ML-based intervention: ML model predicting a serious cardiac event in cardiac patients, defined as VAD procedure, being wait listed for heart transplant or death within the next three months.
The goal of this trial is to determine the effectiveness of a machine-learning (ML) model predicting a serious cardiac event within the next three months, when compared pre- versus post-deployment, in pediatric cardiac inpatients. The main questions it aims to answer are whether deployment of the ML model:
1. Increases PACT consultation within the next three months among admissions without PACT involvement in the previous 100 days
2. Increases PACT consultation or visit within the next three months among those who experience a serious cardiac event during this period
3. Decreases time to PACT consultation or visit among those seen by PACT during this period
4. Decreases the incidence of death in the intensive care unit (ICU)
5. Increases documentation of goals of care
High-risk cardiology patients will be identified by an ML model each morning. If the patient has been seen by the PACT team within the past year, the update will go to the PACT team members. If the patient hasn't been seen by the PACT team, the email will be sent to the cardiology physician in charge of the patient. This physician will decide whether a PACT consultation is necessary based on their clinical judgment. If so, a referral will be made using the usual process. Outcomes of the identified patients will be compared pre- and post-deployment.
| Facility | City | Region | Status |
|---|---|---|---|
| The Hospital for Sick Children | Toronto | Canada |
This page summarises publicly available registry data for informational purposes — not medical advice. Eligibility is determined by each study team; patients should discuss participation with their clinician.
View NCT06886529 on ClinicalTrials.gov ↗ ← All trials in Canada