NCT06198309

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

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

• Status: Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 365 (estimated)
• Sponsor: Li An · Academic / Other
• Sex: All
• Age: 40 Years – 85 Years
• Healthy volunteers: —

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.

Conditions

• Chronic Obstructive Pulmonary Disease Severe

Timeline

• Start date: 2023-05-01
• Primary completion: 2027-12-01
• Completion: 2027-12-01
• First posted: 2024-01-10
• Last updated: 2024-01-10

Locations

1 site across 1 country: China