[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100601269":3},{"organization":4,"armGroups":7,"interventions":13,"overallOfficials":10,"centralContacts":18,"locations":24,"responsibleParty":228,"collaborators":10,"id":231,"slug":232,"hasResults":233,"nctId":234,"briefTitle":235,"officialTitle":236,"acronym":237,"eligibilityCriteria":238,"healthyVolunteers":239,"sex":240,"minAge":241,"maxAge":242,"enrollmentInfo":243,"targetDuration":246,"studyType":247,"phases":10,"briefSummary":248,"conditions":249,"keywords":252,"overallStatus":258,"whyStopped":10,"lastUpdateSubmitDate":259,"lastUpdatePostDateStruct":260,"startDateStruct":263,"completionDateStruct":265,"leadSponsor":267,"locationsCount":268},{"fullName":5,"class":6},"Affiliated Hospital of Changchun University of Chinese Medicine","OTHER",[8],{"label":9,"type":10,"description":10,"interventionNames":11},"Chinese Age-Sex-Stratified Cardiopulmonary Function Cohort (CACSF Cohort)",null,[12],"Other: cardiopulmonary exercise testing (CPET)",[14],{"type":6,"name":15,"description":16,"armGroupLabels":17,"otherNames":10},"cardiopulmonary exercise testing (CPET)","In this study, the cardiopulmonary exercise testing (CPET) system used breath-by-breath continuous analysis for gas exchange and ventilation variables. The protocol included spirometry with an 8-breath data collection method. The cycle ergometer workload ranged from 10 to 40 W\u002Fmin using a RAMP protocol. The standard CPET protocol comprised a 3-min rest, 3-min warm-up, 8 - 12 min incremental exercise phase, and 3-min each of active and passive recovery.",[9],[19],{"name":20,"role":21,"phone":22,"phoneExt":10,"email":23},"Head of Cardiac Rehabilitation Department","CONTACT","+86 131 8088 9430","Xiopingmeng@126.com",[25,42,56,70,80,94,108,121,135,148,162,176,187,201,214],{"facility":26,"status":10,"city":27,"state":28,"zip":29,"country":30,"countryCode":31,"cosmosGeoPoint":32,"geoPoint":37,"contacts":38},"Peking Union Medical College Hospital","Beijing","Beijing Municipality","100730","China","CN",{"type":33,"coordinates":34},"Point",[35,36],116.39723,39.9075,{"lat":36,"lon":35},[39],{"name":40,"role":21,"phone":41,"phoneExt":10,"email":10},"Rongjing R Ding, MD","+86 13552548612",{"facility":43,"status":10,"city":44,"state":45,"zip":46,"country":30,"countryCode":31,"cosmosGeoPoint":47,"geoPoint":51,"contacts":52},"Quanzhou First Hospital Affiliated to Fujian Medical University","Quanzhou","Fujian","362000",{"type":33,"coordinates":48},[49,50],118.58583,24.91389,{"lat":50,"lon":49},[53],{"name":54,"role":21,"phone":55,"phoneExt":10,"email":10},"Ruozhu R Dai","+86 18960337219",{"facility":57,"status":10,"city":58,"state":59,"zip":60,"country":30,"countryCode":31,"cosmosGeoPoint":61,"geoPoint":65,"contacts":66},"Guangdong Provincial People's Hospital Affiliated to Southern Medical University","Guangzhou","Guangdong","510080",{"type":33,"coordinates":62},[63,64],113.25,23.11667,{"lat":64,"lon":63},[67],{"name":68,"role":21,"phone":69,"phoneExt":10,"email":10},"Huan H Ma, MD","+86 15018755932",{"facility":71,"status":10,"city":58,"state":59,"zip":72,"country":30,"countryCode":31,"cosmosGeoPoint":73,"geoPoint":75,"contacts":76},"Guangdong Provincial Hospital of Chinese Medicine","510120",{"type":33,"coordinates":74},[63,64],{"lat":64,"lon":63},[77],{"name":78,"role":21,"phone":79,"phoneExt":10,"email":10},"Wei W Jiang, MD","+86 15630050688",{"facility":81,"status":10,"city":82,"state":83,"zip":84,"country":30,"countryCode":31,"cosmosGeoPoint":85,"geoPoint":89,"contacts":90},"Jiangbin Hospital of Guangxi Zhuang Autonomous