Ignite Creation Date:
2025-12-24 @ 7:32 PM
Ignite Modification Date:
2025-12-29 @ 4:14 PM
Study NCT ID:
NCT06802003
Status:
RECRUITING
Last Update Posted:
2025-05-28
First Post:
2025-01-25
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Predicting Acute Exacerbations of COPD Using Wearable Devices and Remote Monitoring Technology With AI/ML Models
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D029424', 'term': 'Pulmonary Disease, Chronic Obstructive'}], 'ancestors': [{'id': 'D008173', 'term': 'Lung Diseases, Obstructive'}, {'id': 'D008171', 'term': 'Lung Diseases'}, {'id': 'D012140', 'term': 'Respiratory Tract Diseases'}, {'id': 'D002908', 'term': 'Chronic Disease'}, {'id': 'D020969', 'term': 'Disease Attributes'}, {'id': 'D010335', 'term': 'Pathologic Processes'}, {'id': 'D013568', 'term': 'Pathological Conditions, Signs and Symptoms'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 50}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'RECRUITING', 'startDateStruct': {'date': '2025-05-22', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-05', 'completionDateStruct': {'date': '2026-08-31', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-05-22', 'studyFirstSubmitDate': '2025-01-25', 'studyFirstSubmitQcDate': '2025-01-25', 'lastUpdatePostDateStruct': {'date': '2025-05-28', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2025-01-30', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2026-05-31', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Respiration', 'timeFrame': 'Daily/nightly for 12 months', 'description': 'Respiratory rate (RR) and respiratory rate variability (RRV) measured with wearable devices'}, {'measure': 'Cardiovascular', 'timeFrame': 'Daily/nightly for 12 months', 'description': 'Heart rate (HR) and HR variability (HRV) measured with wearable devices'}, {'measure': 'Oxygen level', 'timeFrame': 'Daily/nightly for 12 months', 'description': 'Blood oxygen saturation (SpO2) measured with wearable devices'}, {'measure': 'Step count', 'timeFrame': 'Daily/nightly for 12 months', 'description': 'Parameter measured with wearable devices, related to activity.'}, {'measure': 'Sleep duration', 'timeFrame': 'Nightly for 12 months', 'description': 'Parameter measured with wearable devices.'}, {'measure': 'Rapid eye movement (REM) sleep', 'timeFrame': 'Nightly for 12 months', 'description': 'Parameter measured with wearable devices.'}, {'measure': 'Deep sleep', 'timeFrame': 'Nightly for 12 months', 'description': 'Parameter measured with wearable devices.'}, {'measure': 'Body temperature', 'timeFrame': 'Nightly for 12 months', 'description': 'Peripheral body temperature measured with wearable devices'}, {'measure': 'Resistance at 5 Hz (R5)', 'timeFrame': 'Daily for 12 months', 'description': 'Parameter measured at 5 Hz frequency with handheld oscillometry, related to lung mechanics/function.'}, {'measure': 'Reactance at 5 Hz (X5)', 'timeFrame': 'Daily for 12 months', 'description': 'Parameter measured at 5 Hz frequency with handheld oscillometry, related to lung mechanics/function.'}, {'measure': 'Intra-breath difference between expiratory and inspiratory reactance (ΔXrs)', 'timeFrame': 'Daily for 12 months', 'description': 'Parameter measured with handheld oscillometry, related to lung mechanics/function.'}, {'measure': 'Tidal volume (Vt)', 'timeFrame': 'Daily for 12 months', 'description': 'Parameter measured with handheld oscillometry, related to lung mechanics/function.'}, {'measure': 'Respiratory flows', 'timeFrame': 'Daily for 12 months', 'description': 'Inspiratory and expiratory flows measured with handheld oscillometry, related to lung mechanics/function.'}, {'measure': 'Respiratory rate (RR)', 'timeFrame': 'Daily for 12 months', 'description': 'Parameter measured with handheld oscillometry.'}, {'measure': 'Minute ventilation (Ve)', 'timeFrame': 'Daily for 12 months', 'description': 'Parameter measured with handheld oscillometry, related to lung mechanics/function.'}, {'measure': 'Heart rate (HR) prior oscillometry test', 'timeFrame': 'Daily for 12 months', 'description': 'Parameter measured with handheld oscillometry before performing oscillometry test.'