Real Time Early Warning Model and Mobile Medical Assistant System for the Impact of Air Pollution on AECOPD Disease

NCT04960410 | Completed DMC

• 1 other identifier: LM2018072
• Study Type: observational
• Target: 56
• Locations: 0 countries
• Sites: N/A

Brief Summary

Objective to establish a real-time early warning model of acute exacerbation of chronic obstructive pulmonary disease (COPD) caused by air pollution, and develop the corresponding mobile medical assistant system. Through the cross fusion of existing information technology and medical research results, an auxiliary medical system is formed for information recording, tracking tools, early warning model and clinical diagnosis of patients with COPD.

Conditions

COPD

Outcome Measures

Primary Outcomes (1)

• Frequency of acute exacerbations

  Frequency of acute exacerbations

  1 year incidence rate

Study Arms (2)

Low air pollution

Combination Product: Types and exposure of different air pollutants

High air pollution

Combination Product: Types and exposure of different air pollutants

Interventions

Types and exposure of different air pollutants COMBINATION_PRODUCT

Types and exposure of different air pollutants in COPD patients' living and working environment

High air pollution; Low air pollution

Eligibility Criteria

• Age: 40 Years - 80 Years
• Sex: all
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Stable chronic obstructive pulmonary disease (COPD) patients

You may qualify if:

• Patients aged \> 40 and \< 80 years with post-bronchodilator FEV1/ forced vital capacity (FVC) \< 0.7 and percentage predicted of FEV1\>30%, who were no exacerbation of symptoms in the 6 weeks preceding the study, were included in the study.

You may not qualify if:

• Patients who were diagnosed with other chronic respiratory diseases, including bronchial asthma, bronchiectasis and lung abscess.
• Patients with near-terminal illness, congestive heart failure (NYHA III-IV), or cannot record CAT score timely were excluded.

Sponsors & Collaborators

• Peking University Third Hospital: lead
• Beihang University: collaborator

MeSH Terms

Conditions

Pulmonary Disease, Chronic Obstructive

Condition Hierarchy (Ancestors)

Lung Diseases, Obstructive; Lung Diseases; Respiratory Tract Diseases; Chronic Disease; Disease Attributes; Pathologic Processes; Pathological Conditions, Signs and Symptoms

Study Officials

• Yahong Chen, Dr.

  Peking University Third Hospital

  STUDY DIRECTOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: July 4, 2021
• First Posted: July 13, 2021
• Study Start: January 1, 2017
• Primary Completion: April 23, 2017
• Study Completion: December 30, 2018
• Last Updated: July 13, 2021

Record last verified: 2021-07

Data Sharing

• IPD Sharing: Will not share