The DOI matches its Crossref record; 13 of the 14 references it cites were found in a registry or an index.
Assessing the accuracy of an automated atrial fibrillation detection algorithm using smartphone technology: The iREAD Study
Abstract
Background The Kardia Mobile Cardiac Monitor (KMCM) detects atrial fibrillation (AF) via a handheld cardiac rhythm recorder and AF detection algorithm. The algorithm operates within predefined parameters to provide a "normal" or "possible atrial fibrillation detected" interpretation; outside of these parameters, an "unclassified" rhythm is reported. The system has been increasingly used, but its performance has not been independently tested.Objective The objective of this study was to evaluate whether the KMCM system can accurately detect AF.Methods A single-center, adjudicator-blinded case series of 52 consecutive patients with AF admitted for antiarrhythmic drug initiation were enrolled. Serial 12-lead electrocardiograms (ECGs) and nearly simultaneously acquired KMCM recordings were obtained.Results There were 225 nearly simultaneously acquired KMCM and ECG recordings across 52 enrolled patients (mean age 68 years; 67% male). After exclusion of unclassified recordings, the KMCM automated algorithm interpretation had 96.6% sensitivity and 94.1% specificity for AF detection as compared with physician-interpreted ECGs, with a κ coefficient of 0.89. Physician-interpreted KMCM recordings had 100% sensitivity and 89.2% specificity for AF detection as compared with physician-interpreted ECGs, with a κ coefficient of 0.85. Sixty-two recordings (27.6%) were unclassified by the KMCM algorithm. In these instances, physician interpretation of KMCM recordings had 100% sensitivity and 79.5% specificity for AF detection as compared with 12-lead ECG interpretation, with a κ coefficient of 0.71.Conclusion The KMCM system provides sensitive and specific AF detection relative to 12-lead ECGs when an automated interpretation is provided. Direct physician review of KMCM recordings can enhance diagnostic yield, especially for unclassified recordings.
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“the automatic diagnostic algorithm has excellent sensitivity (96.6%) and specificity (94%) for correctly interpreting AF versus normal sinus rhythm [15].”
From Multi-centre Randomised Controlled Trial of a Smartphone-based Event Recorder Alongside Standard Care Versus Standard Care for Patients Presenting to the Emergency Department with Palpitations and Pre-syncope: The IPED (Investigation of Palpitations in the ED) study (2019) · cites this paper as [15]
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Hindricks, G., Potpara, T., Dagres, N., Arbelo, E., Bax, J. J., Blomström‐Lundqvist, C., Boriani, G., Castella, M., Dan, G.-A., Dilaveris, P., et al. (2020) · European Heart Journal · doi:10.1093/eurheartj/ehaa612 · Cited by 10,550
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How useful is the smartwatch ECG?
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Metadata
- Authors
- William, A. D., Kanbour, M., Callahan, T., Bhargava, M., Varma, N., Rickard, J., Saliba, W., Wolski, K., Hussein, A., Lindsay, B. D., Wazni, O. M., & Tarakji, K. G.
- Affiliations
- Cleveland Clinic (US)
- Marshall University (US)
- Corresponding author
- Tarakji, Khaldoun G.
- ORCID
- Venue
- Heart Rhythm
- Publisher
- Elsevier BV
- Published
- 2018-10
- Volume
- 15
- Issue
- 10
- Pages
- 1561-1565
- ISSN
- 1547-5271 (ISSN-L)
- OpenAlex
- W2888509599
- Cited by
- 154
- References
- 14
- Citations by year
- 2026: 5 · 2025: 7 · 2024: 10 · 2023: 32 · 2022: 19 · 2021: 30 · 2020: 25 · 2019: 23 · 2018: 2
- FWCI
- 15.07
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Heart Rhythm (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › ECG Monitoring and Analysis
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Atrial Fibrillation Management and Outcomes
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Keywords
- atrial fibrillation, diagnostic accuracy, sensitivity and specificity, 12-lead ECG
- MeSH terms
- Smartphone, Adult, Aged, Aged, 80 and over, Algorithms, Atrial Fibrillation, Electrocardiography, Female, Heart Conduction System, Humans, Male, Middle Aged, Predictive Value of Tests, Signal Processing, Computer-Assisted, Telemetry, Reproducibility of Results, Single-Blind Method, Mobile Applications
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