[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100561573":3},{"organization":4,"armGroups":7,"interventions":8,"overallOfficials":7,"centralContacts":12,"locations":18,"responsibleParty":35,"collaborators":7,"id":37,"slug":38,"hasResults":39,"nctId":40,"briefTitle":41,"officialTitle":42,"acronym":7,"eligibilityCriteria":43,"healthyVolunteers":44,"sex":45,"minAge":46,"maxAge":7,"enrollmentInfo":47,"targetDuration":7,"studyType":50,"phases":7,"briefSummary":51,"conditions":52,"keywords":57,"overallStatus":60,"whyStopped":7,"lastUpdateSubmitDate":61,"lastUpdatePostDateStruct":62,"startDateStruct":65,"completionDateStruct":67,"leadSponsor":69,"locationsCount":70},{"fullName":5,"class":6},"Shanghai Zhongshan Hospital","OTHER",null,[9],{"type":6,"name":10,"description":11,"armGroupLabels":7,"otherNames":7},"No Interventions","No interventions.",[13],{"name":14,"role":15,"phone":16,"phoneExt":7,"email":17},"Yixiu Liang, MD","CONTACT","800-555-5850","liang.yixiu@zs-hospital.sh.cn",[19],{"facility":20,"status":7,"city":21,"state":22,"zip":23,"country":24,"countryCode":25,"cosmosGeoPoint":26,"geoPoint":31,"contacts":32},"Zhongshan Hospital","Shanghai","Shanghai Municipality","200032","China","CN",{"type":27,"coordinates":28},"Point",[29,30],121.45806,31.22222,{"lat":30,"lon":29},[33],{"name":14,"role":15,"phone":34,"phoneExt":7,"email":17},"+8602164041990",{"type":36,"investigatorFullName":7,"investigatorTitle":7,"investigatorAffiliation":7,"oldNameTitle":7,"oldOrganization":7},"SPONSOR","100561573","a-foundational-model-for-cardiovascular-disease-diagnosis-and-prediction-100561573",false,"NCT06591923","a Foundational Model for Cardiovascular Disease Diagnosis and Prediction","Development and Clinical Application of a Foundational Model for Cardiovascular Disease Diagnosis and Prediction Based on Multimodal Medical Big Data","Inclusion Criteria:\n\nAge ≥ 18 years: Patients who are 18 years of age or older. Time period: Patients who were treated or diagnosed between January 1, 2009, and December 31, 2023.\n\nComplete medical records: Patients with comprehensive medical records, including ECG, echocardiography, MRI, CTA, nuclear imaging (SPECT\u002FPET), and biochemical test results.\n\nCardiovascular diseases: Patients with diagnosed cardiovascular conditions, such as coronary artery disease (CAD), heart failure, arrhythmias, and valvular heart disease (VHD), as well as healthy individuals for comparison.\n\nWillingness to participate: Patients who are able to provide informed consent or their legal representatives.\n\nExclusion Criteria:\n\nParticipation in other clinical trials: Patients who are currently participating in other clinical trials that may affect the study outcomes.\n\nIncomplete medical records: Patients whose medical records lack essential data, such as ECG, echocardiography, MRI, CTA, nuclear imaging (SPECT\u002FPET), or biochemical test results.\n\nData quality issues: Patients with records that have significant errors, inconsistencies, or incomplete data that cannot be reasonably corrected.\n\nEthical or legal concerns: Patients whose data cannot be used due to a lack of necessary consent or legal\u002Fethical restrictions.",true,"ALL","18 Years",{"count":48,"type":49},1000000,"ESTIMATED","OBSERVATIONAL","The goal of this observational study is to develop and evaluate the efficacy of a foundational model that integrates multimodal medical data to improve the diagnosis and prediction of cardiovascular diseases in patients aged 18 and older, including those with various heart conditions such as coronary artery disease, heart failure, and arrhythmias. The main questions it aims to answer are:\n\nCan a multimodal data-based diagnostic model match or exceed the accuracy of traditional gold-standard methods like coronary angiography, MRI, and echocardiography? Does integrating different types of data (ECG, imaging, biochemical tests) improve diagnostic accuracy and prediction of cardiovascular disease outcomes? Researchers will compare the foundational model with traditional diagnostic methods to see if the model offers better sensitivity, specificity, and prediction accuracy across different heart disease types.\n\nParticipants will:\n\nProvide data from past medical records, including ECG, echocardiography, cardiac MRI, and biochemical tests.\n\nUndergo further data collection if necessary, in line with standard clinical procedures for cardiovascular disease management.",[53,54,55,56],"Coronary Heart Disease (CHD)","Heart Failure","Arrhythmias","Valvular Heart Disease",[58,59],"foundation model","artificial intelligence","NOT_YET_RECRUITING","2024-09-08",{"date":63,"type":64},"2024-09-19","ACTUAL",{"date":66,"type":49},"2024-10",{"date":68,"type":49},"2025-04",{"name":5,"class":6},1]