NCT06109974

Evaluate the Accuracy of a COPD Screening Algorithm Model

Evaluation of an Algorithm That Can Detect COPD by Intelligent Terminal Device

• Status: Completed
• Phase: —
• Study type: Observational
• Enrollment: 400 (actual)
• Sponsor: Peking University First Hospital · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Not accepted

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.

Conditions

• COPD

Timeline

• Start date: 2022-09-13
• Primary completion: 2024-01-04
• Completion: 2024-01-04
• First posted: 2023-10-31
• Last updated: 2024-01-23

Locations

5 sites across 1 country: China