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Completed

NCT Number: NCT05167058

Electrocardiographic Diagnostic Performance of the Apple Watch Augmented With an Artificial Intelligence Algorithm

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.

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Key information

Conditions

Atrial Fibrillation Arrhythmias, Cardiac Atrial Premature Complexes Bradycardia Cardiac Complexes, Premature Cardiac Conduction System Disease Cardiovascular Diseases Heart Diseases Pathologic Processes Pathological Conditions, Signs and Symptoms Premature Supraventricular Beat Premature Ventricular Contraction Tachycardia Ventricular Premature Complexes

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Hackensack Meridian School of Medicine, Hackensack, New Jersey, United States

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About this study

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.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Subjects over 18, able and willing to participate in the study
  • Subjects who are admitted to the hospital for a cardioversion or AF ablation procedure.
  • 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

Exclusion criteria

  • Subjects with paced rhythm or implanted electronic devices
  • Pregnant or breast-feeding subjects

Treatment and study plan

Cardiologs Platform

Device

Smartwatch recordings interpreted by Cardiologs AI done simultaneously with each 12-lead ECG

Other names: Smartwatch

Primary outcomes

  1. 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

    Time frame: 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 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

Secondary outcomes

  1. Evaluation of the performance of smartwatch ECG interpreted by Cardiologs Artificial Intelligence in detecting AF as identified by the physician on the smartwatch ECG

    Time frame: 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 AF as identified by the physician on the smartwatch ECG in the independent annotation center, providing the ground truth from the smartwatch ECG.

  2. 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

    Time frame: 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 in the independent annotation center, providing the ground truth from the smartwatch ECG.

  3. Evaluation of the performance of smartwatch ECG interpreted by Cardiologs Artificial Intelligence in detecting Tachycardia as identified by the physician on the smartwatch ECG

    Time frame: 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 in the independent annotation center, providing the ground truth from the smartwatch ECG.

  4. Evaluation of the performance of smartwatch ECG interpreted by Cardiologs Artificial Intelligence in detecting Bradycardia as identified by the physician on the smartwatch ECG

    Time frame: 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 in the independent annotation center, providing the ground truth from the smartwatch ECG.

  5. 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

    Time frame: 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 in the independent annotation center, providing the ground truth from the smartwatch ECG.

  6. 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

    Time frame: 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 in the independent annotation center, providing the ground truth from the smartwatch ECG.

  7. Assessment of the proportion of smartwatch ECGs identified as inconclusive by Cardiologs Artificial Intelligence and by the physician

    Time frame: 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. 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.

Sponsors and collaborators

Lead sponsor

Cardiologs Technologies

Industry

Registry information

Official study title

Confirmatory Clinical Investigation of Electrocardiographic Diagnostic Performance of the Apple Watch Augmented With an Artificial Intelligence Algorithm

Important dates

Study start
2022
Primary completion
2023
Study completion
2023
First posted
Dec 22, 2021
Registry last updated
Oct 3, 2023

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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