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| Name | Class |
|---|---|
| University of Toronto | OTHER |
| Samsung Electronics | INDUSTRY |
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Our overall research goal for this project is to create a wearable device and mobile application, appealing to patients with Chronic Obstructive Pulmonary Disease (COPD), which provides them with appropriate self-management tools and detects AECOPDs early to permit prompt treatment and prevent severe exacerbations requiring hospitalization.
Our overall research goal for this project is to create a wearable device and mobile application, appealing to patients with COPD, which provides them with appropriate self-management tools and detects Acute Exacerbations of COPD (AECOPDs) early to permit prompt treatment and prevent severe exacerbations requiring hospitalization. Currently, the investigators are developing a second version of this app, WearCOPDv2. This app will incorporate features identified as being desirable from our patient interviews: 1) new sensor that was requested by patients - oxygen saturation, and 2) the app will incorporate a patient-facing interface as patients requested a method to view their data as well as access to information to learn how to manage their condition better.
Research questions:
Can an app designed for patients with COPD that includes biosensor feedback improve self-management of COPD?
What is the accuracy of our sensor data (heart rate, activity, respiratory rate, oxygen saturation, coughing, and other sounds of interest) in detecting early AECOPDs?
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| COPD Patients | This is a prospective cohort study enrolling patients with COPD to 1) wear a smartwatch that passively senses heart rate, motion, audio, 2) use a smartphone that can obtain oxygen saturation upon demand, 3) use a self-management app on the smartwatch, smartphone and a webapp. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| smartphone, smartwatch, WearCOPDv2 application | Device | WearCOPD2 consists of hardware and software components. 6.1 Hardware The hardware for wearCOPDv2 consists of three main components; (1) a smartwatch, (2) a phone, and (3) a server. 6.2 Software The wearCOPDv2 system has two main software components:
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| Measure | Description | Time Frame |
|---|---|---|
| Change in self-management as measured by the Mastery sub-section of the Chronic Respiratory Disease Questionnaire | Can an app designed for patients with COPD that includes biosensor feedback improve self-management of COPD? We will use the Mastery sub-section of the Chronic Respiratory Disease Questionnaire to measure our research question. Mastery is measured with a 7-point likert scale where higher scores indicate better health-related mastery. | 6 months |
| Measure | Description | Time Frame |
|---|---|---|
| Change in self-efficacy as measured by the COPD Self-Efficacy Scale | Can an app designed for patients with COPD that includes biosensor feedback improve self-efficacy of COPD? This will be measured by the COPD self-efficacy scale. Participants will determine how confident they are that they could manage breathing difficulty or avoid breathing difficulty in certain situations. Usin the following scale.
A lower score indicates higher self-efficacy. |
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Inclusion Criteria:
Exclusion Criteria:
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The investigators will recruit patients who have clinically relevant COPD who live at home. They will be identified in clinics and the wards by members of their care team. Posters informing people of the study will also be posted at University Health Network (UHN) with a contact number.
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| Name | Affiliation | Role |
|---|---|---|
| Robert Wu | University Health Network, Toronto | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Toronto General Hospital | Toronto | Ontario | M5G 2C4 | Canada |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 38443858 | Derived | Wu R, de Lara E, Liaqat D, Liaqat S, Chen JL, Son T, Gershon AS. Feasibility of a wearable self-management application for patients with COPD at home: a pilot study. BMC Med Inform Decis Mak. 2024 Mar 5;24(1):66. doi: 10.1186/s12911-024-02461-y. |
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UHN, research personnel will have direct access to the source documents with identifying information.
UHN, University of Toronto (UofT) and Samsung Research America (SRA) will have access to the anonymized subject data for analysis purposes.
Data will become available right away for up to 5 years.
Data will be stored and analyzed on the secure UHN server
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| ID | Term |
|---|---|
| D029424 | Pulmonary Disease, Chronic Obstructive |
| ID | Term |
|---|---|
| D008173 | Lung Diseases, Obstructive |
| D008171 | Lung Diseases |
| D012140 | Respiratory Tract Diseases |
| D002908 | Chronic Disease |
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| 6 months |
| Change in Health related quality of life as measured by the St. George's respiratory questionnaire | Can an app designed for patients with COPD that includes biosensor feedback improve health related quality of life? Scoring and Scales Questions 1 - 7 Scale: Most days a week - Not At All Where a patient has ticked a box, a value of 1 is entered for the appropriate question. Question 8 Where a patient has ticked 'Yes' to having a worse wheeze in the morning, a value of 1 is entered for the appropriate question. Questions 9, 10 & 17 Where a patient has ticked a box, a value of 1 is entered for the appropriate question. Questions 11 - 16 Where a patient has ticked 'True' a value of 1 is entered for the appropriate question. In response to question 14, if a patient is not receiving medication, enter the responses as zero. Score = 100 x (Summed weights from positive items in the questionnaire divided by the Sum of weights for all items in the questionnaire) lower scores indicate higher health related quality of life | 6 months |
| Change in symptom scale as measured by the MRC dyspnea scale | Can an app designed for patients with COPD that includes biosensor feedback improve COPD symptoms? The MRC Dyspnea scale asks you to rate your breathlessness on a 5 point likert scale. | 6 months |
| Accuracy of our derived prediction algorithm to detect acute exacerbations as measured by the daily symptom score. | We will correlate sensor data from the smartwatch to exacerbations defined by the daily symptom score. The daily symptom score asks about daily symptoms of COPD and patients are asked to answer yes or no to whether or not they have experienced a decline of any of the symptoms | 6 months |
| D020969 |
| Disease Attributes |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |