Background:

A significant morbidity, mortality and financial burden is associated with cardiac rhythm abnormalities. Atrial fibrillation (AF) is the most common type of cardiac arrhythmia. Conventional screening tools are often unsuccessful at detecting AF due to its episodic nature. Smartwatches have gained popularity in recent years as a health screening tool.

Objective:

The aim of our study was to systematically review and meta-analyse the diagnostic accuracy of smartwatches in the detection of cardiac arrhythmias.

Methods:

A comprehensive literature search was undertaken using the databases of EMBASE, Medline and the Cochrane Library. PRISMA guidance was followed. Studies reporting use of a smartwatch for detection of cardiac arrythmia were included. Independent proportion and their differences were calculated and pooled through DerSimonian and Laird random-effects modelling. Quality was assessed using the QUADAS-2 tool.

Results:

A total of 18 studies were analysed, measuring diagnostic accuracy in 424, 371 subjects in total. The overall sensitivity, specificity and accuracy of smartwatches to detect cardiac arrhythmias was 100% (95% CI 0.99-1.00), 95% (95% CI 0.93-0.97) and 97% (95% CI 0.96-0.99), respectively. The pooled PPV and NPV for detecting cardiac arrythmias was 85% 85% (95% CI 0.79-0.90) and 100% (95% CI 1.0-1.0), respectively.

Conclusions:

This review demonstrates the evolving field of digital disease screening and the increased role of machine learning in healthcare. The current diagnostic accuracy of smartwatch technology for detection of cardiac arrhythmias is high. Whilst the innovative drive of digital devices in healthcare screening will continue to gain momentum, the process of accurate evidence accrual and regulatory standards ready to accept their introduction is strongly needed. Clinical Trial: PROSPERO registration number: CRD42020213237