scholarly journals Mobile health solutions for atrial fibrillation detection and management: a systematic review

Author(s):  
Astrid N. L. Hermans ◽  
Monika Gawalko ◽  
Lisa Dohmen ◽  
Rachel M. J. van der Velden ◽  
Konstanze Betz ◽  
...  

Abstract Aim We aimed to systematically review the available literature on mobile Health (mHealth) solutions, including handheld and wearable devices, implantable loop recorders (ILRs), as well as mobile platforms and support systems in atrial fibrillation (AF) detection and management. Methods This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. The electronic databases PubMed (NCBI), Embase (Ovid), and Cochrane were searched for articles published until 10 February 2021, inclusive. Given that the included studies varied widely in their design, interventions, comparators, and outcomes, no synthesis was undertaken, and we undertook a narrative review. Results We found 208 studies, which were deemed potentially relevant. Of these studies included, 82, 46, and 49 studies aimed at validating handheld devices, wearables, and ILRs for AF detection and/or management, respectively, while 34 studies assessed mobile platforms/support systems. The diagnostic accuracy of mHealth solutions differs with respect to the type (handheld devices vs wearables vs ILRs) and technology used (electrocardiography vs photoplethysmography), as well as application setting (intermittent vs continuous, spot vs longitudinal assessment), and study population. Conclusion While the use of mHealth solutions in the detection and management of AF is becoming increasingly popular, its clinical implications merit further investigation and several barriers to widespread mHealth adaption in healthcare systems need to be overcome. Graphic abstract Mobile health solutions for atrial fibrillation detection and management: a systematic review.

2016 ◽  
Vol 12 (1) ◽  
pp. 33-45 ◽  
Author(s):  
Eleni Korompoki ◽  
Angela Del Giudice ◽  
Steffi Hillmann ◽  
Uwe Malzahn ◽  
David J Gladstone ◽  
...  

Background and purpose The detection rate of atrial fibrillation has not been studied specifically in transient ischemic attack (TIA) patients although extrapolation from ischemic stroke may be inadequate. We conducted a systematic review and meta-analysis to determine the rate of newly diagnosed atrial fibrillation using different methods of ECG monitoring in TIA. Methods A comprehensive literature search was performed following a pre-specified protocol the PRISMA statement. Prospective observational studies and randomized controlled trials were considered that included TIA patients who underwent cardiac monitoring for >12 h. Primary outcome was frequency of detection of atrial fibrillation ≥30 s. Analyses of subgroups and of duration and type of monitoring were performed. Results Seventeen studies enrolling 1163 patients were included. The pooled atrial fibrillation detection rate for all methods was 4% (95% CI: 2–7%). Yield of monitoring was higher in selected (higher age, more extensive testing for arrhythmias before enrolment, or presumed cardioembolic/cryptogenic cause) than in unselected cohorts (7% vs 3%). Pooled mean atrial fibrillation detection rates rose with duration of monitoring: 4% (24 h), 5% (24 h to 7 days) and 6% (>7 days), respectively. Yield of non-invasive was significantly lower than that of invasive monitoring (4% vs. 11%). Significant heterogeneity was observed among studies (I2=60.61%). Conclusion This first meta-analysis of atrial fibrillation detection in TIA patients finds a lower atrial fibrillation detection rate in TIA than reported for IS and TIA cohorts in previous meta-analyses. Prospective studies are needed to determine actual prevalence of atrial fibrillation and optimal diagnostic procedure for atrial fibrillation detection in TIA.


10.2196/26161 ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. e26161
Author(s):  
Tom E Biersteker ◽  
Martin J Schalij ◽  
Roderick W Treskes

Background Atrial 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. Objective The 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. Methods Two 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. Results A 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. Conclusions Although 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.


