Artificial Intelligence Models to Predict Clinically Relevant Cardiovascular Outcomes (PERCARD)

August 25, 2025 updated by: Centro Cardiologico Monzino

Development of Artificial Intelligence Models to Predict Intrahospital Atrial Fibrillation and Long-term Coronary Event Recurrence in High-risk Patients: PerCard Study

Atrial fibrillation (AF) is a frequent and clinically relevant problem among the events that may occur during the hospitalization period in patients with cardiovascular disease. AF, indeed, is a determinant or aggravating condition of serious adverse events, such as myocardial infarction, heart failure, and thromboembolic stroke. The occurrence of AF in hospitalized patients, such as those admitted for coronary intervention, results in prolonged length of hospitalization, increased likelihood of discharge on anticoagulants, and increased 30-day risk of bleeding. It is noteworthy that while the incidence of AF in the general population is about 1-2 cases per 1000 people per year, this is much higher in patients hospitalized for acute myocardial infarction (AMI) (about 10% over the hospitalization period) or in patients undergoing coronary artery bypass grafting (CABG) (about 25% over the hospitalization period). Thus, identifying patients at high risk of AF during the hospitalization period could allow experimental testing of the efficacy and safety of preventive interventions (e.g., tailored anesthetic or surgical approaches, drug-prevention, etc.). It can be hypothesized that the clinical and nonclinical variables useful in estimating the risk of AF will change depending on the type of patients and that the identification and integration of these variables will require more complex predictive analysis systems than the regression models classically used to develop risk scores.

On the other hand, the risk of recurrence of coronary events throughout the first years after CABG remains high (about 20% at 5 years) despite effective revascularization and early secondary prevention.Although some scores have been developed for estimating the risk of coronary event recurrence in secondary prevention using multivariate regression models, these algorithms consider a limited number of predictors, do not take into account possible interactions between different factors, and their actual predictive ability is not reported in the literature.

With advances in Artificial Intelligence (AI) technology together with the rapid development of digital clinical datasets, machine learning has the potential to analyze substantial amounts of data and recognize patterns to predict AF onset and recurrence of coronary events within a defined time horizon (e.g., in-hospital event) in selected populations in a way that improves the predictive ability of conventional methods.

Study Overview

Status

Completed

Conditions

Intervention / Treatment

Detailed Description

PerCard is a retrospective and prospective observational study. The study aims to develop and validate models for prediction of intrahospital AF and recurrence of coronary events in a long-term follow-up using Artificial Intelligence.

The development and internal validation of predictive models of AF involve two retrospective cohorts:

  • Cohort A: 1258 patients underwent CABG at Centro Cardiologico Monzino (CCM) between 2002 and 2016
  • Cohort B: 2445 patients admitted for AMI STEMI or NSTEMI to CCM between 2010 and 2018

The development and internal validation of predictive models of coronary event recurrence in long-term follow-up involve a third retrospective cohort:

-Cohort C: 1248 patients underwent CABG at CCM between 2002 and 2014 .

External validation of the predictive models of in-hospital AF involves a cohort of patients admitted with AMI STEMI or NSTEMI, who will be prospectively enrolled at Coronary Intensive Care Unit of Centro Cardiologico Monzino.

In the different prediction models, clinical and instrumental variables specific to patients with AMI (e.g., infarcted area), variables that are common to patients with any form of coronary revascularization (e.g., how many and which coronary vessels have been revascularized), or variables that are common to patients and individuals without established coronary artery disease (e.g., age, sex, history of hypertension, particular gene polymorphisms related to AF, signals from the ECG, etc.) will be included, where available.

In addition, the contribution of 16 gene polymorphisms associated with predisposition to intrahospital onset of AF has been previously evaluated in cohort A and will be evaluated and compared in the prospective cohort at the Immunology and Functional Genomics Research Unit of Centro Cardiologico Monzino.

Study Type

Observational

Enrollment (Actual)

273

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • Finland
    • Pirkanmaa
      • Tampere, Pirkanmaa, Finland, 33100
        • Tampere University
  • Germany
    • Ludwigsburg
      • Ludwigsburg, Ludwigsburg, Germany, 71638
        • Protestant University of Apllied Sciences Ludwigsburg
  • Italy
    • Milano
      • Milan, Milano, Italy, 20138
        • Centro Cardiologico Monzino
      • Milan, Milano, Italy, 20133
        • Politecnico di Milano

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Non-Probability Sample

Study Population

500 patients admitted to the Coronary Intensive Care Unit of the CCM for AMI (STEMI or NSTEMI)

Description

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

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
Prospective cohort
Patients who will be admitted for AMI (STEMI or NSTEMI) at Intensive Care Unit of Centro Cardiologico Monzino
Diagnostic test: Blood withdrawal
Optional collection of 5 mL of blood to assess the contribution of 16 gene polymorphisms AF-associated

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Validation of the intrahospital AF prediction model in the prospective cohort
Time Frame: 1 year
External validation ("narrow external validation") of the intrahospital AF prediction model in a cohort of patients who will be admitted for AMI (STEMI or NSTEMI) at the CCM.
1 year

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Genetic evaluation of polymorphisms associated with Atrial Fibrillation
Time Frame: 1 year
Evaluation and comparison of the contribution of 16 AF predisposition-associated gene polymorphisms on the intrahospital onset of arrhythmia between patients who underwent CABG and patients with AMI.
1 year

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Centro Cardiologico Monzino

Collaborators

Tampere University
Politecnico di Milano
Protestant University of Applied Sciences (Ludwigsburg, Germany)

Investigators

  • Principal Investigator: Claudio Tondo, MD, PhD, IRCCS Centro Cardiologico Monzino

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

February 6, 2023

Primary Completion (Actual)

June 30, 2025

Study Completion (Actual)

June 30, 2025

Study Registration Dates

First Submitted

February 21, 2025

First Submitted That Met QC Criteria

February 21, 2025

First Posted (Actual)

February 26, 2025

Study Record Updates

Last Update Posted (Estimated)

August 26, 2025

Last Update Submitted That Met QC Criteria

August 25, 2025

Last Verified

August 1, 2025

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • CCM1860

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

product manufactured in and exported from the U.S.

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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