Clinical Research Directory
Browse clinical research sites, groups, and studies.
Vomiting Prevention in Children With Cancer
Sponsor: The Hospital for Sick Children
Summary
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. The main questions it aims to answer are whether an ML model predicting the risk of vomiting within the next 96 hours will: Primary 1\. Reduce the proportion with any vomiting within the 96-hour window Secondary 1. Reduce the number of vomiting episodes 2. Increase the proportion receiving care pathway-consistent care 3. Impact on number of administrations and costs of antiemetic medications Newly 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.
Official title: Prevention of Vomiting in Pediatric Oncology Inpatients Using Machine Learning
Key Details
Gender
All
Age Range
Any - Any
Study Type
INTERVENTIONAL
Enrollment
1332
Start Date
2025-03-18
Completion Date
2027-03-18
Last Updated
2026-03-05
Healthy Volunteers
No
Interventions
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.
Locations (1)
The Hospital for Sick Children
Toronto, Ontario, Canada