n\n* Take smartphone photos of their baby's dirty diapers at 14, 21, and 28 days of age.\n* Upload the images for analysis by the algorithm.\n* Provide feedback on their experience with this screening process.\n\nThe study seeks to determine if parent-submitted stool images can serve as a practical early screening tool for cholestasis, potentially enabling faster diagnosis and improved outcomes for affected infants.",[63,64,65],"Cholestasis in Newborn","Biliary Atresia","Neonatal Cholestasis",[67,68,69,70,71,72,73,74],"Neonatal cholestasis","Biliary atresia diagnosis","Newborn stool analysis","infant liver disease","screening","machine learning","AI","image analysis","2026-07-06",{"date":77,"type":78},"2026-07-13","ACTUAL",{"date":80,"type":78},"2025-04-01",{"date":82,"type":59},"2026-09-30",{"name":5,"class":6},1]