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. 2023 May 24;25(Suppl 1):euad122.063. doi: 10.1093/europace/euad122.063

Diagnostic accuracy of smart gadgets/wearable devices in detecting atrial fibrillation in primary prevention: a meta-analysis

G Vetta 1, M Magnocavallo 2, A Parlavecchio 3, R Caminiti 4, M Polselli 5, A Sorgente 6, L Pannone 7, G B Chierchia 8, P Rossi 9, S Bianchi 10, A Natale 11, C De Asmundis 12, D G Della Rocca 13
PMCID: PMC10207136

Abstract

Funding Acknowledgements

Type of funding sources: None.

Introduction

Atrial fibrillation (AF) is the most common sustained arrhythmia and an important risk factor for stroke and heart. Recent technology advances have allowed for heart rhythm monitoring using smart gadgets/wearable devices which can be used for early AF diagnosis.

Purpose

We performed a systemic review and meta-analysis to assess the accuracy of AF diagnosis by smart gadgets/wearable devices in primary prevention.

Methods

We systematically searched Medline, Embase and Cochrane electronic databases up to September 22th, 2022 for observational studies of the diagnostic accuracy of smartphone application, wrist-worn wearables and external devices in detecting AF in primary prevention. Studies with 12-lead ECG or single-lead ECG interpreted by a cardiologist as gold standard were included. We calculated the area under the curve (AUC) of the summary receiver operating characteristic curves (SROC) and pooled sensitivities and specificities.

Results

A total of 28 studies were included enrolling 13463 patients, 57%(95% CI: 55-59%) male with average age of 65.3years (95% CI: 60.1 – 70.4). The pooled prevalence of AF was found to be 13% (95% CI 10 – 15%). In the overall analysis of all devices, the AUC was 0.99 (95% CI: 0.97-0.99)(Figure 1), the sensitivity 93%(95% CI: 89 – 95%) and the specificity 97%(95% CI: 95 – 98%) (Figure 2). Wrist-worn wearables had AUC of 0.97 (95% CI: 0.94-0.99), the sensitivity 83%(95% CI: 52 – 96%) and the specificity 98%(95% CI: 87 – 100%). Smartphone applications had AUC of 0.97 (95% CI: 0.96-0.98), the sensitivity 92%(95% CI: 77 – 98%) and the specificity 95%(95% CI: 91 – 97%). External devices had AUC of 0.99 (95% CI: 0.97-0.99), the sensitivity 94%(95% CI: 91 – 96%) and the specificity 97%(95% CI: 95 – 98%). Single-lead ECG had AUC of 0.99 (95% CI: 0.97- 0.99), the sensitivity 93%(95% CI: 88 – 96%) and the specificity 91%(95% CI: 78 – 97%). photoplethysmography pulse waveform technology (PPG) had AUC of 0.97 (95% CI: 0.96-0.98), the sensitivity 91%(95% CI: 78 – 97%) and the specificity 95%(95% CI: 91 – 97%). Pulse beat interval technology had AUC of 0.99 (95% CI: 0.98-0.99), the sensitivity 95%(95% CI: 90 – 98%) and the specificity 96%(95% CI: 93 – 98%)

Conclusions

Smartphone application, wrist-worn devices and external devices have excellent diagnostic accuracy in atrial fibrillation diagnosis in primary prevention.

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