Evidence map›Paper›PMID 35277454›Full record

SynthesisHeart (British Cardiac Society)2022

Smartphone detection of atrial fibrillation using photoplethysmography: a systematic review and meta-analysis.

Simrat Gill, Karina V Bunting, Claudio Sartini, Victor Roth Cardoso, Narges Ghoreishi, Hae-Won Uh, John A Williams, Kiliana Suzart-Woischnik, Amitava Banerjee, Folkert W Asselbergs and 3 more

Open access · hybridAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Heart (British Cardiac Society), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 3 pooled it
7.2field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

30 citing papers in PubMed, 3 syntheses or guidelines pooled it, 47 citations in OpenAlex.

  1. Pooled it
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  12. State of the Art of Artificial Intelligence in Clinical Electrophysiology in 2025: A Scientific Statement of the European Heart Rhythm Association (EHRA) of the ESC, the Heart Rhythm Society (HRS), and the ESC Working Group on E-Cardiology.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2025
    Article
  13. Article
  14. External validation of a machine learning-based classification algorithm for ambulatory heart rhythm diagnostics in pericardioversion atrial fibrillation patients using smartphone photoplethysmography: the SMARTBEATS-ALGO study.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2025
    Article
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  17. Evolution in electrophysiology 100 years after Einthoven: translational and computational innovations in rhythm control of atrial fibrillation.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2024
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 4 institutions in 3 countries.

Simrat GillInstitute of Cardiovascular Sciences, University of Birmingham, Birmingham, UK s.gill.5@bham.ac.uk.ORCID 0000-0002-8302-2891
Karina V BuntingInstitute of Cardiovascular Sciences, University of Birmingham, Birmingham, UK.ORCID 0000-0003-4602-4377
Claudio SartiniMedical Affairs and Pharmacovigilance, Pharmaceuticals, Integrated Evidence Generation, Bayer AG, Leverkusen, Nordrhein-Westfalen, Germany.
Victor Roth CardosoInstitute of Cardiovascular Sciences, University of Birmingham, Birmingham, UK.
Narges GhoreishiMedical Affairs and Pharmacovigilance, Pharmaceuticals, Integrated Evidence Generation, Bayer AG, Leverkusen, Nordrhein-Westfalen, Germany.
Hae-Won UhJulius Center for Health Sciences and Primary Care, University Medical Centre, Utrecht, Netherlands.
John A WilliamsHealth Data Research UK Midlands Site, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
Kiliana Suzart-WoischnikMedical Affairs and Pharmacovigilance, Pharmaceuticals, Integrated Evidence Generation, Bayer AG, Leverkusen, Nordrhein-Westfalen, Germany.
Amitava BanerjeeFarr Institute of Health Informatics Research, University College London, London, UK.ORCID 0000-0001-8741-3411
Folkert W AsselbergsDepartment of Cardiology, University Medical Centre Utrecht Department of Cardiology, Utrecht, Netherlands.
Mjc EijkemansJulius Center for Health Sciences and Primary Care, University Medical Centre, Utrecht, Netherlands.
Georgios V GkoutosHealth Data Research UK Midlands Site, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
Dipak KotechaInstitute of Cardiovascular Sciences, University of Birmingham, Birmingham, UK.ORCID 0000-0002-2570-9812
University Hospitals Birmingham NHS Foundation Trust · GBBayer (Germany) · DEUniversity Medical Center Utrecht · NLFarr Institute · GB

Funding

British Heart Foundation AA/18/2/34218British Heart Foundation FS/CDRF/21/21032
6 · The paper itself

Abstract

objectivesTimely 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.

methodsThis 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.

results28 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.

conclusionPPG 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.

Indexed as

Atrial FibrillationPhotoplethysmographyElectrocardiographyHumansSensitivity and SpecificitySmartphoneatrial fibrillationphotoplethysmographysmartphone

Identifiers

PMID35277454
PMCPMC9554073
OpenAlexW4221110131

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.