Optimize Risk Prediction After Myocardial Infarction: The ORACLE Study

Background. Myocardial infarction (MI) is a leading cause of death worldwide. After MI, longterm antithrombotic therapy is crucial to prevent recurrent events, but increases bleeding, that also impacts morbidity and mortality. Giving these competing risks prediction tools to forecast ischemic and bleeding are of paramount importance to inform clinical decisions, but their current precision is limited. Improve events prediction, by discovering novel and innovative markers of risk would have a tremendous impact on therapeutic decisions and patients' outcome. Objectives. Discover novel "computational biomarkers" of risk and improve current standards of risk prediction by using innovative multidimensional information from wearable devices, biomarkers, behavioural patterns and non-invasive imaging, integrated through artificial intelligence computation. Outcomes. The primary outcomes of interest for this analysis are bleeding and ischemic events occurring in or outside the hospital at longest available follow-up. Bleeding will be categorised according to the Bleeding Academic Research Consortium (BARC) definition. The occurrence of major adverse cardiovascular events (MACE), a composite of cardiovascular death, MI, definite stent thrombosis and stroke will be collected according to the Academic Research Consortium-2 classification.

NCT Number	NCT06993415
Lead Sponsor	Fundación Pública Andaluza para la Investigación de Málaga en Biomedicina y Salud Collaborators: European Research Council
Conditions	Myocardial Infarction (MI)
Enrollment	750 participants
Start Date	2025-06
Primary Completion	2028-02 (estimated)
Study Completion	2028-02 (estimated)
Updated on ClinicalTrials.gov	2025-06-10