Review of mobile applications for the detection and management of atrial fibrillation.
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ABSTRACT: Background
Free mobile applications (apps) that use photoplethysmography (PPG) waveforms may extend atrial fibrillation (AF) detection to underserved populations, but they have not been rigorously evaluated.Objective
The purpose of this study was to systematically review and evaluate the quality, functionality, and adherence to self-management behaviors of existing mobile apps for AF.Methods
We systematically searched 3 app stores for apps that were free, available in English, and intended for use by patients to detect and manage AF. A minimum of 2 reviewers evaluated (1) app quality, using the Mobile Application Rating Scale (MARS); (2) functionality using published criteria; and (3) features that support 4 self-management behaviors (including PPG waveform monitoring) identified using evidence-based guidelines. Interrater reliability between the reviewers was calculated.Results
Of 12 included apps, 5 (42%) scored above average for quality (MARS score ≥3.0). App quality was highest for their ease of use, navigation, layout, and visual appeal (eg, functionality and aesthetics) and lowest for their behavioral change support and subjective impressions of quality. The most common app functionalities were capturing and graphically displaying user-entered data (n = 9 [75%]). Nearly all apps (n = 11 [92%]) supported PPG waveform monitoring, but only 2 (17%) supported all 4 self-management behaviors. Interrater reliability was high (0.75-0.83).Conclusion
The reviewed apps had wide variability in quality, functionality, and adherence to self-management behaviors. Given the accessibility of these apps to underserved populations and the tremendous potential they hold for improving AF detection and management, high priority should be given to improving app quality and functionality.
SUBMITTER: Turchioe MR
PROVIDER: S-EPMC7351352 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:AimsAtrial fibrillation (AF) is the most common sustained arrhythmia and an important risk factor for stroke and heart failure. We aimed to conduct a systematic review of the literature and summarize the performance of mobile health (mHealth) devices in diagnosing and screening for AF.Methods and resultsWe conducted a systematic search of MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials. Forty-three studies met the inclusion criteria and were divided into two groups: 28 studies aimed at validating smart devices for AF diagnosis, and 15 studies used smart devices to screen for AF. Evaluated technologies included smartphones, with photoplethysmographic (PPG) pulse waveform measurement or accelerometer sensors, smartbands, external electrodes that can provide a smartphone single-lead electrocardiogram (iECG), such as AliveCor, Zenicor and MyDiagnostick, and earlobe monitor. The accuracy of these devices depended on the technology and the population, AliveCor and smartphone PPG sensors being the most frequent systems analysed. The iECG provided by AliveCor demonstrated a sensitivity and specificity between 66.7% and 98.5% and 99.4% and 99.0%, respectively. The PPG sensors detected AF with a sensitivity of 85.0-100% and a specificity of 93.5-99.0%. The incidence of newly diagnosed arrhythmia ranged from 0.12% in a healthy population to 8% among hospitalized patients.ConclusionAlthough the evidence for clinical effectiveness is limited, these devices may be useful in detecting AF. While mHealth is growing in popularity, its clinical, economic, and policy implications merit further investigation. More head-to-head comparisons between mHealth and medical devices are needed to establish their comparative effectiveness.
| S-EPMC7842109 | biostudies-literature
Project description:AimWe 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.MethodsThis 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.ResultsWe 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.ConclusionWhile 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. Mobile health solutions for atrial fibrillation detection and management: a systematic review.
| S-EPMC8454991 | biostudies-literature
Project description:Atrial fibrillation (AF) affects over 1.4 million people in the UK, resulting in a five-fold increased stroke risk and a three to four times greater risk of severe, disabling stroke. Atrial fibrillation, a chronic disease, requires monitoring, medication, and lifestyle measures. A self-management approach supported by mobile health (mHealth) may empower AF self-care. To assess the need to develop new mHealth self-management interventions for those with AF this review aimed to identify commercially available AF self-management apps, analyse, and synthesize (i) characteristics, (ii) functions, (iii) privacy/security, (iv) incorporated behaviour change techniques (BCTs), and (v) quality and usability. We searched app stores for 'atrial fibrillation' and 'anticoagulation', and included apps focused on AF self-management in the review. We examined app functions, privacy statements against best practice recommendations, the inclusion of BCTs using the App Behaviour Change Scale, and app quality/usability using the Mobile App Rating Scale. From an initial search of 555 apps, five apps were included in the review. Common functions were educational content, medication trackers, and communication with healthcare professionals. Apps contained limited BCTs, lacked intuitive functions and were difficult to use. Privacy policies were difficult to read. App quality rated from poor to acceptable and no app had been evaluated in a clinical trial. The review reports a lack of commercially available AF self-management apps of sufficient standard for use in healthcare settings. This highlights the need for clinically validated mHealth interventions incorporating evidence-based BCTs to support AF self-management.
