optimize risk prediction after myocardial infarction: the oracle study

Conditions: Myocardial Infarction (MI)

Summary: 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.


Eligibility 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

Keywords: myocardial infarction (mi) risk prediction artificial intelligence oracle study computational biomarkers ischemic events bleeding events prospective observational study