Region","Nanning","Guangxi","530021",{"type":33,"coordinates":86},[87,88],108.31667,22.81667,{"lat":88,"lon":87},[91],{"name":92,"role":21,"phone":93,"phoneExt":10,"email":10},"Youcai Y Hu, MD","+86 13978870585",{"facility":95,"status":10,"city":96,"state":97,"zip":98,"country":30,"countryCode":31,"cosmosGeoPoint":99,"geoPoint":103,"contacts":104},"Daqing Oilfield General Hospital","Daqing","Heilongjiang","163000",{"type":33,"coordinates":100},[101,102],125,46.58333,{"lat":102,"lon":101},[105],{"name":106,"role":21,"phone":107,"phoneExt":10,"email":10},"Zhiqing Z Fan, MD","+86 13836769588",{"facility":109,"status":10,"city":110,"state":97,"zip":111,"country":30,"countryCode":31,"cosmosGeoPoint":112,"geoPoint":116,"contacts":117},"The Second Hospital of Harbin Medical University","Harbin","150086",{"type":33,"coordinates":113},[114,115],126.65,45.75,{"lat":115,"lon":114},[118],{"name":119,"role":21,"phone":120,"phoneExt":10,"email":10},"Jian J Wu, MD","+86 15245001123",{"facility":122,"status":10,"city":123,"state":124,"zip":125,"country":30,"countryCode":31,"cosmosGeoPoint":126,"geoPoint":130,"contacts":131},"Anyang Regional Hospital of Puyang City, Henan Province","Puyang","Henan","457000",{"type":33,"coordinates":127},[128,129],115.04363,35.75641,{"lat":129,"lon":128},[132],{"name":133,"role":21,"phone":134,"phoneExt":10,"email":10},"Hui H Liu, MD","+86 13903727688",{"facility":136,"status":10,"city":137,"state":124,"zip":138,"country":30,"countryCode":31,"cosmosGeoPoint":139,"geoPoint":143,"contacts":144},"Zhengzhou Central Hospital Affiliated to Zhengzhou University","Zhengzhou","450000",{"type":33,"coordinates":140},[141,142],113.64861,34.75778,{"lat":142,"lon":141},[145],{"name":146,"role":21,"phone":147,"phoneExt":10,"email":10},"Dongwei D Wang","+86 18937633428",{"facility":149,"status":10,"city":150,"state":151,"zip":152,"country":30,"countryCode":31,"cosmosGeoPoint":153,"geoPoint":157,"contacts":158},"Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology","Wuhan","Hubei","430030",{"type":33,"coordinates":154},[155,156],114.26667,30.58333,{"lat":156,"lon":155},[159],{"name":160,"role":21,"phone":161,"phoneExt":10,"email":10},"Cuntai C Zhang, MD","+86 15927668408",{"facility":163,"status":10,"city":164,"state":165,"zip":166,"country":30,"countryCode":31,"cosmosGeoPoint":167,"geoPoint":171,"contacts":172},"Xiangya Second Hospital of Central South University","Changsha","Hunan","410011",{"type":33,"coordinates":168},[169,170],112.97087,28.19874,{"lat":170,"lon":169},[173],{"name":174,"role":21,"phone":175,"phoneExt":10,"email":10},"Danyan D Xu, MD","+86 13974874636",{"facility":5,"status":10,"city":177,"state":178,"zip":179,"country":30,"countryCode":31,"cosmosGeoPoint":180,"geoPoint":184,"contacts":185},"Changchun","Jilin","130000",{"type":33,"coordinates":181},[182,183],125.32278,43.88,{"lat":183,"lon":182},[186],{"name":20,"role":21,"phone":22,"phoneExt":10,"email":23},{"facility":188,"status":10,"city":189,"state":190,"zip":191,"country":30,"countryCode":31,"cosmosGeoPoint":192,"geoPoint":196,"contacts":197},"Qilu Hospital of Shandong University","Jinan","Shangdong","250012",{"type":33,"coordinates":193},[194,195],116.99722,36.66833,{"lat":195,"lon":194},[198],{"name":199,"role":21,"phone":200,"phoneExt":10,"email":10},"Lin L Shen, MD","+86 18560082257",{"facility":202,"status":10,"city":203,"state":204,"zip":205,"country":30,"countryCode":31,"cosmosGeoPoint":206,"geoPoint":210,"contacts":211},"Tongji Hospital","Shanghai","Shanghai Municipality","200065",{"type":33,"coordinates":207},[208,209],121.45806,31.22222,{"lat":209,"lon":208},[212],{"name":20,"role":21,"phone":213,"phoneExt":10,"email":10},"+86 