| S-EPMC8210674 | biostudies-literature
Project description: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.
| S-EPMC8116993 | biostudies-literature
Project description:BACKGROUND:Mobile health applications may improve patient education and self-care for a complex condition such as atrial fibrillation (AF). Little is known about the accessibility of mobile health applications ("apps") and their readability. We evaluated the readability and quality of available apps for AF. METHODS:We searched the Apple and Google Play app stores with the terms "atrial fibrillation" and "afib." We downloaded English-language apps (up to n?=?100 for each term) and categorized them by name, App store, cost, content, uploading agency (heath care associated [HCA] versus non-HCA), target audience (health care professional [HCP] versus non-HCP), scientific validity (i.e., citation of peer-reviewed or validated medical information), and user ratings. We analyzed the text of apps intended for a non-HCP target audience for readability with 10 established measures. RESULTS:Of the 206 downloaded apps, 50.5% were excluded as unrelated to AF, inaccessible, or non-English language. The majority of apps contained information about AF (63.2% Apple, 52.2% Google Play) and AF detection (52.6% Apple, 56.5% Google Play). A minority of non-HCP apps contained scientifically validated content (Apple, 15.8%; Google Play, 13.0%; P?=?NS). App mean readability was grade 12.1?±?2.6. CONCLUSIONS:Most AF apps lacked scientific validation and were written at excessively high reading-grade levels. Our results suggest caution with mobile health apps, particularly for users with limited health literacy. There is potential opportunity for a multi-disciplinary effort by regulatory agencies, healthcare organizations, and app stores to improve relevance, scientific validity, and readability of AF apps for patients with this complex and morbid disease.
| S-EPMC6710110 | biostudies-literature
Project description:Catheter-based ablation techniques have a well-established role in atrial fibrillation (AF) management. The prevalence and impact of AF is increasing globally, thus mandating an emphasis on improving ablation techniques through innovation. One key area of ongoing evolution in this field is the use of laser energy to perform pulmonary vein isolation during AF catheter ablation. While laser use is not as widespread as other ablation techniques, such as radiofrequency ablation and cryoballoon ablation, advancements in product design and procedural protocols have demonstrated laser balloon ablation to be equally safe and effective compared to these other modalities. Additionally, strategies to improve procedural efficiency and decrease radiation exposure through low fluoroscopy protocols make this technology an increasingly promising and exciting option.
| S-EPMC7917803 | biostudies-literature
Project description:BACKGROUND:Patients with diabetes lack information on which commercially available applications (apps) improve diabetes-related outcomes. We conducted a rapid evidence review to examine features, clinical efficacy, and usability of apps for self-management of type 1 and type 2 diabetes in adults. METHODS:Ovid/Medline and the Cochrane Database of Systematic Reviews were searched for systematic reviews and technology assessments. Reference lists of relevant systematic reviews were examined for primary studies. Additional searches for primary studies were conducted online, through Ovid/Medline, Embase, CINAHL, and ClinicalTrials.gov . Studies were evaluated for eligibility based on predetermined criteria, data were extracted, study quality was assessed using a risk of bias tool, information on app features was collected, and app usability was assessed. Results are summarized qualitatively. RESULTS:Fifteen articles evaluating 11 apps were identified: six apps for type 1 and five apps for type 2 diabetes. Common features of apps included setting reminders and tracking blood glucose and hemoglobin A1c (HbA1c), medication use, physical activity, and weight. Compared with controls, use of eight apps, when paired with support from a healthcare provider or study staff, improved at least one outcome, most often HbA1c. Patients did not experience improvements in quality of life, blood pressure, or weight, regardless of app used or type of diabetes. Study quality was variable. Of the eight apps available for usability testing, two were scored "acceptable," three were "marginal," and three were "not acceptable." DISCUSSION:Limited evidence suggests that use of some commercially available apps, when combined with additional support from a healthcare provider or study staff, may improve some short-term diabetes-related outcomes. The impact of these apps on longer-term outcomes is unclear. More rigorous and longer-term studies of apps are needed. REGISTRATION:This review was funded by the Agency for Healthcare Research and Quality (AHRQ). The protocol is available at: http://www.effectivehealthcare.ahrq.gov/topics/diabetes-mobile-devices/research-protocol .