}, {'measure': 'Blood oxygen saturation (SpO2) prior oscillometry test', 'timeFrame': 'Daily for 12 months', 'description': 'Parameter measured with handheld oscillometry before performing oscillometry test.'}, {'measure': 'Daily symptom questionnaire', 'timeFrame': 'Daily for 12 months', 'description': '• Visual analog scale (VAS) scores for dyspnea, sputum volume, sputum purulence, cough, wheeze, and fatigue, scaled 0-10. Higher scores indicate worse symptoms.'}, {'measure': 'Weekly exacerbation questionnaire', 'timeFrame': 'Weekly for 12 months', 'description': '• Self report on any exacerbation(s) which occurred in the preceding week and their date(s), whether/how the exacerbation was treated, and in what treatment setting.'}, {'measure': 'Calories', 'timeFrame': 'Daily/nightly for 12 months', 'description': 'Parameter measured with wearable devices, related to activity.'}, {'measure': 'Metabolic equivalents', 'timeFrame': 'Daily/nightly for 12 months', 'description': 'Parameter measured with wearable devices, related to activity.'}, {'measure': 'Movement intensity', 'timeFrame': 'Daily/nightly for 12 months', 'description': 'Parameter measured with wearable devices, related to activity.'}, {'measure': 'Sleep efficiency', 'timeFrame': 'Nightly for 12 months', 'description': 'Parameter measured with wearable devices.'}, {'measure': 'Sleep oncet', 'timeFrame': 'Nightly for 12 months', 'description': 'Parameter measured with wearable devices.'}, {'measure': 'Sleep disturbance', 'timeFrame': 'Nightly for 12 months', 'description': 'Parameter measured with wearable devices.'}], 'secondaryOutcomes': [{'measure': 'COPD Assessment Test (CAT)', 'timeFrame': 'Once (baseline visit)', 'description': 'Validated COPD questionnaire consisting of 8 questions and scaled 0-40. Higher scores indicate the severity of disease impact.'}, {'measure': '6-Minute Walk Test (6MWT)', 'timeFrame': 'Once (baseline visit)', 'description': 'Standard and validated assessment in COPD. Outcomes include distance walked as well as heart rate (HR), oxygen saturation (SpO2), and respiratory rate (RR) during the test. the 6MWT will be performed once at baseline while the participant is wearing the biometric wearable devices.'}, {'measure': 'System Usability Scale (SUS)', 'timeFrame': 'Through study completion, 1 year.', 'description': 'Practical and reliable tool to determine the user experience with a variety of systems and devices. Scaled from 1-5, higher scores indicate better experience.'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['acute exacerbation of COPD (AECOPD)', 'chronic obstructive pulmonary disease (COPD)', 'artificial intelligence/machine learning (AI/ML)', 'remote patient monitoring (RPM)', 'biometric wearable device', 'oscillometry'], 'conditions': ['COPD', 'AE COPD']}, 'descriptionModule': {'briefSummary': 'This study is aimed to collect real-time physiological data using two wearable devices (a biometric ring and a biometric wristband), daily lung mechanical measurements by a handheld oscillometer, and participant-reported symptoms in patients with COPD remotely from their home environment. The data will be used to train and validate artificial intelligence and machine learning (AI/ML) models to predict COPD exacerbations in advance of their actual occurrence. The data will also be used to test the new severity classification system for exacerbations of COPD, as well as to determine important relationships between physiological measurements from the wearable devices, the handheld oscillometer, the self-reported symptoms, and the tests performed at the baseline visit.', 'detailedDescription': 'A single-site, prospective, observational cohort study to collect high-quality multidimensional data from the wearable/portable devices, as well as symptom and exacerbation data, in high-risk patients with frequent exacerbations in order to develop a COPD exacerbation predictive model.