Abstract

BackgroundAtrial fibrillation (AF) is the most common arrhythmia, and its prevalence is increasing. Early diagnosis is important to reduce the risk of stroke. Mobile health (mHealth) devices, such as single-lead electrocardiogram (ECG) devices, have been introduced to the worldwide consumer market over the past decade. Recent studies have assessed the usability of these devices for detection of AF, but it remains unclear if the use of mHealth devices leads to a higher AF detection rate.ObjectiveThe goal of the research was to conduct a systematic review of the diagnostic detection rate of AF by mHealth devices compared with traditional outpatient follow-up. Study participants were aged 16 years or older and had an increased risk for an arrhythmia and an indication for ECG follow-up—for instance, after catheter ablation or presentation to the emergency department with palpitations or (near) syncope. The intervention was the use of an mHealth device, defined as a novel device for the diagnosis of rhythm disturbances, either a handheld electronic device or a patch-like device worn on the patient’s chest. Control was standard (traditional) outpatient care, defined as follow-up via general practitioner or regular outpatient clinic visits with a standard 12-lead ECG or Holter monitoring. The main outcome measures were the odds ratio (OR) of AF detection rates.MethodsTwo reviewers screened the search results, extracted data, and performed a risk of bias assessment. A heterogeneity analysis was performed, forest plot made to summarize the results of the individual studies, and albatross plot made to allow the P values to be interpreted in the context of the study sample size.ResultsA total of 3384 articles were identified after a database search, and 14 studies with a 4617 study participants were selected. All studies but one showed a higher AF detection rate in the mHealth group compared with the control group (OR 1.00-35.71), with all RCTs showing statistically significant increases of AF detection (OR 1.54-19.16). Statistical heterogeneity between studies was considerable, with a Q of 34.1 and an I2 of 61.9, and therefore it was decided to not pool the results into a meta-analysis.ConclusionsAlthough the results of 13 of 14 studies support the effectiveness of mHealth interventions compared with standard care, study results could not be pooled due to considerable clinical and statistical heterogeneity. However, smartphone-connectable ECG devices provide patients with the ability to document a rhythm disturbance more easily than with standard care, which may increase empowerment and engagement with regard to their illness. Clinicians must beware of overdiagnosis of AF, as it is not yet clear when an mHealth-detected episode of AF must be deemed significant.

Highlights

  • Atrial fibrillation (AF) is the most commonly diagnosed arrhythmia [1]

  • All studies but one showed a higher AF detection rate in the Mobile health (mHealth) group compared with the control group, with all randomized controlled trials (RCTs) showing statistically significant increases of AF detection

  • Conclusions: the results of 13 of 14 studies support the effectiveness of mHealth interventions compared with standard care, study results could not be pooled due to considerable clinical and statistical heterogeneity

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Summary

Introduction

Atrial fibrillation (AF) is the most commonly diagnosed arrhythmia [1]. It may be paroxysmal (present for 30 seconds to 7 days), persistent (present for more than 7 days), or permanent [2]. The worldwide prevalence of AF is increasing. A European study has shown that the number of patients with diagnosed AF is expected to increase from a prevalence of 2.3% in 2010 to 3.5% to 4.3% in 2050 [6]. Compared with patients with sinus rhythm, those with AF are found to have a 2.4-fold risk of stroke, and the risk of ischemic heart disease and development of chronic kidney disease are both increased 1.6-fold [8]. Atrial fibrillation (AF) is the most common arrhythmia, and its prevalence is increasing. Recent studies have assessed the usability of these devices for detection of AF, but it remains unclear if the use of mHealth devices leads to a higher AF detection rate

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