| S-EPMC6025680 | biostudies-literature
Project description:The prevalence and economic burden of atrial fibrillation (AF) are predicted to more than double over the next few decades. In addition to anticoagulation and treatment of concomitant cardiovascular conditions, early and standardized rhythm control therapy reduces cardiovascular outcomes as compared with a rate control approach, favouring the restoration, and maintenance of sinus rhythm safely. Current therapies for rhythm control of AF include antiarrhythmic drugs (AADs) and catheter ablation (CA). However, response in an individual patient is highly variable with some remaining free of AF for long periods on antiarrhythmic therapy, while others require repeat AF ablation within weeks. The limited success of rhythm control therapy for AF is in part related to incomplete understanding of the pathophysiological mechanisms and our inability to predict responses in individual patients. Thus, a major knowledge gap is predicting which patients with AF are likely to respond to rhythm control approach. Over the last decade, tremendous progress has been made in defining the genetic architecture of AF with the identification of rare mutations in cardiac ion channels, signalling molecules, and myocardial structural proteins associated with familial (early-onset) AF. Conversely, genome-wide association studies have identified common variants at over 100 genetic loci and the development of polygenic risk scores has identified high-risk individuals. Although retrospective studies suggest that response to AADs and CA is modulated in part by common genetic variation, the development of a comprehensive clinical and genetic risk score may enable the translation of genetic data to the bedside care of AF patients. Given the economic impact of the AF epidemic, even small changes in therapeutic efficacy may lead to substantial improvements for patients and health care systems.
| S-EPMC8208749 | biostudies-literature
Project description:Atrial fibrillation (AF) is the most common arrhythmia encountered in clinical practice, and its paroxysmal nature makes its detection challenging. In this trial, we evaluated a novel App for its accuracy to differentiate between patients in AF and patients in sinus rhythm (SR) using the plethysmographic sensor of an iPhone 4S and the integrated LED only.For signal acquisition, we used an iPhone 4S, positioned with the camera lens and LED light on the index fingertip. A 5 min video file was recorded with the pulse wave extracted from the green light spectrum of the signal. RR intervals were automatically identified. For discrimination between AF and SR, we tested three different statistical methods. Normalized root mean square of successive difference of RR intervals (nRMSSD), Shannon entropy (ShE), and SD1/SD2 index extracted from a Poincaré plot. Eighty patients were included in the study (40 patients in AF and 40 patients in SR at the time of examination). For discrimination between AF and SR, ShE yielded the highest sensitivity and specificity with 85 and 95%, respectively. Applying a tachogram filter resulted in an improved sensitivity of 87.5%, when combining ShE and nRMSSD, while specificity remained stable at 95%. A combination of SD1/SD2 index and nRMSSD led to further improvement and resulted in a sensitivity and specificity of 95%.The algorithm tested reliably discriminated between SR and AF based on pulse wave signals from a smartphone camera only. Implementation of this algorithm into a smartwatch is the next logical step.
| S-EPMC5437701 | biostudies-literature
Project description:BackgroundFoodborne disease outbreaks are common and notifiable in South Africa; however, they are rarely reported and poorly investigated. Surveillance data from the notification system is suboptimal and limited, and does not provide adequate information to guide public health action and inform policy. We performed a systematic review of published literature to identify mobile application-based outbreak response systems for managing foodborne disease outbreaks and to determine the elements that the system requires to generate foodborne disease data needed for public action.MethodsStudies were identified through literature searches using online databases on PubMed/Medline, CINAHL, Academic Search Complete, Greenfile, Library, Information Science & Technology. Search was limited to studies published in English during the period January 1990 to November 2020. Search strategy included various terms in varying combinations with Boolean phrases "OR" and "AND". Data were collected following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Statement. A standardised data collection tool was used to extract and summarise information from identified studies. We assessed qualities of mobile applications by looking at the operating system, system type, basic features and functionalities they offer for foodborne disease outbreak management.ResultsFive hundred and twenty-eight (528) publications were identified, of which 48 were duplicates. Of the remaining 480 studies, 2.9% (14/480) were assessed for eligibility. Only one of the 14 studies met the inclusion criteria and reported on one mobile health application named MyMAFI (My Mobile Apps for Field Investigation). There was lack of detailed information on the application characteristics. However, based on minimal information available, MyMAFI demonstrated the ability to generate line lists, reports and offered functionalities for outbreak verification and epidemiological investigation. Availability of other key components such as environmental and laboratory investigations were unknown.ConclusionsThere is limited use of mobile applications on management of foodborne disease outbreaks. Efforts should be made to set up systems and develop applications that can improve data collection and quality of foodborne disease outbreak investigations.
| S-EPMC8653522 | biostudies-literature