Using AI to predict heart complications in hospitalized patients
Development of Artificial Intelligence Models to Predict Intrahospital Atrial Fibrillation and Long-term Coronary Event Recurrence in High-risk Patients: PerCard Study
This study is testing if using artificial intelligence can help doctors predict heart complications in hospitalized patients who have had a heart attack or heart surgery.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 500 (estimated) |
| Ages | 18 Years and up |
| Sex | All |
| Sponsor | Centro Cardiologico Monzino Academic / other |
| Locations | 4 sites (Tampere and 3 other locations) |
| Trial ID | NCT06847100 on ClinicalTrials.gov |
What this trial studies
This observational study aims to develop and validate artificial intelligence models that predict the occurrence of atrial fibrillation (AF) and the recurrence of coronary events in patients hospitalized for acute myocardial infarction (AMI) or undergoing coronary artery bypass grafting (CABG). It utilizes both retrospective and prospective cohorts, including over 4,000 patients, to analyze clinical and genetic data. The study focuses on identifying high-risk patients during their hospital stay to improve outcomes and reduce complications associated with AF.
Who should consider this trial
Good fit: Ideal candidates for this study are adults aged 18 and older who are admitted to the Coronary Intensive Care Unit for acute myocardial infarction.
Not a fit: Patients who are already experiencing acute or permanent atrial fibrillation at the time of admission will not benefit from this study.
Why it matters
Potential benefit: If successful, this study could lead to better prediction and management of atrial fibrillation in hospitalized patients, potentially reducing complications and improving patient outcomes.
How similar studies have performed: Other studies have shown promise in using artificial intelligence for predicting cardiovascular events, making this approach both relevant and potentially impactful.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * age ≥18 years * patient admitted to the Coronary Intensive Care Unit of the CCM for AMI (STEMI or NSTEMI) * signature of informed consent to use clinical and instrumental data and, optionally, genetic data specific to the purpose of this study (gene polymorphisms presumably related to the development of AF) Exclusion Criteria: * any chronic or acute condition that prevents the patient from consciously consenting to the use of his or her personal, clinical, and instrumental data * patients already in acute or permanent AF at the time of admission
Where this trial is running
Tampere and 3 other locations
- Tampere University — Tampere, Finland (Active_not_recruiting)
- Protestant University of Apllied Sciences Ludwigsburg — Ludwigsburg, Germany (Active_not_recruiting)
- Politecnico di Milano — Milano, Italy (Active_not_recruiting)
- Centro Cardiologico Monzino — Milano, Italy (Recruiting)
Study contacts
- Principal investigator: Claudio Tondo, MD, PhD — IRCCS Centro Cardiologico Monzino
- Study coordinator: Claudio Tondo, MD, PhD
- Email: claudio.tondo@cardiologicomonzino.it
- Phone: 0258002480
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.