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NCT Number: NCT06993415

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.

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Key information

Conditions

Myocardial Infarction (MI) Cardiovascular Diseases Heart Diseases Infarction Ischemia Myocardial Infarction Myocardial Ischemia Necrosis Pathologic Processes Pathological Conditions, Signs and Symptoms Vascular Diseases

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Hospital Universitario Virgen de la Victoria

Málaga, 29010, Spain

Location status: Recruiting

Location contact

Francesco Costa, MD

CONTACT

[email protected]

+34951030435

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

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

Treatment and study plan

Data Collection

Other

The ORACLE program is a prospective, deep phenotyping, study based on multimodal information and artificial intelligence computation. We will prospectively collect in-hospital and out-of-hospital data of a large cohort of patients presenting with MI, including data from wearable devices recording continuous ECG, interstitial-fluids, non-invasive blood pressure and mobility, behavioural patterns from a dedicated mobile application, blood and urine biomarkers and non-invasive imaging. We will leverage on AI, using statistical learning methods and neural networks, to explore patterns and higher order interactions within the data to provide novel "computational biomarkers" of ischemic and bleeding risk.

Other names: Data collection from biological samples, wearable devices and tests

Primary outcomes

  1. Frequency and severity of bleeding and ischemic events

    Time frame: 8 months inclusion and 12 months follow-up after end of study

    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.

Secondary outcomes

  1. Number of death, stroke, recurrent MI, stent thrombosis, heart failure, hospitalization

    Time frame: 8 months inclusion and 12 months follow-up after end of study

    Death will be defined as death from cardiovascular causes or cerebrovascular causes and any death without another known cause. Stroke will be defined as an acute new neurological deficit ending in death or lasting >24 hours not due to another readily identifiable cause such as trauma. Recurrent MI is defined according to the fourth universal definition of MI. Stent thrombosis will be classified as definite, probable or possible according to the Academic Research Consortium (ARC) definition. New-onset heart failure requiring re-hospitalisation or unplanned medical contact for heart failure symptoms will be evaluated. Recurrent hospitalization for acute coronary syndrome, unstable angina or clinically-indicated urgent revascularization will also be evaluated.

Other outcomes

  1. Quality life and adherence to treatment

    Time frame: 8 months inclusion and 12 months follow-up after end of study

    Patients' quality of life and adherence to treatment will be evaluated with:

    • Health mobility and mental scales (i.e. EQ-5D-5L and SF-12v2)
    • Anginal status according to the Seattle Angina questionnaire (SAQ)
    • Functional status according to the Kansas City Cardiomiopathy questionnaire (KCCQ)
    • Modified Borg Dyspnoea Scale

Study contacts

Contact information is provided by the study sponsor or research team.

Dr. Francesco Costa

CONTACT

[email protected]

+34

Sponsors and collaborators

Lead sponsor

Fundación Pública Andaluza para la Investigación de Málaga en Biomedicina y Salud

Other

Collaborators

  • European Research Council

Registry information

Official study title

Optimize Risk Prediction After Myocardial Infarction Through Artificial Intelligence and Multidimensional Evaluation: The ORACLE Study

Acronym: ORACLE

Important dates

Study start
2025
Primary completion
2028
Study completion
2028
First posted
May 28, 2025
Registry last updated
Jun 10, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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