COPD
Conditions
Keywords
COPD, Intelligent Terminal Device, Algorithm model
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, we have established an algorithm that can detect and infer the severity of COPD from physiological parameters and audio data collected by wearable devices, and in this stage, we aim to evaluate the accuracy of this algorithm.
Detailed description
The investigators have established an algorithm that can detect COPD from physiological parameters, coughing sounds, and forceful expiratory sounds collected by wearable devices. This study will test the accuracy of this algorithm. In this study, 404 residents at high risk of COPD (COPD-PS score≥5) will be enrolled. Questionnaires related to COPD will be collected, subjects will undergo pulmonary function tests and electrocardiogram. Physiological parameters such as oxygen saturation and heart rate will be collected by a wearable device 3 times for 2 minutes each time, and coughing sound will be collected. As spirometry is the gold standard for the diagnosis of COPD, the accuracy of COPD diagnosis algorithm model by intelligent terminal devices will be verified. 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 the IRB review and approval.
Interventions
None listed
Sponsors
Civil Aviation General Hospital
Shichahai Community Health Service Center of Xicheng District Beijing
The Hospital of Changping District Beijing
Baizhifang Community Health Service Center of Xicheng District Beijing
Peking University First Hospital
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
1. Over the age of 18, no gender restrictions. 2. Participants at high risk of COPD (COPD-PS score ≥5). 3. Able to carry out daily activities and wear wearable devices. 4. Willing to participate in the study, willing to comply with the study protocol, and have the ability to sign informed consent. 5. Possess mobile communication equipment, which can meet the requirement of installing wearable device applications and recording function.
Exclusion criteria
1. Diagnosed with chronic respiratory diseases other than COPD, such as asthma, lung cancer, active tuberculosis, bronchiectasis and diffuse lung diseases (interstitial pneumonia, occupational lung disease, sarcoidosis, etc.). 2. lobectomy and/or lung transplantation, pleural disease. 3. Complicated with serious underlying diseases, including severe mental illness, intellectually impaired diseases, neurological disease (resulting in limb movement disorder), malignant tumor (PS score \> 2), chronic liver disease (transaminase \> 3 times the upper limit of normal), heart failure (NYHA\> Grade 3), autoimmune disease, chronic kidney disease (CKD-5), unstable coronary artery disease, arrhythmia (atrial fibrillation, atrial flutter, severe ventricular arrhythmia), congenital heart disease, pulmonary hypertension, etc., or life expectancy of less than 6 months. 4. Malnutrition (BMI\<18 kg/m2). 5. Bilateral wrist and hand edema, wrist soft tissue injury, inability to wear a watch/bracelet due to incomplete skin. 6. Dual upper limb pigmentation or abnormal blood supply (occlusion, thrombosis, trauma, etc.).
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| The diagnostic accuracy of the algorithm for COPD | 1 year | The diagnostic accuracy of the algorithm for COPD |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| The diagnostic sensitivity and specificity of the algorithm | 1 year | The diagnostic sensitivity and specificity of the algorithm |
| The diagnostic accuracy of COPD-PS score for COPD | 1 year | The diagnostic accuracy of COPD-PS score for COPD |
Countries
China
Outcome results
None listed