PACT Involvement in Cardiology Patients
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: ML-based intervention.
- Who it may be relevant to
- Registry conditions: Machine Learning, Cardiovascular Outcome, Pediatric Palliative Care, Pediatric Cardiology. Basic parameters: up to 18 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Canada
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Unsure about the terms? Read our patient guide →
Official title
Early PACT Involvement in Cardiology Patients Using Machine Learning
Overview
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.
Detailed description
At The Hospital for Sick Children (SickKids), the collaboration between cardiology and palliative care is much stronger than other centers, with routine involvement in patients being considered for heart transplant. Despite this, earlier involvement of palliative care would be advantageous. Our cardiology co-investigators identified patients who would benefit from earlier palliative care team involvement as those receiving advanced heart therapies (defined as ventricular assist device (VAD) and being wait listed for heart transplant) and those who die. The study team created a clinical deployment environment named SickKids Enterprise-wide Data in Azure Repository (SEDAR). \[1\] SEDAR is a modular and robust approach to deliver foundational data that is re-usable across multiple ML projects. It offers validated EHR data in a standardized and curated schema. ML is a promising approach to identify cardiac patients at the highest risk of these serious cardiac outcomes who may benefit from earlier palliative care team involvement. To assess the effectiveness of this approach, patient outcomes will be compared pre- and post-deployment of the ML model. The pre-period will include patients admitted for a 12-month period before deployment (starting 15 months prior to deployment). The post-period will include patients admitted for a 12-month period following deployment starting 3 months post-deployment start.
Interventions
- Other 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.
Primary outcome measures
- Proportion of admissions with PACT consultation within the next three months among admissions without PACT involvement in the previous 100 days [Time frame: Time of enrolment to 3 months]
Secondary outcome measures (4)
- PACT consultation or visit within the next three months among those with a positive model prediction [Time frame: Time of enrolment to 3 months]
- Time to PACT consultation or visit among those seen by PACT [Time frame: Time of enrolment to 3 months]
- Death in the ICU [Time frame: Time of enrolment to 3 months]
- Documentation of goals of care [Time frame: Time of enrolment to 3 months]
Eligibility criteria
Inclusion criteria
- Pediatric inpatients admitted to cardiology
Exclusion criteria
- Expected to be discharged prior to midnight on the day of admission
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Allocation
- N/A
- Model
- Single group
- Masking
- Open label
- Primary purpose
- Supportive care
Study locations
Canada · 1 center
- The Hospital for Sick Children — Toronto
Publications
- Patel P, Robinson PD, Phillips R, Baggott C, Devine K, Gibson P, Guilcher GMT, Holdsworth MT, Neumann E, Orsey AD, Spinelli D, Thackray J, van de Wetering M, Cabral S, Sung L, Dupuis LL. Treatment of breakthrough and prevention of refractory chemotherapy-induced nausea and vomiting in pediatric cancer patients: Clinical practice guideline update. Pediatr Blood Cancer. 2023 Aug;70(8):e30395. doi: 1 PMID 37178438
Identifiers
NCT: NCT06886529 · 3433