[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100639433":3},{"organization":4,"armGroups":7,"interventions":8,"overallOfficials":7,"centralContacts":24,"locations":33,"responsibleParty":56,"collaborators":7,"id":60,"slug":61,"hasResults":62,"nctId":63,"briefTitle":64,"officialTitle":65,"acronym":66,"eligibilityCriteria":67,"healthyVolunteers":62,"sex":68,"minAge":69,"maxAge":7,"enrollmentInfo":70,"targetDuration":7,"studyType":73,"phases":7,"briefSummary":74,"conditions":75,"keywords":80,"overallStatus":35,"whyStopped":7,"lastUpdateSubmitDate":89,"lastUpdatePostDateStruct":90,"startDateStruct":93,"completionDateStruct":95,"leadSponsor":97,"locationsCount":98},{"fullName":5,"class":6},"Marmara University Pendik Training and Research Hospital","OTHER",null,[9,14,19],{"type":6,"name":10,"description":11,"armGroupLabels":7,"otherNames":12},"GPT-4o HEART Score Calculator","OpenAI GPT-4o (model: gpt-4o-2024-11-20, temperature=0, max\\_tokens=500, response\\_format=JSON). Each patient's anonymized anamnesis text, ECG report text, troponin value, and age are submitted via a separate API call with no conversation history. Output: HEART score components (0-2 each), total score (0-10), risk group, and indeterminate status.",[13],"GPT-4o İndeks Testi",{"type":6,"name":15,"description":16,"armGroupLabels":7,"otherNames":17},"Claude HEART Score Calculator","Anthropic Claude (model: claude-sonnet-4-6, temperature=0, max\\_tokens=500, response\\_format=JSON). Identical system prompt and input format as GPT-4o. Processed independently with no cross-contamination between models. Output: same JSON schema as GPT-4o.",[18],"Claude İndeks Testi",{"type":6,"name":20,"description":21,"armGroupLabels":7,"otherNames":22},"Three-Expert Consensus HEART Score","Three emergency medicine physicians (\\>=3 years experience, HEART-score trained) independently score each anonymized record. Majority vote (2\u002F3) determines component scores; a 4th adjudicator resolves ties. Experts are blinded to LLM scores, each other's scores, and MACE outcomes.",[23],"Referans Standart",[25,30],{"name":26,"role":27,"phone":28,"phoneExt":7,"email":29},"Emir Unal, Assistant Professor","CONTACT","+905327766010","emirunal@gmail.com",{"name":31,"role":27,"phone":7,"phoneExt":7,"email":32},"Emre Kudu, associate professor","dr.emre.kudu@gmail.com",[34],{"facility":5,"status":35,"city":36,"state":36,"zip":37,"country":38,"countryCode":7,"cosmosGeoPoint":39,"geoPoint":44,"contacts":45},"RECRUITING","Istanbul","34870","Turkey (Türkiye)",{"type":40,"coordinates":41},"Point",[42,43],28.94966,41.01384,{"lat":43,"lon":42},[46,49,52,54],{"name":47,"role":27,"phone":48,"phoneExt":7,"email":29},"Emir ünal","05327766010",{"name":50,"role":51,"phone":7,"phoneExt":7,"email":7},"Emre Kudu","SUB_INVESTIGATOR",{"name":53,"role":51,"phone":7,"phoneExt":7,"email":7},"Erhan Altunbas",{"name":55,"role":51,"phone":7,"phoneExt":7,"email":7},"Sinan Karacabey",{"type":57,"investigatorFullName":58,"investigatorTitle":59,"investigatorAffiliation":5,"oldNameTitle":7,"oldOrganization":7},"PRINCIPAL_INVESTIGATOR","Emir Ünal","MD, Assistant Professor","100639433","diagnostic-accuracy-of-gpt-4o-and-claude-for-heart-score-calculation-in-chest-pain-100639433",false,"NCT07626060","Diagnostic Accuracy of GPT-4o and Claude for HEART Score Calculation in Chest Pain","Diagnostic Accuracy of Large Language Models (GPT-4o and Claude) in HEART Score Calculation and 30-Day MACE Prediction in Emergency Department Chest Pain Patients: A Prospective Observational Validation Study Against Three-Expert Consensus","LLM-HEART","INCLUSION CRITERIA:\n\n* Age \\>=18 years\n* Chief complaint of non-traumatic chest pain at the emergency department\n* Written informed consent obtained from the patient or legally authorized representative\n* Availability for 30-day follow-up (reachable by telephone and\u002For actively registered in the e-Nabiz national health database)\n\nEXCLUSION CRITERIA:\n\n* Traumatic chest pain etiology\n* ST-elevation myocardial infarction (STEMI) at presentation requiring immediate reperfusion protocol\n* Refusal or subsequent withdrawal of informed consent\n* Inability to complete the mandatory 30-day follow-up period\n\nWITHDRAWAL CRITERIA:\n\n* Patient or representative requests data withdrawal after initial consent\n* Administrative identification of retrospective data entry after enrollment","ALL","18 Years",{"count":71,"type":72},690,"ESTIMATED","OBSERVATIONAL","This prospective observational diagnostic accuracy study evaluates whether large language models (LLMs) - GPT-4o (OpenAI, gpt-4o-2024-11-20) and Claude (Anthropic, claude-sonnet-4-6) - can accurately calculate HEART scores from unstructured Turkish clinical notes and predict 30-day major adverse cardiac events (MACE) in emergency department patients presenting with non-traumatic chest pain.\n\nThe study will enroll 600 consecutive adult patients. For each patient, the same anonymized data (free-text anamnesis, ECG report text, troponin value, and age) will be independently processed by both LLMs via separate API calls with deterministic settings (temperature=0, JSON format). A three-expert consensus HEART score - derived through blinded independent scoring by three emergency medicine physicians with majority-vote adjudication - serves as the reference standard for agreement analysis. Actual 30-day MACE (all-cause death, AMI Type 1\u002F2\u002F4b, unplanned revascularization) determined via national health database and telephone follow-up serves as the outcome for diagnostic accuracy analysis.\n\nA secondary documentation-quality sub-study will quantify how spontaneously Turkish emergency anamnesis notes capture HEART score parameters.",[76,77,78,79],"Emergency Medicine","Artificial Intelligence (AI)","Artificial Intelligence (AI) in Diagnosis","Chest Pain Rule Out Myocardial Infarction",[81,82,83,84,85,86,87,88],"Large Language Model","GPT-4o","Claude Sonnet","Emergency Department","Diagnostic Accuracy","Medical Informatics","Physician vs AI","HEART score","2026-06-22",{"date":91,"type":92},"2026-06-23","ACTUAL",{"date":94,"type":72},"2026-06",{"date":96,"type":72},"2027-06",{"name":5,"class":6},1]