Detect and Infer the Severity of COPD by Intelligent Terminal Device
- Conditions
- COPD
- Registration Number
- NCT05551169
- Lead Sponsor
- Peking University First Hospital
- Brief Summary
Chronic obstructive pulmonary disease (COPD) is one of the most common respiratory diseases. Early detection and treatment are critical to prevent the deterioration of COPD. In this study, investigators aim to develop an algorithm that can detect and infer the severity level of COPD from physiological parameters and audio data which are collected by a wearable device. Investigators will complete the study in two stages: stage 1. A panel study to assess the ability to infer the severity of COPD by intelligent terminal devices; stage 2. Establish an algorithm that can detect and infer the severity level of COPD by intelligent terminal devices.
- Detailed Description
In this study, investigators aim to establish an algorithm that can detect and infer the severity level of COPD from physiological parameters, coughing sounds, and forceful blowing sounds data that are collected by wearable devices.
This study is divided into two stages. Stage one: A panel study to assess the ability to infer the severity of COPD by intelligent terminal devices. 30 patients with stable COPD will be enrolled and will undergo pulmonary function tests, electrocardiogram, echocardiography measurement, blood gas analysis, six-minutes walking test (6MWT), and polysomnography. And they are required to fill in the questionnaires related to COPD every day. Physiological parameters including oxygen saturation, heart rate, sleep, and physical activity will be collected by a wearable device for 7-14 consecutive days. Coughing and forceful blowing sounds will be collected twice daily. The association between the severity of COPD and physiological parameters from the wearable device will be analyzed.
Stage two: Establish an algorithm that can detect and infer the severity level of COPD by intelligent terminal devices. 200 patients with stable COPD and 200 non- COPD subjects will be enrolled. Questionnaires related to COPD will be collected, and subjects will undergo pulmonary function tests and electrocardiograms. Physiological parameters including oxygen saturation and heart rate will be continuously collected by a wearable device for about 3～7 days. Investigators will also collect coughing and forceful blowing sounds. A COPD diagnosis algorithm model based on physiological parameters and audio data of intelligent terminal devices will be established.
The study protocol has been approved by the Peking University First Hospital Institutional Review Board (IRB) (2022-083). Any protocol modifications will be submitted for IRB review and approval.
Recruitment & Eligibility
- Status
- COMPLETED
- Sex
- All
- Target Recruitment
- 432
Not provided
Not provided
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method Stage 1: Association between the severity of COPD airflow restriction and data collected by wearable devices 2 months Association between the severity of COPD airflow restriction and data collected by wearable devices
Stage 2：Establish an algorithm that can detect and infer the severity level of COPD by intelligent terminal devices 5 months Establish an algorithm that can detect and infer the severity level of COPD by intelligent terminal devices
- Secondary Outcome Measures
Name Time Method Stage 2: number of adverse events 5 months The number of adverse events
Stage 1: Association between the severity of COPD airflow restriction, CAT score, mMRC score, echocardiography, blood gas analysis, six-minutes walking distance, polysomnography，and data collected by wearable devices 2 months Association between the severity of COPD airflow restriction, CAT score, mMRC score, echocardiography, blood gas analysis, six-minutes walking distance, polysomnography，and data collected by wearable devices
Stage 1: The compliance of subjects with wearable devices 2 months The compliance of subjects with wearable devices is defined as the percentage of the actual completion time of data collection to the minimum required time (10 hours X 7 days=70 hours).
Stage 2: Association between the severity of COPD airflow restriction, CAT score, mMRC score，and data collected by wearable devices 5 months Association between the severity of COPD airflow restriction, CAT score, mMRC score，and data collected by wearable devices
Trial Locations
- Locations (10)
Beijing Luhe Hospital
🇨🇳Beijing, Beijing, China
Civil Aviation General Hospital
🇨🇳Beijing, Beijing, China
Peking University Shougang Hospital
🇨🇳Beijing, Beijing, China
Aerospace 731 Hospital
🇨🇳Beijing, Beijing, China
Beijing Jingmei Group General Hospital
🇨🇳Beijing, Beijing, China
Beijing Miyun Hospital
🇨🇳Beijing, Beijing, China
Beijing Jishuitan Hospital
🇨🇳Beijing, Beijing, China
People's Hospital of Beijing Daxing District
🇨🇳Beijing, Beijing, China
Shichahai community health service center
🇨🇳Beijing, Beijing, China
The Hospital of Shunyi District Beijing
🇨🇳Beijing, Beijing, China