Optimizing risk prediction after a heart attack (ORACLE)
Optimize Risk Prediction After Myocardial Infarction Through Artificial Intelligence and Multidimensional Evaluation: The ORACLE Study
Fundación Pública Andaluza para la Investigación de Málaga en Biomedicina y Salud · NCT06993415
This project will try to use wearable data, blood tests, imaging, and AI to better predict bleeding and repeat heart events in people who've had a heart attack and are at high risk.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 750 (estimated) |
| Ages | 18 Years and up |
| Sex | All |
| Sponsor | Fundación Pública Andaluza para la Investigación de Málaga en Biomedicina y Salud (other) |
| Locations | 1 site (Málaga, Málaga) |
| Trial ID | NCT06993415 on ClinicalTrials.gov |
What this trial studies
ORACLE is an observational study enrolling patients hospitalized for myocardial infarction who undergo invasive management and meet predefined high‑risk criteria. The study collects multidimensional data including wearable device signals, blood biomarkers, behavioral patterns, and non‑invasive imaging, linked to clinical outcomes. Advanced machine learning and AI will be applied to discover 'computational biomarkers' that predict future ischemic and bleeding events occurring in or out of hospital. The aim is to improve current risk scores and support safer, more personalized long‑term antithrombotic decisions.
Who should consider this trial
Good fit: Ideal candidates are people recently hospitalized for ST‑elevation or non‑ST‑elevation myocardial infarction or unstable angina who underwent invasive management and meet at least two predefined high‑risk criteria (for example age >65, diabetes, multivessel disease, chronic kidney disease, prior stroke or prior MI).
Not a fit: Patients without high‑risk features, those not treated invasively, or those with severe thrombocytopenia or other conditions that preclude follow‑up monitoring are unlikely to receive direct benefit from the predictive models.
Why it matters
Potential benefit: If successful, the approach could provide clinicians with more accurate personalized estimates of bleeding and ischemic risk to guide safer long‑term antithrombotic therapy.
How similar studies have performed: Similar efforts combining wearable signals, biomarkers, imaging, and AI for cardiovascular risk prediction are emerging and have shown early promise, but broad external validation is still limited.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * Patients with Myocardial Infarction (i.e. hospitalization for ST- segment elevated, non-ST-segment elevated myocardial infarction or unstable angina) undergoing invasive management and at high risk of clinical events (i.e. presence of at least two of these high risk criteria: age \>65 years, diabetes mellitus, multivessel disease, peripheral artery disease, chronic kidney disease, prior stroke anytime or prior TIA in the last 6 months, prior MI, complex PCI, Prior PCI/CABG, heart failure, BMI\>27, anticipated long term use of an oral anticoagulant, haemoglobin less than 11g/dl, spontaneous bleeding requiring hospitalization or transfusion in the past 12 months, bleeding diathesis\* active malignancy other than skin, previous spontaneous intracranial hemorrhage). * Systemic conditions associated with an increased bleeding risk (e.g. haematological disorders, including a history of or current thrombocytopaenia defined as a platelet count \<100,000/mm3 (\<100 x 10\^9/L), or any known coagulation disorder associated with increased bleeding risk. Exclusion Criteria: * Age \< 18 years * Low life expectancy (\<1 year) * Pregnant or breastfeeding women * Evidence at coronary angiography of non-significant coronary artery disease (\<30% in the left main stem or \<50% in the other coronary segments) * Subject belongs to a vulnerable population (per investigator's judgment), subject unable to read or write, or other conditions that unable the patient to fully comprehend and comply to the study procedures as per investigator's judgement
Where this trial is running
Málaga, Málaga
- Hospital Universitario Virgen de la Victoria — Málaga, Málaga, Spain (RECRUITING)
Study contacts
- Study coordinator: Dr. Francesco Costa
- Email: dottfrancescocosta@gmail.com
- Phone: +34
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.
Conditions: Myocardial Infarction, Risk prediction, Artificial Intelligence, ORACLE study, Computational Biomarkers, Ischemic Events, Bleeding Events, Prospective Observational Study