COPDNCT06109974
Evaluate the Accuracy of a COPD Screening Algorithm Model
An observational study of COPD, run by Peking University First Hospital at 5 sites in China.
Trial 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… Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- COPD
- How many people
- 400 participants
- Where
- 5 sitesChina
- Study dates
- 13 Sep 2022to 4 Jan 2024
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: participants at high risk of COPD
Who may be able to join
- 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 applications and recording function.
Who cannot join
- 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 incomplete skin.
- Dual upper limb pigmentation or abnormal blood supply (occlusion, thrombosis, trauma, etc.).
Trial locations and contacts
5 sites in 1 country.
5 sites in 1 country
China5 sites
Baizhifang Community Health Service Center of Xicheng District Beijing
Beijing, Beijing Municipality
Civil Aviation General Hospita
Beijing, Beijing Municipality
Guangfa Wang
Beijing, Beijing Municipality
Shichahai community health service center
Beijing, Beijing Municipality
The Hospital of Changping District Beijing
Beijing, Beijing Municipality
About this study
Official title: Evaluation of an Algorithm That Can Detect COPD by Intelligent Terminal Device
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.
Read the 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
- Keywords
- COPD, Intelligent Terminal Device, Algorithm model
- Medical subject headings
- Pulmonary Disease, Chronic Obstructive
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Participants with high risk of COPD | no intervention |
What is being measured
The primary outcome is the main question the study is designed to answer.
The diagnostic accuracy of the algorithm for COPD
The diagnostic accuracy of the algorithm for COPD
Measured: 1 year
Secondary outcomes (2)
The diagnostic sensitivity and specificity of the algorithm
The diagnostic sensitivity and specificity of the algorithm
Measured: 1 year
The diagnostic accuracy of COPD-PS score for COPD
The diagnostic accuracy of COPD-PS score for COPD
Measured: 1 year
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted31 Oct 2023
- Study start13 Sep 2022
- Primary completion4 Jan 2024
- Study completion4 Jan 2024
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for COPDStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 400 participants (actual)
Sponsor and investigators
- Lead sponsor
- Peking University First Hospital
- Sponsor type
- University, hospital or other
- Collaborators
- 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
- Responsible party
- Principal investigator, Guangfa Wang, Peking University First Hospital
- Investigators
- Guangfa Wang, MD, Study chair, Peking University First Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06109974
- Sponsor's protocol ID
- 2022083-20230810
- Status last verified
- Jan 2024
- First submitted
- 25 Oct 2023
- Last updated
- 23 Jan 2024
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 23 Jan 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Evaluation of an Algorithm That Can Detect COPD by Intelligent Terminal Device
- ClinicalTrials.gov ID
- NCT06109974
- Acronym / sponsor ID
- 2022083-20230810
- Conditions
- COPD
- Keywords
- COPD, Intelligent Terminal Device, Algorithm model
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 400 participants (actual)
- Lead sponsor
- Peking University First HospitalUniversity, hospital or other
- Collaborators
- 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
- Study start
- 13 Sep 2022 (actual)
- Primary completion
- 4 Jan 2024 (actual)
- Study completion
- 4 Jan 2024 (actual)
- First posted
- 31 Oct 2023 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Participants with high risk of COPD | – | –no intervention |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- participants at high risk of COPD
Key inclusion criteria (5 listed)
- 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 applications and recording function.
Key exclusion criteria (6 listed)
- 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 incomplete skin.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
The diagnostic accuracy of the algorithm for COPD
Time frame: 1 year
The diagnostic accuracy of the algorithm for COPD
2 secondary outcomes
The diagnostic sensitivity and specificity of the algorithm
Time frame: 1 year
The diagnostic accuracy of COPD-PS score for COPD
Time frame: 1 year
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 23 Jan 2024.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Guangfa Wang, MD study chair
Peking University First Hospital
5 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of COPD, run by Peking University First Hospital at 5 sites in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 5 inclusion and 6 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 23 Jan 2024. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 5 sites in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
The diagnostic accuracy of the algorithm for COPD (time frame: 1 year). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 23 Jan 2024.