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

NCT05825014 | Recruiting

• 1 other identifier: CRE Ref_ No_ 2022_679
• Study Type: observational
• Target: 100,000
• Locations: 1 country
• Sites: 1

Brief Summary

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. 1.Frequent readmission
2. 2.Composite outcome (Early + Frequent readmissions)
3. 3.Mortality
4. 4.Longstayers

Conditions

COPD Exacerbation

Outcome Measures

Primary Outcomes (1)

• Early Readmission

  Patients were readmitted to hospital with the primary diagnosis of AECOPD\* within 30 days since the discharge date of the index admission

  30 days

Secondary Outcomes (3)

• Frequent Admitters

  365 days

• 1-Year Mortality

  365 days

• Longstayers

  365 days

Interventions

No intervention OTHER

No intervention

Eligibility Criteria

• Age: 40 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Patients are discharged from 2016 -2022 from hospital for acute exacerbation of COPD

You may qualify if:

• ≥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.

You may not qualify if:

• Admission diagnosis due to causes other than COPD

Sponsors & Collaborators

• Chinese University of Hong Kong: lead

Study Sites (1)

The Chinese University of Hong Kong

Hong Kong, New Territories, Hong Kong

RECRUITING

Study Officials

• David Hui, MD

  Chinese University of Hong Kong

  STUDY DIRECTOR

Central Study Contacts

Fanny Ko, MD

CONTACT

35053133; fannyko@cuhk.edu.hk

Study Design

• Study Type: observational
• Observational Model: ECOLOGIC OR COMMUNITY
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Honorary Clinical Associate Professor

Study Record Dates

• First Submitted: April 11, 2023
• First Posted: April 24, 2023
• Study Start: August 29, 2023
• Primary Completion (Estimated): April 30, 2027
• Study Completion (Estimated): April 30, 2028
• Last Updated: March 18, 2026

Record last verified: 2026-03

Locations

HK (1)