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Predicting Adverse Outcomes Using Machine Learning of COPD Patients in Hong Kong

Recruitingn/aAges 40 Years - anyAllChinese University of Hong Kong
NCT05825014 on ClinicalTrials.gov ↗
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In plain words

What the trial is, and whether it could suit you

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: Primary outcome: Early admission Secondary outcomes: 1. Frequent readmission 2. Composite outcome (Early + Frequent readmissions) 3. Mortality 4. Longstayers

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📋 Eligibility rules (as published)
Inclusion Criteria: * ≥40 years * Patients are discharged from 2016 -2022 * Discharge Diagnosis: Using the Discharge Diagnosis ICD Codes found in the Primary Diagnosis to determine if a patient has COPD * Validated against Spirometry results (for patient with a spirometry reading): Spirometry reading taken from anytime point before. Patient should have Post FEV1/FVC ratio of \< 0.7 in any one of the spirometry readings. If Post FEV1/FVC is not available, we will check if patients have a Pre FEV1/FVC value, and will also include patients with Pre FEV1/FVC ratio of \< 0.7 in any one of the spirometry readings. Exclusion Criteria: * Admission diagnosis due to causes other than COPD
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What it tests

  • No intervention
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Where

1 site
The Chinese University of Hong Kong
Hong Kong, Hong Kong
🤝 Taking part is your choice, and you can leave at any time. Only the trial team can confirm you are eligible — always decide together with your own doctor.
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