13661615008",{"facility":215,"status":10,"city":216,"state":217,"zip":218,"country":30,"countryCode":31,"cosmosGeoPoint":219,"geoPoint":223,"contacts":224},"First Affiliated Hospital of Xi'an Jiaotong University","Xi’an","Shanxi","710061",{"type":33,"coordinates":220},[221,222],113.52486,35.99785,{"lat":222,"lon":221},[225],{"name":226,"role":21,"phone":227,"phoneExt":10,"email":10},"Fenling F Fan, MD","+86 15182916660",{"type":229,"investigatorFullName":230,"investigatorTitle":20,"investigatorAffiliation":5,"oldNameTitle":10,"oldOrganization":10},"PRINCIPAL_INVESTIGATOR","Xiaoping Meng","100601269","a-study-on-cardiopulmonary-exercise-tolerance-standards-for-healthy-chinese-population-100601269",false,"NCT07108296","A Study on Cardiopulmonary Exercise Tolerance Standards for Healthy Chinese Population","Multi-center Clinical Cohort Study on Cardiopulmonary Exercise Tolerance Standards in Chinese Healthy Population","MCCS-CCPETS","Inclusion Criteria:\n\n* Detailed medical history taken, with no symptoms of discomfort reported\n* Good physical condition, with no history of severe chronic diseases\n* No history of long - term medication use\n* Willing to undergo cardiopulmonary exercise testing, with no ST - T segment changes observed during the test\n* Age: 18 - 65 years old\n* BMI: 18.5 - 28kg\u002Fm²\n* No smoking history or quit smoking for ≥5 years\n* Physical examination reports within 2 years show no significant abnormalities.\n\nExclusion Criteria:\n\n* Pre - test resting blood pressure ≥160\u002F100 mmHg (1 mmHg=0.133 kPa)\n* Chronic cardiovascular diseases, such as heart failure, coronary atherosclerotic heart disease, hypertension, congenital heart disease, cardiomyopathy, and severe arrhythmias\n* Respiratory diseases, such as chronic obstructive pulmonary disease, asthma, pulmonary artery hypertension, bronchiectasis, and respiratory failure\n* Digestive system diseases, such as peptic ulcer, gastrointestinal bleeding, hepatitis, liver cirrhosis, ulcerative colitis, Crohn's disease, chronic pancreatitis, and chronic cholecystitis\n* Endocrine system diseases, such as hyperthyroidism, hypothyroidism, diabetes, and other diseases with clear hormone abnormalities\n* Acute or chronic kidney diseases, blood system diseases, malignant tumors, and bone and joint diseases that affect activity\n* No history of acute infection within 2 weeks\n* Unable to cooperate with the examination\n* Contraindications to cardiopulmonary exercise testing: acute myocardial infarction",true,"ALL","18 Years","65 Years",{"count":244,"type":245},4620,"ESTIMATED","1 Day","OBSERVATIONAL","This project intends to conduct a large-sample, prospective, multicenter clinical cohort study in healthy populations. By utilizing a digital cardiopulmonary rehabilitation clinical data research platform, The investigators aim to achieve automated, standardized, and uniform collection, analysis, and AI modeling of large-scale cardiopulmonary exercise testing (CPET) data. The ultimate goals are:\n\nTo establish reference standards for cardiopulmonary exercise capacity in the Chinese healthy population.\n\nTo develop machine learning-based predictive models for key CPET variables (e.g., peak VO₂) tailored to Chinese demographics.\n\nTo compare performance differences between domestically produced and imported CPET devices.",[250,251],"Oxygen Consumption","Cardiorespiratory Fitness",[253,254,255,256,257],"Peak Oxygen Uptake","VO2@AT","Cardiopulmonary Exercise Tolerance","Prediction Model","Healthy Population","NOT_YET_RECRUITING","2025-08-06",{"date":261,"type":262},"2025-08-11","ACTUAL",{"date":264,"type":245},"2025-09-01",{"date":266,"type":245},"2027-03-30",{"name":5,"class":6},15]