[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100531170":3},{"organization":4,"armGroups":7,"interventions":18,"overallOfficials":10,"centralContacts":24,"locations":34,"responsibleParty":52,"collaborators":10,"id":56,"slug":57,"hasResults":58,"nctId":59,"briefTitle":60,"officialTitle":61,"acronym":10,"eligibilityCriteria":62,"healthyVolunteers":58,"sex":63,"minAge":64,"maxAge":10,"enrollmentInfo":65,"targetDuration":68,"studyType":69,"phases":10,"briefSummary":70,"conditions":71,"keywords":10,"overallStatus":37,"whyStopped":10,"lastUpdateSubmitDate":73,"lastUpdatePostDateStruct":74,"startDateStruct":77,"completionDateStruct":79,"leadSponsor":81,"locationsCount":82},{"fullName":5,"class":6},"Beijing Anzhen Hospital","OTHER",[8,14],{"label":9,"type":10,"description":11,"interventionNames":12},"No cardiovascular adverse and cerebrovascular events (MACCE) occurred during the 1-month period",null,"No cardiovascular and cerebrovascular adverse events (MACCE)，which included cardiovascular death, all-cause mortality, nonfatal myocardial infarction, refractory angina, new onset heart failure and stroke. Follow-up visits are conducted by in-person or telephone and registration is carried out.",[13],"Combination Product: Clinical evaluation, laboratory and cardiac imaging results, medication, surgery, and any hospitalization",{"label":15,"type":10,"description":16,"interventionNames":17},"Group of major cardiovascular and cerebrovascular adverse events (MACCE) occurring during 1 month","Cardiovascular and cerebrovascular adverse events occur, the rest of the same as in the previous group",[13],[19],{"type":20,"name":21,"description":22,"armGroupLabels":23,"otherNames":10},"COMBINATION_PRODUCT","Clinical evaluation, laboratory and cardiac imaging results, medication, surgery, and any hospitalization","Examination： Electrocardiogram、 imaging examination、 X-ray, CTA, bedside echocardiography. Laboratory test results of patients, including complete blood count, D-dimer, myocardial injury markers, sST2, MPO, and other indicators. History of cardiovascular and pulmonary vascular drug therapy: Antithrombotic therapy (type, measurement) , Anticoagulation therapy (type, metering), Other drug treatments (type, measurement)",[15,9],[25,30],{"name":26,"role":27,"phone":28,"phoneExt":10,"email":29},"Xiaonan \u002F He, Professor","CONTACT","15001108399","hxndoctor@126.com",{"name":31,"role":27,"phone":32,"phoneExt":10,"email":33},"Haotian \u002F Wu, Bachelor","13966123702","wuhaotian3702@163.com",[35],{"facility":36,"status":37,"city":38,"state":39,"zip":40,"country":41,"countryCode":42,"cosmosGeoPoint":43,"geoPoint":48,"contacts":49},"Xiaonan He","RECRUITING","Beijing","Chaoyang","100029","China","CN",{"type":44,"coordinates":45},"Point",[46,47],116.39723,39.9075,{"lat":47,"lon":46},[50],{"name":51,"role":27,"phone":28,"phoneExt":10,"email":29},"Xiaonan \u002F HE, Professor",{"type":53,"investigatorFullName":54,"investigatorTitle":55,"investigatorAffiliation":5,"oldNameTitle":10,"oldOrganization":10},"SPONSOR_INVESTIGATOR","Xiao-nan He","Chief physician of Emergency and Critical Care Center of Beijing Anzhen Hospital","100531170","early-warning-and-classification-model-for-acute-non-traumatic-chest-pain-100531170",false,"NCT06196307","Early Warning and Classification Model for Acute Non-traumatic Chest Pain","A Prospective Study of Acute Nontraumatic Chest Pain - Warning and Classification","Inclusion Criteria:\n\n1. Age ≥ 18 years\n2. Symptom onset or worsening within 24 hours before presentation, with a chief complaint of acute chest pain meeting the broad definition of chest pain (2021 AHA)\n3. Presentation to the emergency department, with a clinical diagnosis consistent with non-traumatic chest pain\n4. Signed informed consent\n\nExclusion Criteria:\n\n1. traumatic chest pain\n2. systemic pain caused by malignant tumors or rheumatic diseases involving the chest\n3. Patients were lost to follow-up","ALL","18 Years",{"count":66,"type":67},10000,"ESTIMATED","1 Month","OBSERVATIONAL","Acute non-traumatic chest pain is one of the common causes of presentation in emergency patients, but the causes of acute non-traumatic chest pain are complex, the severity of the condition varies greatly, and the specificity of symptoms is not high. Machine learning and intelligent auxiliary models can greatly shorten the time of clinical decision-making, and improve the accuracy of etiological diagnosis in patients with chest pain, reduce the rate of misdiagnosis and missed diagnosis, and provide a clear direction for further treatment.",[72],"Chest Pain","2026-02-03",{"date":75,"type":76},"2026-02-05","ACTUAL",{"date":78,"type":76},"2022-08-30",{"date":80,"type":67},"2028-12-30",{"name":54,"class":6},1]