Evaluate the Accuracy of a COPD Screening Algorithm Model

Sponsor

Peking University First Hospital (Other)

Overall Status

Enrolling by invitation

CT.gov ID

NCT06109974

Collaborator

Civil Aviation General Hospital (Other), Shichahai Community Health Service Center of Xicheng District Beijing (Other), The Hospital of Changping District Beijing (Other), Baizhifang Community Health Service Center of Xicheng District Beijing (Other)

404

Enrollment

Locations

25.6

Anticipated Duration (Months)

80.8

Patients Per Site

3.2

Patients Per Site Per Month

Study Details

Study Description

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.

Condition or Disease	Intervention/Treatment	Phase
COPD

Detailed Description

We 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.

Study Design

Study Type:

Observational

Anticipated Enrollment :

404 participants

Observational Model:

Cohort

Time Perspective:

Prospective

Official Title:

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

Actual Study Start Date :

Sep 13, 2022

Anticipated Primary Completion Date :

Oct 31, 2024

Anticipated Study Completion Date :

Oct 31, 2024

Arms and Interventions

Arm	Intervention/Treatment
Participants with high risk of COPD no intervention

Outcome Measures

Primary Outcome Measures

The diagnostic accuracy of the algorithm for COPD [1 year]
The diagnostic accuracy of the algorithm for COPD

Secondary Outcome Measures

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

Eligibility Criteria

Criteria

Ages Eligible for Study:

18 Years and Older

Sexes Eligible for Study:

All

Accepts Healthy Volunteers:

Inclusion Criteria:

Over the age of 18, no gender restrictions.
Participants at high risk of COPD (COPD-PS score ≥5).
Able to carry out daily activities and wear wearable devices.
Willing to participate in the study, willing to comply with the study protocol, and have the ability to sign informed consent.
Possess mobile communication equipment, which can meet the requirement of installing wearable device APP and recording function.

Exclusion Criteria:

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.).
lobectomy and/or lung transplantation, pleural disease.
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.
Malnutrition (BMI<18 kg/m2).
Bilateral wrist and hand edema, wrist soft tissue injury, inability to wear a watch/bracelet due to incompleted skin.
Dual upper limb pigmentation or abnormal blood supply (occlusion, thrombosis, trauma, etc.).

Contacts and Locations

Locations

	Site	City	State	Country
1	Baizhifang Community Health Service Center of Xicheng District Beijing	Beijing	Beijing	China
2	Civil Aviation General Hospita	Beijing	Beijing	China
3	Guangfa Wang	Beijing	Beijing	China
4	Shichahai community health service center	Beijing	Beijing	China
5	The Hospital of Changping District Beijing	Beijing	Beijing	China

Sponsors and Collaborators

Peking University First Hospital
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

Investigators

Study Chair: Guangfa Wang, MD, Peking University First Hospital

Study Documents (Full-Text)

None provided.

More Information

Publications

None provided.

Responsible Party:

Guangfa Wang, Prof. & MD., Peking University First Hospital

ClinicalTrials.gov Identifier:

NCT06109974

Other Study ID Numbers:

2022083-20230810

First Posted:

Oct 31, 2023

Last Update Posted:

Oct 31, 2023

Last Verified:

Oct 1, 2023

Studies a U.S. FDA-regulated Drug Product:

Studies a U.S. FDA-regulated Device Product:

Keywords provided by Guangfa Wang, Prof. & MD., Peking University First Hospital

COPD

Intelligent Terminal Device

Algorithm model

Study Results

No Results Posted as of Oct 31, 2023