1120 DIAGNOSTIC ACCURACY OF SMART GADGETS/WEREABLE DEVICES IN ATRIAL FIBRILLATION DETECTION: A METANALYSIS

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. Hypothesis We performed a systemic review and meta-analysis to assess the accuracy of AF diagnosis by smart gadgets/wearable devices. Methods We systematically searched Medline, Embase and Cochrane electronic databases up to April 15th, 2022 for observational studies of the diagnostic accuracy of smartphone application, wrist-worn wearables and external devices in detecting AF. 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 79 studies were included enrolling 36903 patients, 66.3% male with average age of 68.3±8 years. In the overall analysis of all devices, the AUC was 0.99 (95% CI: 0.98-1.00), the sensitivity 95%(95% CI: 94–96%), the specificity 96%(95% CI: 96–97%). Wrist-worn wearables had AUC of 0.99 (95% CI: 0.98-1.00), the sensitivity 95%(9% CI: 92–97%), the specificity 97%(95% CI: 96–98%)(Figure 1A). Smartphone applications had AUC of 0.98 (95% CI: 0.96-0.99), the sensitivity 96%(9% CI: 94–97%), the specificity 96%(95% CI: 93–98%)(Figure 1B). External devices had AUC of 0.99 (95% CI: 0.98-1.00), the sensitivity 95%(9% CI: 93–97%), the specificity 96%(95% CI: 95–97%)(Figure 1C). Single-lead ECG had AUC of 0.99 (95% CI: 0.98- 1.00), the sensitivity 95%(9% CI: 92–96%), the specificity 96%(95% CI: 95–97%). PPG had AUC of 0.99 (95% CI: 0.98-1.00), the sensitivity 96%(9% CI: 95–97%), the specificity 97%(95% CI: 95–98%). Conclusions Smartphone application, wrist-worn devices and external devices with PPG and single-lead ECG have excellent diagnostic accuracy in atrial fibrillation diagnosis. Figure 1. Summary Receiver Operating Characteristic curves and Areas Under The Curve of Wrist-worn wearables (A), Smartphone applications (B) and External devices (C).