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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.
The SWAF study is a prospective, non-significant risk, non-randomized, multicentric, open, comparative, confirmatory study.
Under 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.
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Cardiologs Platform | Device | Smartwatch recordings interpreted by Cardiologs AI done simultaneously with each 12-lead ECG |
|
| Measure | Description | Time Frame |
|---|---|---|
| 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 | 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 | Readings taken simultaneously right before and right after the cardioversion according to the monitoring protocol at the hospital |
| Measure | Description | Time Frame |
|---|---|---|
| Evaluation of the performance of smartwatch ECG interpreted by Cardiologs Artificial Intelligence in detecting AF as identified by the physician on the smartwatch ECG | 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. |
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Inclusion Criteria:
Exclusion Criteria:
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200 subjects: subjects who are hospitalized for cardioversion or AF ablation procedure per standard of care
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| Name | Affiliation | Role |
|---|---|---|
| Elaine Y Wan, MD | Columbia University, New York | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Hackensack Meridian School of Medicine | Hackensack | New Jersey | 07601 | United States | ||
| The Valley Hospital |
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| Readings taken simultaneously right before and right after the cardioversion according to the monitoring protocol at the hospital |
| 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 | 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. | Readings taken simultaneously right before and right after the cardioversion according to the monitoring protocol at the hospital |
| Evaluation of the performance of smartwatch ECG interpreted by Cardiologs Artificial Intelligence in detecting Tachycardia as identified by the physician on the smartwatch ECG | 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. | Readings taken simultaneously right before and right after the cardioversion according to the monitoring protocol at the hospital |
| Evaluation of the performance of smartwatch ECG interpreted by Cardiologs Artificial Intelligence in detecting Bradycardia as identified by the physician on the smartwatch ECG | 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. | Readings taken simultaneously right before and right after the cardioversion according to the monitoring protocol at the hospital |
| 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 | 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. | Readings taken simultaneously right before and right after the cardioversion according to the monitoring protocol at the hospital |
| 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 | 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. | Readings taken simultaneously right before and right after the cardioversion according to the monitoring protocol at the hospital |
| Assessment of the proportion of smartwatch ECGs identified as inconclusive by Cardiologs Artificial Intelligence and by the physician | 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. | Readings taken simultaneously right before and right after the cardioversion according to the monitoring protocol at the hospital |
| Ridgewood |
| New Jersey |
| 07450 |
| United States |
| Columbia University Medical Center/ NewYork Presbyterian Hospital | New York | New York | 10032 | United States |
| ID | Term |
|---|---|
| D001281 | Atrial Fibrillation |
| D013610 | Tachycardia |
| D001919 | Bradycardia |
| D018880 | Atrial Premature Complexes |
| D018879 | Ventricular Premature Complexes |
| ID | Term |
|---|---|
| D001145 | Arrhythmias, Cardiac |
| D006331 | Heart Diseases |
| D002318 | Cardiovascular Diseases |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |
| D000075224 | Cardiac Conduction System Disease |
| D005117 | Cardiac Complexes, Premature |
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