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Original research
Accuracy of a smartwatch based single-lead electrocardiogram device in detection of atrial fibrillation
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  1. Kevin Rajakariar1,
  2. Anoop N Koshy2,
  3. Jithin K Sajeev1,
  4. Sachin Nair3,
  5. Louise Roberts1,3,
  6. Andrew W Teh1,3
  1. 1 Department of Cardiology, Box Hill Hospital, Box Hill, Victoria, Australia
  2. 2 Department of Cardiology, University of Melbourne, Austin Health, Melbourne, Victoria, Australia
  3. 3 Eastern Health Clinical School, Monash University, Clayton, Victoria, Australia
  1. Correspondence to Dr Andrew W Teh, Department of Cardiology, Box Hill Hospital, Box Hill, Victoria 3128, Australia; andrew.teh{at}easternhealth.org.au

Abstract

Objective The AliveCor KardiaBand (KB) is an Food and Drug Administration-approved smartwatch-based cardiac rhythm monitor that records a lead-Intelligent ECG (iECG). Despite the appeal of wearable integrated ECG devices, there is a paucity of data evaluating their accuracy in diagnosing atrial fibrillation (AF). We evaluated whether a smartwatch-based device for AF detection is an accurate tool for diagnosing AF when compared with 12-lead ECG.

Methods A prospective, multi-centre, validation study was conducted in an inpatient hospital setting. The KB paired with a smartwatch, generated an automated diagnosis of AF or sinus rhythm (SR). This was compared with a 12-lead ECG performed immediately after iECG tracing. Where an unclassified or no-analysis tracing was generated, repeat iECG was performed.

Results 439 ECGs (iECGs (n=239) and 12-lead ECG (n=200)) were recorded in 200 patients (AF: n=38; SR: n=162) from three tertiary centres. Sensitivity and specificity using KB was 94.4% and 81.9% respectively, with a positive predictive value of 54.8% and negative predictive value of 98.4%. Agreement between 12-lead ECG and KB diagnosis was moderate when unclassified tracings were included (κ=0.60, 95% CI 0.47 to 0.72). Combining the automated device diagnosis with blinded electrophysiologists (EP) interpretation of unclassified tracings improved overall agreement (EP1: κ=0.76, 95% CI 0.65 to 0.87; EP2: κ=0.74, 95% CI 0.63 to 0.86).

Conclusion The KB demonstrated moderate diagnostic accuracy when compared with a 12-lead ECG. Combining the automated device diagnosis with EP interpretation of unclassified tracings yielded improved accuracy. However, even with future improvements in automated algorithms, physician involvement will likely remain an essential component when exploring the utility of these devices for arrhythmia screening.

Clinical trial registration URL: https://www.anzctr.org.au/ Unique identifier: ACTRN12616001374459.

  • AliveCor
  • KardiaBand
  • atrial fibrillation
  • smartwatch
  • mobile health
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Footnotes

  • KR and ANK are joint first authors.

  • Twitter @DrAnoop_Koshy

  • Contributors KR and ANK equally contributed to the initial manuscript draft, recruitment and data analysis. SN was involved in data collection. JKS and LR contributed to data analysis and draft revision. AWT reviewed the data, edited and approved the final submitted draft.

  • Funding This work was supported by the Eastern Health Foundation Research Grant [EHFRG2017_029]. The sponsor had no role in study design, collection, analysis, interpretation of data and in the decision to submit the article for publication. Dr. Koshy is supported by scholarships from the National Health and Medical Research Council of Australia, National Heart Foundation and The Royal Australasian College of Physicians.

  • Competing interests None declared.

  • Patient consent for publication Not required.

  • Ethics approval Institutional ethics review board approval of the study protocol (LR55-2016).

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement All data relevant to the study are included in the article or uploaded as supplementary information. Data are available upon reasonable request

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