2020 ◽  
Vol 13 (1) ◽  
Author(s):  
Natalie V. S. Vinkeles Melchers ◽  
Luc E. Coffeng ◽  
Sake J. de Vlas ◽  
Wilma A. Stolk

Abstract Background Lymphatic filariasis (LF) infection is generally diagnosed through parasitological identification of microfilariae (mf) in the blood. Although historically the most commonly used technique for counting mf is the thick blood smear based on 20 µl blood (TBS20), various other techniques and blood volumes have been applied. It is therefore a challenge to compare mf prevalence estimates from different LF-survey data. Our objective was to standardise microfilaraemia (mf) prevalence estimates to TBS20 as the reference diagnostic technique. Methods We first performed a systematic review to identify studies reporting on comparative mf prevalence data as measured by more than one diagnostic test, including TBS20, on the same study population. Associations between mf prevalences based on different diagnostic techniques were quantified in terms of odds ratios (OR, with TBS20 blood as reference), using a meta-regression model. Results We identified 606 articles matching our search strategy and included 14 in our analyses. The OR of the mf prevalences as measured by the more sensitive counting chamber technique (≥ 50 µl blood) was 2.90 (95% confidence interval (CI): 1.60–5.28). For membrane filtration (1 ml blood) the OR was 2.39 (95% CI: 1.62–3.53), Knott’s technique it was 1.54 (95% CI: 0.72–3.29), and for TBS in ≥ 40 µl blood it was 1.37 (95% CI: 0.81–2.30). Conclusions We provided transformation factors to standardise mf prevalence estimates as detected by different diagnostic techniques to mf prevalence estimates as measured by TBS20. This will facilitate the use and comparison of more datasets in meta-analyses and geographic mapping initiatives across countries and over time.


10.2196/19099 ◽  
2020 ◽  
Vol 3 (2) ◽  
pp. e19099
Author(s):  
Ben Patel ◽  
Arron Thind

Background Mobile health (mHealth) apps are increasingly used postoperatively to monitor, educate, and rehabilitate. The usability of mHealth apps is critical to their implementation. Objective This systematic review evaluates the (1) methodology of usability analyses, (2) domains of usability being assessed, and (3) results of usability analyses. Methods The A Measurement Tool to Assess Systematic Reviews checklist was consulted. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guideline was adhered to. Screening was undertaken by 2 independent reviewers. All included studies were assessed for risk of bias. Domains of usability were compared with the gold-standard mHealth App Usability Questionnaire (MAUQ). Results A total of 33 of 720 identified studies were included for data extraction. Of the 5 included randomized controlled trials (RCTs), usability was never the primary end point. Methodology of usability analyses included interview (10/33), self-created questionnaire (18/33), and validated questionnaire (9/33). Of the 3 domains of usability proposed in the MAUQ, satisfaction was assessed in 28 of the 33 studies, system information arrangement was assessed in 11 of the 33 studies, and usefulness was assessed in 18 of the 33 studies. Usability of mHealth apps was above industry average, with median System Usability Scale scores ranging from 76 to 95 out of 100. Conclusions Current analyses of mHealth app usability are substandard. RCTs are rare, and validated questionnaires are infrequently consulted. Of the 3 domains of usability, only satisfaction is regularly assessed. There is significant bias throughout the literature, particularly with regards to conflicts of interest. Future studies should adhere to the MAUQ to assess usability and improve the utility of mHealth apps.


2020 ◽  
Author(s):  
Ben Patel ◽  
Arron Thind

BACKGROUND Mobile health (mHealth) apps are increasingly used postoperatively to monitor, educate, and rehabilitate. The usability of mHealth apps is critical to their implementation. OBJECTIVE This systematic review evaluates the (1) methodology of usability analyses, (2) domains of usability being assessed, and (3) results of usability analyses. METHODS The A Measurement Tool to Assess Systematic Reviews checklist was consulted. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guideline was adhered to. Screening was undertaken by 2 independent reviewers. All included studies were assessed for risk of bias. Domains of usability were compared with the gold-standard mHealth App Usability Questionnaire (MAUQ). RESULTS A total of 33 of 720 identified studies were included for data extraction. Of the 5 included randomized controlled trials (RCTs), usability was never the primary end point. Methodology of usability analyses included interview (10/33), self-created questionnaire (18/33), and validated questionnaire (9/33). Of the 3 domains of usability proposed in the MAUQ, satisfaction was assessed in 28 of the 33 studies, system information arrangement was assessed in 11 of the 33 studies, and usefulness was assessed in 18 of the 33 studies. Usability of mHealth apps was above industry average, with median System Usability Scale scores ranging from 76 to 95 out of 100. CONCLUSIONS Current analyses of mHealth app usability are substandard. RCTs are rare, and validated questionnaires are infrequently consulted. Of the 3 domains of usability, only satisfaction is regularly assessed. There is significant bias throughout the literature, particularly with regards to conflicts of interest. Future studies should adhere to the MAUQ to assess usability and improve the utility of mHealth apps.


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