Ignite Creation Date:
2025-12-25 @ 12:05 AM
Ignite Modification Date:
2025-12-25 @ 10:04 PM
Study NCT ID:
NCT05167058
Status:
COMPLETED
Last Update Posted:
2023-10-03
First Post:
2021-12-08
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Electrocardiographic Diagnostic Performance of the Apple Watch Augmented With an Artificial Intelligence Algorithm
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D001281', 'term': 'Atrial Fibrillation'}, {'id': 'D013610', 'term': 'Tachycardia'}, {'id': 'D001919', 'term': 'Bradycardia'}, {'id': 'D018880', 'term': 'Atrial Premature Complexes'}, {'id': 'D018879', 'term': 'Ventricular Premature Complexes'}], 'ancestors': [{'id': 'D001145', 'term': 'Arrhythmias, Cardiac'}, {'id': 'D006331', 'term': 'Heart Diseases'}, {'id': 'D002318', 'term': 'Cardiovascular Diseases'}, {'id': 'D010335', 'term': 'Pathologic Processes'}, {'id': 'D013568', 'term': 'Pathological Conditions, Signs and Symptoms'}, {'id': 'D000075224', 'term': 'Cardiac Conduction System Disease'}, {'id': 'D005117', 'term': 'Cardiac Complexes, Premature'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'CASE_ONLY'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 220}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2022-04-21', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2023-10', 'completionDateStruct': {'date': '2023-03-31', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2023-10-02', 'studyFirstSubmitDate': '2021-12-08', 'studyFirstSubmitQcDate': '2021-12-08', 'lastUpdatePostDateStruct': {'date': '2023-10-03', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2021-12-22', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2023-01-20', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Evaluation of the performance of smartwatch ECG interpreted by Cardiologs Artificial Intelligence in detecting AF (Atrial Fibrillation or Flutter) as identified by the physician on the 12-lead ECG', 'timeFrame': 'Readings taken simultaneously right before and right after the cardioversion according to the monitoring protocol at the hospital', 'description': 'Evaluation of the performance of smartwatch ECG interpreted by Cardiologs Artificial Intelligence in detecting AF (Atrial Fibrillation or Flutter) as identified by the physician on the 12-lead ECG in the independent annotation center, providing the ground truth from the 12-lead ECG'}], 'secondaryOutcomes': [{'measure': 'Evaluation of the performance of smartwatch ECG interpreted by Cardiologs Artificial Intelligence in detecting AF as identified by the physician on the smartwatch ECG', 'timeFrame': 'Readings taken simultaneously right before and right after the cardioversion according to the monitoring protocol at the hospital', 'description': 'Evaluation of the performance of smartwatch ECG interpreted by Cardiologs Artificial Intelligence in detecting AF as identified by the physician on the smartwatch ECG in the independent annotation center, providing the ground truth from the smartwatch ECG.'}, {'measure': 'Evaluation of the performance of smartwatch ECG interpreted by Cardiologs Artificial Intelligence in detecting Sinus Rhythm as identified by the physician on the smartwatch ECG', 'timeFrame': 'Readings taken simultaneously right before and right after the cardioversion according to the monitoring protocol at the hospital', 'description': 'Evaluation of the performance of smartwatch ECG interpreted by Cardiologs Artificial Intelligence in detecting Sinus Rhythm as identified by the physician on the smartwatch ECG in the independent annotation center, providing the ground truth from the smartwatch ECG.'}, {'measure': 'Evaluation of the performance of smartwatch ECG interpreted by Cardiologs Artificial Intelligence in detecting Tachycardia as identified by the physician on the smartwatch ECG', 'timeFrame': 'Readings taken simultaneously right before and right after the cardioversion according to the monitoring protocol at the hospital', 'description': 'Evaluation of the performance of smartwatch ECG interpreted by Cardiologs Artificial Intelligence in detecting Tachycardia as identified by the physician on the smartwatch ECG in the independent annotation center, providing the ground truth from the smartwatch ECG.'}, {'measure': 'Evaluation of the performance of smartwatch ECG interpreted by Cardiologs Artificial Intelligence in detecting Bradycardia as identified by the physician on the smartwatch ECG', 'timeFrame': 'Readings taken simultaneously right before and right after the cardioversion according to the monitoring protocol at the hospital', 'description': 'Evaluation of the performance of smartwatch ECG interpreted by Cardiologs Artificial Intelligence in detecting Bradycardia as identified by the physician on the smartwatch ECG in the independent annotation center, providing the ground truth from the smartwatch ECG.'