[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"conditionNormalized\":\"thromboembolic-risk\",\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:thromboembolic-risk":32},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,1,0,[8],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":14,"acronym":15,"eligibilityCriteria":16,"healthyVolunteers":17,"sex":18,"minAge":19,"maxAge":20,"enrollmentInfo":21,"targetDuration":24,"studyType":25,"phases":4,"briefSummary":26,"conditions":27,"keywords":37,"overallStatus":47,"whyStopped":4,"lastUpdateSubmitDate":48,"lastUpdatePostDateStruct":49,"startDateStruct":52,"completionDateStruct":54,"leadSponsor":56,"locationsCount":5},"100626909","thromboembolic-risk-associated-to-high-atrial-fibrillation-risk-100626909",false,"NCT07441759","throMboembolic Risk Associated To High atrIal Fibrillation riSk","Economic, Clinical, and Societal Impact of Early Thromboembolic -Risk Detection in High-Risk Atrial Fibrillation: A Model -Based Evaluation of the MATHIAS Strategy.","MATHIAS","Inclusion Criteria (PREFATE study): assessed at baseline\n\n* Adults aged 65-95 years without prior AF and at High risk of AF, according to the risk score validated in the AFRICAT (Atrial Fibrilation Research in CATalonia) study. This scale considers the following variables for risk calculation: sex, age, weight, cardiac rate and CHA2DS2-VASc (congestive heart failure, hypertension, age ≥75 (doubled), diabetes mellitus, prior stroke or transient ischemic attack (doubled), vascular disease, age 65-74, female) score.\n* with active records in the HCC3\u002FCMBD systems\n* CHA2DS2-VASc score≥2.\n* Ability to use a smart phone (or at least the caregiver).\n\nExclusion Criteria: Patients with the following conditions will be excluded (exclusion criteria):\n\n* Previous diagnosis of AF.\n* Previous diagnosis of stroke.\n* Severe cognitive impairment, with a score on the Global Deterioration Scale (GDS)≥3.\n* Severe functional impairment, with a Barthel score ≤60, or modified Rankin score≥4.\n* Active anticoagulant treatment at the inclusion.\n* Vital prognosis less than 1 year.\n* Pacemaker carriers.",true,"ALL","65 Years","95 Years",{"count":22,"type":23},1000,"ESTIMATED","2 Years","OBSERVATIONAL","Cardiovascular diseases are the leading cause of mortality from treatable conditions in the European Union and the second from preventable causes, with a standardized mortality rate of 257.8 deaths per 100,000 inhabitants. In 2022, more than 1.11 million deaths in individuals under 75 years could have been avoided. Atrial fibrillation (AF) and major adverse cardiovascular events (MACE) are highly prevalent in the elderly and generate substantial healthcare costs. AF significantly increases the risk of MACE and is projected to rise markedly in the coming decades.\n\nIn Europe, AF prevalence is expected to increase 2.5-fold over the next 50 years, with a lifetime risk of 1 in 3-5 individuals after age 55. AF-related strokes are projected to increase by 34%, and ischemic strokes in individuals over 80 are expected to triple between 2016 and 2060. Additionally, a 27% increase is anticipated among stroke survivors who subsequently develop AF or related conditions. AF substantially impacts morbidity, mortality, and disease progression, and early detection and treatment are crucial to prevent severe outcomes.\n\nEuropean action plans (2018-2030) and the 2024 ESC\u002FESO guidelines emphasize early detection and management of AF in primary care. Although several AF prediction models exist, their integration into clinical practice remains challenging. AF represents a clinical continuum, with thrombotic risk present even before arrhythmia onset. High-risk patients for AF also show a high incidence of MACE, defined as a composite of myocardial infarction, stroke, systemic embolic events, and cardiovascular death.\n\nThe proposed strategy involves developing and clinically validating an Artificial Intelligence (AI) model to improve early thrombotic risk prediction in patients at high risk of AF, using MACE as the primary outcome. This model aims to outperform the traditional CHA₂DS₂-VASc score by incorporating both classical and emerging clinical factors. The estimated timeline from clinical validation to commercialization is approximately 48 months.\n\nAI-based prediction is expected to enable personalized treatment, reduce the incidence of MACE, hospitalizations, and disability, and improve cost-effectiveness, ultimately decreasing the social and economic burden of AF and stroke in Europe.",[28,29,30,31,32,33,34,35,36],"MACE","Atrial Fibrillation (AF)","Quality-adjusted Life-years","Electronic Health Records","Thromboembolic Risk","Cost-effectiveness Analysis","Artificial Intelligence (AI)","Cardio Vascular Disease","Cardio-cerebrovascular Disease",[38,39,40,41,42,43,44,45,46],"Atrial fibrillation","Thromboembolic risk","Artificial intelligence","Stroke","Major Adverse Cardiovascular Events","Sex differences","Primary care","Cost-effectiveness analysis","Quality-adjusted life-years","NOT_YET_RECRUITING","2026-02-27",{"date":50,"type":51},"2026-03-02","ACTUAL",{"date":53,"type":23},"2026-07-06",{"date":55,"type":23},"2028-12-31",{"name":57,"class":58},"Fundacio d'Investigacio en Atencio Primaria Jordi Gol i Gurina","OTHER"]