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RECRUITING
NCT06198309

Risk Prediction Model for Exacerbating Phenotype in Patients With Chronic Obstructive Pulmonary Disease

Sponsor: Li An

View on ClinicalTrials.gov

Summary

This study is planned to be conducted based on the cohort of patients with severe chronic obstructive pulmonary disease in our hospital. Based on gut microbiota, random forest was used to search for potential diagnostic biomarkers in patients with frequent acute exacerbation and controls with non frequent acute exacerbation; Construct a frequent acute exacerbation risk prediction model using random forest, support vector machine, and BP neural network models. The development of this study will provide valuable references for the clinical classification and prognosis evaluation of chronic obstructive pulmonary disease (COPD), and improve the health level of COPD patients by further searching for treatable targets.

Official title: A Risk-predictive Model for Frequent Acute Exacerbation Phenotype in Patients With Severe Chronic Obstructive Pulmonary Disease

Key Details

Gender

All

Age Range

40 Years - 85 Years

Study Type

OBSERVATIONAL

Enrollment

365

Start Date

2023-05-01

Completion Date

2027-12-01

Last Updated

2024-01-10

Healthy Volunteers

Not specified

Locations (1)

Beijing Chaoyang Hospital Affiliated to Capital Medical University

Beijing, Beijing Municipality, China