}, {'measure': 'Evaluation of the performance of smartwatch ECG interpreted by Cardiologs Artificial Intelligence in detecting Premature Supraventricular Complexes as identified by the physician on the smartwatch ECG', 'timeFrame': 'Readings taken simultaneously right before and right after the cardioversion according to the monitoring protocol at the hospital', 'description': 'Evaluation of the performance of smartwatch ECG interpreted by Cardiologs Artificial Intelligence in detecting Premature Supraventricular Complexes as identified by the physician on the smartwatch ECG in the independent annotation center, providing the ground truth from the smartwatch ECG.'}, {'measure': 'Evaluation of the performance of smartwatch ECG interpreted by Cardiologs Artificial Intelligence in detecting Premature Ventricular Complexes as identified by the physician on the smartwatch ECG', 'timeFrame': 'Readings taken simultaneously right before and right after the cardioversion according to the monitoring protocol at the hospital', 'description': 'Evaluation of the performance of smartwatch ECG interpreted by Cardiologs Artificial Intelligence in detecting Premature Ventricular Complexes as identified by the physician on the smartwatch ECG in the independent annotation center, providing the ground truth from the smartwatch ECG.'}, {'measure': 'Assessment of the proportion of smartwatch ECGs identified as inconclusive by Cardiologs Artificial Intelligence and by the physician', 'timeFrame': 'Readings taken simultaneously right before and right after the cardioversion according to the monitoring protocol at the hospital', 'description': 'Assessment of the proportion of smartwatch ECGs identified as inconclusive by Cardiologs Artificial Intelligence and by the physician. Inconclusive may mean that there may have been too much artefact or noise to acquire a good signal or that the rhythm is unclassifiable or contains other abnormal rhythm.'}]}, 'oversightModule': {'isUsExport': False, 'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': True}, 'conditionsModule': {'conditions': ['Atrial Fibrillation', 'Tachycardia', 'Bradycardia', 'Premature Supraventricular Beat', 'Premature Ventricular Contraction']}, 'descriptionModule': {'briefSummary': 'The SWAF study will compare the performance of a smartwatch combined with Cardiologs Platform algorithm in the detection of Atrial Fibrillation and other arrhythmias with that measured on a manually read 12-lead ECG in subjects hospitalized for cardioversion or AF ablation.', 'detailedDescription': 'The SWAF study is a prospective, non-significant risk, non-randomized, multicentric, open, comparative, confirmatory study.\n\nUnder subject consent, subjects hospitalized for cardioversion or AF ablation will have a smartwatch ECG recording done simultaneously with 12-lead ECG measurement right before the intervention. If a subject is found in Normal Sinus Rhythm he/she will be discharged otherwise the patient will undergo cardioversion and will have simultaneous recordings done a second time after the intervention. All the measurements will be done in accordance with the existing subject monitoring protocol.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': '200 subjects: subjects who are hospitalized for cardioversion or AF ablation procedure per standard of care', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Subjects over 18, able and willing to participate in the study\n* Subjects who are admitted to the hospital for a cardioversion or AF ablation procedure.\n* Subjects having read the patient information letter and provided his/her consent to participate in writing, by dating and signing the informed consent prior to any trial-related procedure being conducted\n\nExclusion Criteria:\n\n* Subjects with paced rhythm or implanted electronic devices\n* Pregnant or breast-feeding subjects'}, 'identificationModule': {'nctId': 'NCT05167058', 'briefTitle': 'Electrocardiographic Diagnostic Performance of the Apple Watch Augmented With an Artificial Intelligence Algorithm', 'organization': {'class': 'INDUSTRY', 'fullName': 'Cardiologs Technologies'}, 'officialTitle': 'Confirmatory Clinical Investigation of Electrocardiographic Diagnostic Performance of the Apple Watch Augmented With an Artificial Intelligence Algorithm', 'orgStudyIdInfo': {'id': 'SWAF'}}, 'armsInterventionsModule': {'interventions': [{'name': 'Cardiologs Platform', 'type': 'DEVICE', 'otherNames': ['Smartwatch'], 'description': 'Smartwatch recordings interpreted by Cardiologs AI done simultaneously with each 12-lead ECG'}]}, 'contactsLocationsModule': {'locations': [{'zip': '07601', 'city': 'Hackensack', 'state': 'New Jersey', 'country': 'United States', 'facility': 'Hackensack Meridian School of Medicine', 'geoPoint': {'lat': 40.88593, 'lon': -74.04347}}, {'zip': '07450', 'city': 'Ridgewood', 'state': 'New Jersey', 'country': 'United States', 'facility': 'The Valley Hospital', 'geoPoint': {'lat': 40.97926, 'lon': -74.11653}}, {'zip': '10032', 'city': 'New York', 'state': 'New York', 'country': 'United States', 'facility': 'Columbia University Medical Center/ NewYork Presbyterian Hospital', 'geoPoint': {'lat': 40.71427, 'lon': -74.00597}}], 'overallOfficials': [{'name': 'Elaine Y Wan, MD', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Columbia University, New York'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Cardiologs Technologies', 'class': 'INDUSTRY'}, 'responsibleParty': {'type': 'SPONSOR'}}}}