Actively Recruiting
Predicting Adverse Outcomes Using Machine Learning of COPD Patients in Hong Kong
Led by Chinese University of Hong Kong · Updated on 2026-03-18
100000
Participants Needed
1
Research Sites
243 weeks
Total Duration
On this page
AI-Summary
What this Trial Is About
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
CONDITIONS
Official Title
Predicting Adverse Outcomes Using Machine Learning of COPD Patients in Hong Kong
Who Can Participate
Eligibility Criteria
You may qualify if you...
- Age 40 years or older
- Discharged from hospital between 2016 and 2022
- Discharge diagnosis includes COPD using ICD codes in primary diagnosis
- Spirometry results showing Post FEV1/FVC ratio less than 0.7 or, if Post FEV1/FVC unavailable, Pre FEV1/FVC ratio less than 0.7
You will not qualify if you...
- Admission diagnosis due to causes other than COPD
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
Trial Site Locations
Total: 1 location
1
The Chinese University of Hong Kong
Hong Kong, New Territories, Hong Kong
Actively Recruiting
Research Team
F
Fanny Ko, MD
CONTACT
How is the study designed?
Study Type
OBSERVATIONAL
Masking
N/A
Allocation
N/A
Model
N/A
Primary Purpose
N/A
Number of Arms
0
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