European Society of Cardiology smartphone and tablet applications for patients with atrial fibrillation and their health care providers

Kotecha, Dipak; Chua, Winnie; Fabritz, Larissa; Hendriks, Jeroen; Casadei, Barbara; Schotten, Ulrich; Vardas, Panos; Heidbüchel, Hein; Dean, Veronica; Kirchhof, Paulus

doi:10.1093/europace/eux299

Cited by 103 publications

(80 citation statements)

References 59 publications

(52 reference statements)

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“…eHealth can be used across all stages of the disease-management pathway, from screening and diagnosis, to decisionmaking around treatment selection, to ongoing therapeutic monitoring and management [380,381]. Furthermore, eHealth has enabled components of AF care to be offered in a wide range of practice settings, including community pharmacies, nurse-led clinics, and home-based services.…”

Section: Ehealth To Support Atrial Fibrillation Managementmentioning

confidence: 99%

National Heart Foundation of Australia and the Cardiac Society of Australia and New Zealand: Australian Clinical Guidelines for the Diagnosis and Management of Atrial Fibrillation 2018

Brieger

Amerena

Attia

et al. 2018

Heart, Lung and Circulation

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246

235

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Section: Ehealth To Support Atrial Fibrillation Managementmentioning

confidence: 99%

National Heart Foundation of Australia and the Cardiac Society of Australia and New Zealand: Australian Clinical Guidelines for the Diagnosis and Management of Atrial Fibrillation 2018

Brieger

Amerena

Attia

et al. 2018

Heart, Lung and Circulation

Self Cite

246

235

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“…From apps that collect smartphone sensor data that researcher can use to predict relapse in schizophrenia6 to others used to monitor heart conditions in real time,7 the potential of apps across healthcare is vast. However, the majority of apps featured in the research literature are often not available to the public 8.…”

Section: Introductionmentioning

confidence: 99%

Understanding the quality, effectiveness and attributes of top-rated smartphone health apps

Wisniewski

Liu

Henson

et al. 2019

Evid Based Mental Health

108

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ObjectiveThis study aimed to understand the attributes of popular apps for mental health and comorbid medical conditions, and how these qualities relate to consumer ratings, app quality and classification by the WHO health app classification framework.MethodsWe selected the 10 apps from the Apple iTunes store and the US Android Google Play store on 20 July 2018 from six disease states: depression, anxiety, schizophrenia, addiction, diabetes and hypertension. Each app was downloaded by two authors who provided information on the apps’ attributes, functionality, interventions, popularity, scientific backing and WHO app classification rating.ResultsA total of 120 apps were examined. Although none of these apps had Food and Drug Administration marketing approval, nearly 50% made claims that appeared medical. Most apps offered a similar type of services with 87.5% assigned WHO classification 1.4.2 ‘self-monitoring of health or diagnostic data by a client’ or 1.6.1 ‘client look-up of health information’. The ‘last updated’ attribute was highly correlated with a quality rating of the app although no apps features (eg, uses Global Positioning System, reminders and so on) were.ConclusionDue to the heterogeneity of the apps, we were unable to define a core set of features that would accurately assess app quality. The number of apps making unsupported claims combined with the number of apps offering questionable content warrants a cautious approach by both patients and clinicians in selecting safe and effective ones.Clinical Implications‘Days since last updated’ offers a useful and easy clinical screening test for health apps, regardless of the condition being examined.

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“…The workload of specialized clinics may be reduced if live remote patient monitoring was enabled by modern wearables. This could be a contributively brick for structured disease management applications [ 24 ].…”

Section: Discussionmentioning

confidence: 99%

Reliable Detection of Atrial Fibrillation with a Medical Wearable during Inpatient Conditions

Jacobsen

Dembek

Ziakos

et al. 2020

Sensors

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Atrial fibrillation (AF) is the most common arrhythmia and has a major impact on morbidity and mortality; however, detection of asymptomatic AF is challenging. This study sims to evaluate the sensitivity and specificity of non-invasive AF detection by a medical wearable. In this observational trial, patients with AF admitted to a hospital carried the wearable and an ECG Holter (control) in parallel over a period of 24 h, while not in a physically restricted condition. The wearable with a tight-fit upper armband employs a photoplethysmography technology to determine pulse rates and inter-beat intervals. Different algorithms (including a deep neural network) were applied to five-minute periods photoplethysmography datasets for the detection of AF. A total of 2306 h of parallel recording time could be obtained in 102 patients; 1781 h (77.2%) were automatically interpretable by an algorithm. Sensitivity to detect AF was 95.2% and specificity 92.5% (area under the receiver operating characteristics curve (AUC) 0.97). Usage of deep neural network improved the sensitivity of AF detection by 0.8% (96.0%) and specificity by 6.5% (99.0%) (AUC 0.98). Detection of AF by means of a wearable is feasible in hospitalized but physically active patients. Employing a deep neural network enables reliable and continuous monitoring of AF.

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European Society of Cardiology smartphone and tablet applications for patients with atrial fibrillation and their health care providers

Cited by 103 publications

References 59 publications

National Heart Foundation of Australia and the Cardiac Society of Australia and New Zealand: Australian Clinical Guidelines for the Diagnosis and Management of Atrial Fibrillation 2018

National Heart Foundation of Australia and the Cardiac Society of Australia and New Zealand: Australian Clinical Guidelines for the Diagnosis and Management of Atrial Fibrillation 2018

Understanding the quality, effectiveness and attributes of top-rated smartphone health apps

Reliable Detection of Atrial Fibrillation with a Medical Wearable during Inpatient Conditions

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