Smartphone-based atrial fibrillation screening in the general population: feasibility and impact on medical treatment

Author:

Gruwez Henri123ORCID,Verbrugge Frederik H145,Proesmans Tine6,Evens Stijn6,Vanacker Peter78,Rutgers Matthieu Pierre9,Vanhooren Geert10,Bertrand Philippe13,Pison Laurent13ORCID,Haemers Peter2ORCID,Vandervoort Pieter13,Nuyens Dieter3

Affiliation:

1. Biomedical Research Institute, Faculty of Medicine and Life Sciences, Hasselt University , Hasselt , Belgium

2. Department of Cardiovascular Sciences, Catholic University Leuven , Leuven , Belgium

3. Department of Cardiology, Hospital East-Limburg , Genk , Belgium

4. Centre for Cardiovascular Diseases, University Hospital Brussels , Jette , Belgium

5. Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel , Brussels , Belgium

6. Qompium NV , Hasselt , Belgium

7. Department of Neurology, Antwerp University Hospital and Antwerp University , Antwerp , Belgium

8. Department of Neurology, Groeninge Hospital , Kortrijk , Belgium

9. Department of Neurology, Clinique de l’Europe , Brussels , Belgium

10. Department of Neurology, Sint-Jan Hospital Brugge-Oostende , Bruges , Belgium

Abstract

Abstract Aims The aim of this study is to determine the feasibility, detection rate, and therapeutic implications of large-scale smartphone-based screening for atrial fibrillation (AF). Methods and results Subjects from the general population in Belgium were recruited through a media campaign to perform AF screening during 8 consecutive days with a smartphone application. The application analyses photoplethysmography traces with artificial intelligence and offline validation of suspected signals to detect AF. The impact of AF screening on medical therapy was measured through questionnaires. Atrial fibrillation was detected in the screened population (n = 60.629) in 791 subjects (1.3%). From this group, 55% responded to the questionnaire. Clinical AF [AF confirmed on a surface electrocardiogram (ECG)] was newly diagnosed in 60 individuals and triggered the initiation of anti-thrombotic therapy in 45%, adjustment of rate or rhythm controlling strategies in 62%, and risk factor management in 17%. In subjects diagnosed with known AF before screening, a positive screening result led to these therapy adjustments in 9%, 39%, and 11%, respectively. In all subjects with clinical AF and an indication for oral anti-coagulation (OAC), OAC uptake increased from 56% to 74% with AF screening. Subjects with clinical AF were older with more co-morbidities compared with subclinical AF (no surface ECG confirmation of AF) (P < 0.001). In subjects with subclinical AF (n = 202), therapy adjustments were performed in only 7%. Conclusion Smartphone–based AF screening is feasible at large scale. Screening increased OAC uptake and impacted therapy of both new and previously diagnosed clinical AF but failed to impact risk factor management in subjects with subclinical AF.

Publisher

Oxford University Press (OUP)

Subject

Energy Engineering and Power Technology,Fuel Technology

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