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Gill S, Bunting KV, Sartini C, Cardoso VR, Ghoreishi N, Uh HW, Williams JA, Suzart-Woischnik K, Banerjee A, Asselbergs FW, Eijkemans M, Gkoutos GV, Kotecha D. Smartphone detection of atrial fibrillation using photoplethysmography: a systematic review and meta-analysis. Heart 2022; 108:1600-1607. [PMID: 35277454 PMCID: PMC9554073 DOI: 10.1136/heartjnl-2021-320417] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/09/2021] [Accepted: 01/24/2022] [Indexed: 11/24/2022] Open
Abstract
OBJECTIVES Timely diagnosis of atrial fibrillation (AF) is essential to reduce complications from this increasingly common condition. We sought to assess the diagnostic accuracy of smartphone camera photoplethysmography (PPG) compared with conventional electrocardiogram (ECG) for AF detection. METHODS This is a systematic review of MEDLINE, EMBASE and Cochrane (1980-December 2020), including any study or abstract, where smartphone PPG was compared with a reference ECG (1, 3 or 12-lead). Random effects meta-analysis was performed to pool sensitivity/specificity and identify publication bias, with study quality assessed using the QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies-2) risk of bias tool. RESULTS 28 studies were included (10 full-text publications and 18 abstracts), providing 31 comparisons of smartphone PPG versus ECG for AF detection. 11 404 participants were included (2950 in AF), with most studies being small and based in secondary care. Sensitivity and specificity for AF detection were high, ranging from 81% to 100%, and from 85% to 100%, respectively. 20 comparisons from 17 studies were meta-analysed, including 6891 participants (2299 with AF); the pooled sensitivity was 94% (95% CI 92% to 95%) and specificity 97% (96%-98%), with substantial heterogeneity (p<0.01). Studies were of poor quality overall and none met all the QUADAS-2 criteria, with particular issues regarding selection bias and the potential for publication bias. CONCLUSION PPG provides a non-invasive, patient-led screening tool for AF. However, current evidence is limited to small, biased, low-quality studies with unrealistically high sensitivity and specificity. Further studies are needed, preferably independent from manufacturers, in order to advise clinicians on the true value of PPG technology for AF detection.
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Affiliation(s)
- Simrat Gill
- Institute of Cardiovascular Sciences, University of Birmingham, Birmingham, UK
- Health Data Research UK Midlands Site, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | - Karina V Bunting
- Institute of Cardiovascular Sciences, University of Birmingham, Birmingham, UK
- Health Data Research UK Midlands Site, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | - Claudio Sartini
- Medical Affairs and Pharmacovigilance, Pharmaceuticals, Integrated Evidence Generation, Bayer AG, Leverkusen, Nordrhein-Westfalen, Germany
| | - Victor Roth Cardoso
- Institute of Cardiovascular Sciences, University of Birmingham, Birmingham, UK
- Health Data Research UK Midlands Site, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
| | - Narges Ghoreishi
- Medical Affairs and Pharmacovigilance, Pharmaceuticals, Integrated Evidence Generation, Bayer AG, Leverkusen, Nordrhein-Westfalen, Germany
| | - Hae-Won Uh
- Julius Center for Health Sciences and Primary Care, University Medical Centre, Utrecht, Netherlands
| | - John A Williams
- Health Data Research UK Midlands Site, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
| | - Kiliana Suzart-Woischnik
- Medical Affairs and Pharmacovigilance, Pharmaceuticals, Integrated Evidence Generation, Bayer AG, Leverkusen, Nordrhein-Westfalen, Germany
| | - Amitava Banerjee
- Farr Institute of Health Informatics Research, University College London, London, UK
| | - Folkert W Asselbergs
- Department of Cardiology, University Medical Centre Utrecht Department of Cardiology, Utrecht, Netherlands
- Department of Cardiology, University College London Faculty of Population Health Sciences, London, UK
- Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, UK
| | - Mjc Eijkemans
- Julius Center for Health Sciences and Primary Care, University Medical Centre, Utrecht, Netherlands
| | - Georgios V Gkoutos
- Health Data Research UK Midlands Site, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
| | - Dipak Kotecha
- Institute of Cardiovascular Sciences, University of Birmingham, Birmingham, UK
- Health Data Research UK Midlands Site, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
- Department of Cardiology, University Medical Centre Utrecht Department of Cardiology, Utrecht, Netherlands
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