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A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program
Published on: April 19, 2019
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Can eHealth programs for cardiac arrhythmias be scaled-up by using the KardiaMobile algorithm?
Bridget M I Slaats1,2, Sebastiaan Blok1,2, G Aernout Somsen1
1Cardiology Centers of the Netherlands, Utrecht, The Netherlands.
Cardiovascular Digital Health Journal
|May 20, 2024
Summary
The KardiaMobile algorithm demonstrates high accuracy in detecting sinus rhythm and atrial fibrillation in remote monitoring. This suggests its potential as a standalone diagnostic tool, especially for sinus rhythm detection.
Area of Science:
- Cardiology
- Digital Health
- Medical Devices
Background:
- Remote monitoring devices improve atrial fibrillation diagnosis and treatment adherence.
- Current algorithms have variable accuracy, necessitating manual review of electrocardiographic (ECG) recordings.
Purpose of the Study:
- To validate the KardiaMobile algorithm's performance within the Dutch HartWacht telemonitoring program.
Main Methods:
- Retrospective analysis of 86,816 ECGs from 2298 patients.
- Diagnostic accuracy assessed against a telemonitoring team's reference.
- Key metrics included sensitivity, specificity, PPV, NPV, and F1 scores.
Main Results:
- For sinus rhythm: sensitivity 0.956, specificity 0.985, PPV 0.996, F1 score 0.976.
- For atrial fibrillation: sensitivity 0.989, specificity 0.953, NPV 0.997, F1 score 0.906.
- Identified 29 uncorrected false positives for sinus rhythm and 2 false negatives for atrial fibrillation.
Conclusions:
- The KardiaMobile algorithm shows high validity for detecting sinus rhythm and good validity for atrial fibrillation.
- The algorithm shows promise as a standalone tool, particularly for sinus rhythm detection.
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