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

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.

Study Overview

• Status: Recruiting
• Conditions: Chronic Obstructive Pulmonary Disease Severe

• Study Type: Observational
• Enrollment (Estimated): 365

Contacts and Locations

• Study Contact: Name: Li An; Phone Number: CHN+13681133265; Email: bjzy818@sina.com

Study Locations

• China
  • Beijing
    • Beijing, Beijing, China, 100000
      • Recruiting
      • Beijing Chaoyang Hospital Affiliated to Capital Medical University
      • Contact: Li An, doctorate; Phone Number: CHN+13681133265; Email: bjzy818@sina.com

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: N/A

• Sampling Method: Non-Probability Sample

Study Population

A patient with severe chronic obstructive pulmonary disease who visited the Department of Respiratory and Critical Care Medicine, Beijing Chaoyang Hospital, Capital Medical University since January 2023

Description

Inclusion Criteria:

1. Patients who meet the diagnostic criteria for COPD of the global initiative for chronic obstructive lung diseases (GOLD 2022) and GOLD grading Ⅲ - Ⅳ (FEV1/FVC<70%, FEV1% predicted value ≤ 50% after Bronchiectasis)
2. Age>40 years old
3. COPD stable for more than 4 weeks
4. Short acting Bronchiectasis was not used within 24 hours before this experiment, long acting Bronchiectasis was not used within 48 hours, and glucocorticoids were not used throughout the body in the past month
5. Patient informed and signed consent form

Exclusion Criteria:

1. Asthma, active pulmonary tuberculosis, interstitial pneumonia and severe Bronchiectasis
2. Complicated with serious diseases (acute infection, diabetes, stroke, heart disease, liver and kidney dysfunction, cancer or autoimmune disease)
3. History of chronic diarrhea or constipation
4. History of Gastrointestinal Surgery
5. Using probiotics or antibiotics within the past 4 weeks
6. No history of using oral hormones or traditional Chinese medicine in the past three months
7. Pregnancy or lactation

Study Plan

How is the study designed?

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort
Frequent exacerbation of COPD
Non-frequent exacerbation of COPD

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Evaluate the predictive performance of the COPD frequent seizure risk prediction model based on the area under the ROC curve.	According to the Area Under Curve (AUC) of ROC, the largest one has the best predictive performance. When AUC>0.5, the closer it is to 1, the better the predictive performance of the model. When AUC=0.5, it indicates poor model fitting and no potential predictive value.	A year

Collaborators and Investigators

• Sponsor: Li An

Study record dates

Study Major Dates

• Study Start (Actual): May 1, 2023
• Primary Completion (Estimated): December 1, 2027
• Study Completion (Estimated): December 1, 2027

Study Registration Dates

• First Submitted: December 27, 2023
• First Submitted That Met QC Criteria: December 27, 2023
• First Posted (Actual): January 10, 2024

Study Record Updates

• Last Update Posted (Actual): January 10, 2024
• Last Update Submitted That Met QC Criteria: December 27, 2023
• Last Verified: December 1, 2023

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Pathologic Processes; Respiratory Tract Diseases; Disease Attributes; Chronic Disease; Lung Diseases; Lung Diseases, Obstructive; Pulmonary Disease, Chronic Obstructive
• Other Study ID Numbers: al123456

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No