[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100584216":3},{"organization":4,"armGroups":7,"interventions":14,"overallOfficials":21,"centralContacts":35,"locations":46,"responsibleParty":62,"collaborators":39,"id":65,"slug":66,"hasResults":67,"nctId":68,"briefTitle":69,"officialTitle":70,"acronym":39,"eligibilityCriteria":71,"healthyVolunteers":67,"sex":72,"minAge":39,"maxAge":39,"enrollmentInfo":73,"targetDuration":39,"studyType":76,"phases":77,"briefSummary":79,"conditions":80,"keywords":84,"overallStatus":48,"whyStopped":39,"lastUpdateSubmitDate":89,"lastUpdatePostDateStruct":90,"startDateStruct":93,"completionDateStruct":95,"leadSponsor":97,"locationsCount":98},{"fullName":5,"class":6},"The Hospital for Sick Children","OTHER",[8],{"label":9,"type":10,"description":11,"interventionNames":12},"ML model","EXPERIMENTAL","ML model to predict the risk of vomiting within the next 96 hours.",[13],"Other: ML-based intervention",[15],{"type":6,"name":16,"description":17,"armGroupLabels":18,"otherNames":19},"ML-based intervention","For each patient, a ML model will predict the risk of vomiting within the next 96 hours. Patients will then receive care pathway-consistent interventions based on the ML model predictions.",[9],[20],"Machine learning model",[22,25,27,29,31,33],{"name":23,"affiliation":5,"role":24},"Lillian Sung, MD, PhD","PRINCIPAL_INVESTIGATOR",{"name":26,"affiliation":5,"role":24},"Lee Dupuis, RPh, PhD",{"name":28,"affiliation":5,"role":24},"Priya Patel, PharmD",{"name":30,"affiliation":5,"role":24},"Adam Yan, MD, MBI",{"name":32,"affiliation":5,"role":24},"Lawrence Guo, PhD",{"name":34,"affiliation":5,"role":24},"Santiago Arciniegas, MSc",[36,41],{"name":23,"role":37,"phone":38,"phoneExt":39,"email":40},"CONTACT","416-813-5287",null,"lillian.sung@sickkids.ca",{"name":42,"role":37,"phone":43,"phoneExt":44,"email":45},"Agata Wolochacz, BMSc","416-813-7654","309976","agata.wolochacz@sickkids.ca",[47],{"facility":5,"status":48,"city":49,"state":50,"zip":51,"country":52,"countryCode":53,"cosmosGeoPoint":54,"geoPoint":59,"contacts":60},"RECRUITING","Toronto","Ontario","M5G1X8","Canada","CA",{"type":55,"coordinates":56},"Point",[57,58],-79.39864,43.70643,{"lat":58,"lon":57},[61],{"name":23,"role":37,"phone":38,"phoneExt":39,"email":40},{"type":24,"investigatorFullName":63,"investigatorTitle":64,"investigatorAffiliation":5,"oldNameTitle":39,"oldOrganization":39},"Lillian Sung","Chief Clinical Data Scientist, Paediatric Oncologist","100584216","vomiting-prevention-in-children-with-cancer-100584216",false,"NCT06886451","Vomiting Prevention in Children With Cancer","Prevention of Vomiting in Pediatric Oncology Inpatients Using Machine Learning","Inclusion Criteria:\n\n* All pediatric patients admitted to the oncology service at SickKids\n\nExclusion Criteria:\n\n* Pediatric patients admitted to the oncology service at SickKids that are discharged prior to prediction time","ALL",{"count":74,"type":75},1332,"ESTIMATED","INTERVENTIONAL",[78],"NA","The goal of this single arm trial is to learn if a machine learning (ML) model predicting the risk of vomiting within the next 96 hours will impact vomiting outcomes in inpatient cancer pediatric patients.\n\nThe main questions it aims to answer are whether an ML model predicting the risk of vomiting within the next 96 hours will:\n\nPrimary\n\n1\\. Reduce the proportion with any vomiting within the 96-hour window\n\nSecondary\n\n1. Reduce the number of vomiting episodes\n2. Increase the proportion receiving care pathway-consistent care\n3. Impact on number of administrations and costs of antiemetic medications\n\nNewly admitted participants will have a ML model predict the risk of vomiting within the next 96 hours according to their medical admission information. The prediction will be made at 8:30 AM following admission. Pharmacists will be charged with bringing information about patients' vomiting risk to the attention of the medical team and implementing interventions.",[81,82,83],"Chemotherapy Induced Nausea and Vomiting","Quality of Life (QOL)","Pediatric Cancer",[85,86,87,88],"Vomiting","Machine learning","Quality of life","Pediatric oncology","2026-03-03",{"date":91,"type":92},"2026-03-05","ACTUAL",{"date":94,"type":92},"2025-03-18",{"date":96,"type":75},"2027-03-18",{"name":5,"class":6},1]