[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100502650":3},{"organization":4,"armGroups":7,"interventions":8,"overallOfficials":11,"centralContacts":15,"locations":21,"responsibleParty":40,"collaborators":7,"id":44,"slug":45,"hasResults":46,"nctId":47,"briefTitle":48,"officialTitle":48,"acronym":7,"eligibilityCriteria":49,"healthyVolunteers":46,"sex":50,"minAge":51,"maxAge":7,"enrollmentInfo":52,"targetDuration":7,"studyType":55,"phases":7,"briefSummary":56,"conditions":57,"keywords":7,"overallStatus":24,"whyStopped":7,"lastUpdateSubmitDate":59,"lastUpdatePostDateStruct":60,"startDateStruct":63,"completionDateStruct":65,"leadSponsor":67,"locationsCount":68},{"fullName":5,"class":6},"Chinese University of Hong Kong","OTHER",null,[9],{"type":6,"name":10,"description":10,"armGroupLabels":7,"otherNames":7},"No intervention",[12],{"name":13,"affiliation":5,"role":14},"David Hui, MD","STUDY_DIRECTOR",[16],{"name":17,"role":18,"phone":19,"phoneExt":7,"email":20},"Fanny Ko, MD","CONTACT","35053133","fannyko@cuhk.edu.hk",[22],{"facility":23,"status":24,"city":25,"state":26,"zip":7,"country":25,"countryCode":27,"cosmosGeoPoint":28,"geoPoint":33,"contacts":34},"The Chinese University of Hong Kong","RECRUITING","Hong Kong","New Territories","HK",{"type":29,"coordinates":30},"Point",[31,32],114.17469,22.27832,{"lat":32,"lon":31},[35,38],{"name":36,"role":18,"phone":19,"phoneExt":7,"email":37},"David S Hui, MD","dschui@cuhk.edu.hk",{"name":39,"role":18,"phone":19,"phoneExt":7,"email":20},"fanny WS Ko, MD",{"type":41,"investigatorFullName":42,"investigatorTitle":43,"investigatorAffiliation":5,"oldNameTitle":7,"oldOrganization":7},"PRINCIPAL_INVESTIGATOR","Fanny W.S. Ko","Honorary Clinical Associate Professor","100502650","predicting-adverse-outcomes-using-machine-learning-of-copd-patients-in-hong-kong-100502650",false,"NCT05825014","Predicting Adverse Outcomes Using Machine Learning of COPD Patients in Hong Kong","Inclusion Criteria:\n\n* ≥40 years\n* Patients are discharged from 2016 -2022\n* Discharge Diagnosis: Using the Discharge Diagnosis ICD Codes found in the Primary Diagnosis to determine if a patient has COPD\n* Validated against Spirometry results (for patient with a spirometry reading):\n\nSpirometry reading taken from anytime point before. Patient should have Post FEV1\u002FFVC ratio of \\\u003C 0.7 in any one of the spirometry readings. If Post FEV1\u002FFVC is not available, we will check if patients have a Pre FEV1\u002FFVC value, and will also include patients with Pre FEV1\u002FFVC ratio of \\\u003C 0.7 in any one of the spirometry readings.\n\nExclusion Criteria:\n\n* Admission diagnosis due to causes other than COPD","ALL","40 Years",{"count":53,"type":54},100000,"ESTIMATED","OBSERVATIONAL","This study aims to develop predictive models for patients with a diagnosis of COPD at discharge of an index admission on these outcomes using machine learning:\n\nPrimary outcome: Early admission\n\nSecondary outcomes:\n\n1. Frequent readmission\n2. Composite outcome (Early + Frequent readmissions)\n3. Mortality\n4. Longstayers",[58],"COPD Exacerbation","2026-03-17",{"date":61,"type":62},"2026-03-18","ACTUAL",{"date":64,"type":62},"2023-08-29",{"date":66,"type":54},"2028-04-30",{"name":5,"class":6},1]