Ignite Creation Date:
2025-12-24 @ 11:33 PM
Ignite Modification Date:
2025-12-25 @ 9:21 PM
Study NCT ID:
NCT04543656
Status:
UNKNOWN
Last Update Posted:
2021-09-28
First Post:
2020-08-10
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Personalized Blood Pressure Care Using IoMTs and Artificial Intelligence
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24', 'submissionTracking': {'submissionInfos': [{'resetDate': '2023-01-27', 'releaseDate': '2022-04-21'}], 'estimatedResultsFirstSubmitDate': '2022-04-21'}}, 'conditionBrowseModule': {'meshes': [{'id': 'D058246', 'term': 'Prehypertension'}], 'ancestors': [{'id': 'D014652', 'term': 'Vascular Diseases'}, {'id': 'D002318', 'term': 'Cardiovascular Diseases'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'RANDOMIZED', 'maskingInfo': {'masking': 'SINGLE', 'whoMasked': ['PARTICIPANT']}, 'primaryPurpose': 'PREVENTION', 'interventionModel': 'PARALLEL'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 100}}, 'statusModule': {'overallStatus': 'UNKNOWN', 'lastKnownStatus': 'RECRUITING', 'startDateStruct': {'date': '2020-10-01', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2021-09', 'completionDateStruct': {'date': '2022-06', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2021-09-27', 'studyFirstSubmitDate': '2020-08-10', 'studyFirstSubmitQcDate': '2020-09-02', 'lastUpdatePostDateStruct': {'date': '2021-09-28', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2020-09-10', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2022-06', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Average change in systolic blood pressure (SBP) in experimental vs. control group', 'timeFrame': 'Initial 2 week data collection, weekly lifestyle recommendations, 6 months total', 'description': "Average SBP during the first and last week of a patient's enrollment will be used to calculate SBP change for each patient."}, {'measure': 'Average change in diastolic blood pressure (DBP) in experimental vs. control group', 'timeFrame': 'Initial 2 week data collection, weekly lifestyle recommendations, 6 months total', 'description': "Average DBP during the first and last week of a patient's enrollment will be used to calculate DBP change for each patient."}], 'secondaryOutcomes': [{'measure': 'Number of patients in experimental group that followed lifestyle recommendations', 'timeFrame': 'Initial 2 week data collection, weekly lifestyle recommendations, 6 months total', 'description': 'This secondary outcome measure is interested in assessing patient engagement within the experimental group. Data from the activity tracker (steps, sleep quality, active minutes, etc.) will be used to assess whether a patient followed the lifestyle recommendations.'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Pre-hypertension']}, 'referencesModule': {'seeAlsoLinks': [{'url': 'https://ieeexplore.ieee.org/abstract/document/8822927', 'label': 'Offline and Online Learning Techniques for Personalized Blood Pressure Prediction and Health Behavior Recommendations'}]}, 'descriptionModule': {'briefSummary': 'In this RCT, up to 100 adults classified as pre-hypertensive will be randomized to either an artificial intelligence (AI) based lifestyle intervention group or an active control group with a 1 to 1 ratio. Both groups will receive an identical activity tracker (Samsung Galaxy Watch) and BP monitor (Omron Evolv). The AI intervention group will receive automated and personalized lifestyle recommendations based on their lifestyle (e.g. sleep, exercise and diet) and blood pressure (BP) data, involving an automated analytics engine using statistics and machine learning. The active control group will not receive these lifestyle recommendations. The investigators aim to assess objectively the effectiveness of the AI-based personalized lifestyle recommendations on the patients BP.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* age ≥18 years\n* SBP between 130 mmHg to 139 mmHg or/and DBP between 80 to 89 mmHg in a research office\n* speaking and reading English\n* having an iPhone 8 or newer or an Android x or newer\n\nExclusion Criteria:\n\n* currently taking antihypertensive medication\n* self-reported diagnosis of coronary heart disease, medical condition or other physical problem necessitating special attention in an exercise program (e.g., cancer, eating disorder, uncontrolled diabetes)\n* current participation in a lifestyle modification program or research study\n* self-report of being currently pregnant'}, 'identificationModule': {'nctId': 'NCT04543656', 'briefTitle': 'Personalized Blood Pressure Care Using IoMTs and Artificial Intelligence', 'organization': {'class': 'OTHER', 'fullName': 'University of California, San Diego'}, 'officialTitle': 'Personalized Blood Pressure Care for Prehypertensive Patients Using IoMTs and Artificial Intelligence', 'orgStudyIdInfo': {'id': '1'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'AI-Based Lifestyle Recommendations Group', 'description': 'Participants in this group receive AI-based, personalized lifestyle recommendations based on analysis of their activity tracker and blood pressure data.', 'interventionNames': ['Behavioral: AI-Based Lifestyle Recommendations']}, {'type': 'ACTIVE_COMPARATOR', 'label': 'Control Group', 'description': 'Participants in this group do not receive the lifestyle recommendations, but are provided with an identical activity tracker and blood pressure monitor.', 'interventionNames': ['Other: No Lifestyle Recommendations']}], 'interventions': [{'name': 'AI-Based Lifestyle Recommendations', 'type': 'BEHAVIORAL', 'description': 'The intervention provides participants with automated and personalized lifestyle recommendations involving a sophisticated analytics engine using advanced statistics and machine learning.', 'armGroupLabels': ['AI-Based Lifestyle Recommendations Group']}, {'name': 'No Lifestyle Recommendations', 'type': 'OTHER', 'description': 'The control group receives an identical activity tracker and BP monitor in order to objectively assess the effectiveness of the experimental group intervention.', 'armGroupLabels': ['Control Group']}]}, 'contactsLocationsModule': {'locations': [{'zip': '92093', 'city': 'La Jolla', 'state': 'California', 'status': 'RECRUITING', 'country': 'United States', 'contacts': [{'name': 'Sujit Dey', 'role': 'CONTACT'}], 'facility': 'University of California, San Diego', 'geoPoint': {'lat': 32.84727, 'lon': -117.2742}}], 'centralContacts': [{'name': 'Sujit Dey, PhD', 'role': 'CONTACT', 'email': 'dey@eng.ucsd.edu', 'phone': '8587617518'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'University of California, San Diego', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Principal Investigator', 'investigatorFullName': 'Sujit Dey', 'investigatorAffiliation': 'University of California, San Diego'}}}, 'annotationSection': {'annotationModule': {'unpostedAnnotation': {'unpostedEvents': [{'date': '2022-04-21', 'type': 'RELEASE'}, {'date': '2023-01-27', 'type': 'RESET'}], 'unpostedResponsibleParty': 'Sujit Dey, Principal Investigator, University of California, San Diego'}}}}