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '40 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Patients with COPD with a documented history of frequent exacerbations.\n\nWhile there is no specific method to estimate sample sizes for machine learning-based clinical research, based on two prior COPD studies measuring respiratory rate (RR) differences between stable-state and peak exacerbation phases, it was estimated that detecting a 4 breaths/min difference in RR (effect size 0.74) requires 17 prospectively collected exacerbation events, with alpha set to 0.05, power set to 0.8, and two-tailed analysis. Detecting a more subtle difference (i.e. 2 breaths/min; effect size 0.36) would require 63 events.\n\nAssuming each participant experiences two exacerbations annually, 32 participants would meet these requirements. To account for the long observation period, the potential for non-events, and a 25% attrition rate, up to 50 participants will be recruited for this one-year study.', 'healthyVolunteers': False, 'eligibilityCriteria': "Inclusion Criteria:\n\n* Males/females, age ≥ 40, former/current smokers with ≥10 pack-year smoking history\n* FEV1/FVC \\< 0.7, with 80% \\< FEV1 ≤50% (moderate, 'GOLD 2') 50% \\< FEV1 ≤ 30% (severe, 'GOLD 3') or FEV1 \\< 30% (very severe, 'GOLD 4') COPD\n* History of 2 or more exacerbations in the preceding 12 months requiring corticosteroids, antibiotics, or both\n* Ability to provide informed consent\n* Ability to access internet at least once daily\n\nExclusion Criteria:\n\n* No existing COPD diagnosis\n* Any medical/cognitive/functional condition which renders inability to operate research equipment/devices, and/or to complete daily symptom response"}, 'identificationModule': {'nctId': 'NCT06802003', 'acronym': 'ePredictAECOPD', 'briefTitle': 'Predicting Acute Exacerbations of COPD Using Wearable Devices and Remote Monitoring Technology With AI/ML Models', 'organization': {'class': 'OTHER', 'fullName': 'McGill University Health Centre/Research Institute of the McGill University Health Centre'}, 'officialTitle': 'Early Prediction of Acute Exacerbations of COPD Using Wearable and Portable Remote Monitoring Technology With AI/ML Empowered Platforms: A Prospective Clinical Study', 'orgStudyIdInfo': {'id': '2025-10606'}}, 'armsInterventionsModule': {'interventions': [{'name': 'Biometric wearable and handheld devices', 'type': 'DEVICE', 'description': 'In this study, participants will be equipped with biometric wearable devices, i.e. ring and wristband, as well as with a handheld oscillometer, to measure their physiological parameters and lung mechanical changes (lung function).'}]}, 'contactsLocationsModule': {'locations': [{'zip': 'H4A 3J1', 'city': 'Montreal', 'state': 'Quebec', 'status': 'RECRUITING', 'country': 'Canada', 'contacts': [{'name': 'Bryan A. Ross', 'role': 'CONTACT', 'email': 'bryan.ross@mcgill.ca', 'phone': '(514) 843-1465'}], 'facility': 'McGill University Health Centre', 'geoPoint': {'lat': 45.50884, 'lon': -73.58781}}], 'centralContacts': [{'name': 'Bryan A. Ross, MD, MSc (Physiol), MSc (Epi)', 'role': 'CONTACT', 'email': 'bryan.ross@mcgill.ca', 'phone': '(514) 843-1465'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO', 'description': 'Due to data privacy regulations, individual participant data collected during this study is not publicly accessible. However, access to anonymized data may be granted upon evaluation by the trial management group. Additional documents will also be available upon inquiry. All requests should be directed to the corresponding author (BAR).'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'McGill University Health Centre/Research Institute of the McGill University Health Centre', 'class': 'OTHER'}, 'collaborators': [{'name': 'Restech Srl', 'class': 'INDUSTRY'}], 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Clinician-Scientist (RI-MUHC), Respirologist (MUHC), Assistant Professor (McGill University)', 'investigatorFullName': 'Bryan A. Ross', 'investigatorAffiliation': 'McGill University Health Centre/Research Institute of the McGill University Health Centre'}}}}