Evidence map›Paper›PMID 34104466›Full record

ArticleDigital health

Distinguishing atrial fibrillation from sinus rhythm using commercial pulse detection systems: The non-interventional BAYathlon study.

Christian Müller, Ulf Hengstmann, Michael Fuchs, Martin Kirchner, Frank Kleinjung, Harald Mathis, Stephan Martin, Ingo Bläse, Stefan Perings

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02875106 (BAYathlon - a Digital Non-interventional AF Screening Study to Identify Commercial Pulse Detection Systems), which is not on this map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
4.1field-weighted citation impact, top 5% 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.

NCT02875106 completednot on this map

BAYathlon - a Digital Non-interventional AF Screening Study to Identify Commercial Pulse Detection Systems (CPDS) Detecting AF and Sinus Rhythm Parallel to ECG Recording Within Routine Clinical Setting

TypeobservationalSponsorBayerRan2017 to 2019Enrolled165ConditionsAtrial FibrillationArms12-point-ECG, Polar V800, 360° eMotion FAROS SET + Belt, Adidas Micoach smart run, TomTom Runner Cardio HRM
3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 26 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
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

9 authors at 4 institutions in 1 country.

Christian MüllerBayer Vital GmbH, Leverkusen, Germany.ORCID https://orcid.org/0000-0002-3722-7685
Ulf HengstmannBayer AG, Leverkusen, Germany.
Michael FuchsFraunhofer-Institut für Angewandte Informationstechnik FIT, Sankt Augustin, Germany.
Martin KirchnerBayer Vital GmbH, Leverkusen, Germany.
Frank KleinjungBayer AG, Berlin, Germany.
Harald MathisFraunhofer-Institut für Angewandte Informationstechnik FIT, Sankt Augustin, Germany.
Stephan MartinVerbund Katholischer Kliniken Düsseldorf, Düsseldorf, Germany.
Ingo BläseCardio Centrum Düsseldorf, Düsseldorf, Germany.
Stefan PeringsCardio Centrum Düsseldorf, Düsseldorf, Germany.
Bayer (Germany) · DEFraunhofer Institute for Applied Information Technology · DEHeinrich Heine University Düsseldorf · DEVerbund Katholischer Kliniken Düsseldorf · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveEarly diagnosis of atrial fibrillation (AFib) is a priority for stroke prevention. We sought to test four commercial pulse detection systems (CPDSs) for ability to distinguish AFib from normal sinus rhythm using a published algorithm (Zhou et al., PLoS One 2015;10:e0136544), compared with visual diagnosis by electrocardiogram inspection.

methodsBAYathlon was a prospective, non-interventional, single-centre study. Adult cardiology patients with documented AFib or sinus rhythm who were due to have a routine 5-min electrocardiogram were randomized to undergo a parallel 5-min pulse assessment with a Polar V800, eMotion Faros 360, TomTom heart rate monitor, or Adidas miCoach Smart Run.

results144 patients (73 with AFib, 71 with sinus rhythm (based on electrocardiograms); median age: 73 years; 53.5% male) were analysed. Algorithm sensitivities (primary endpoint) and specificities for AFib when applied to CPDS recordings were 93.3% and 94.1% with the Polar V800, 90.0% and 84.2% with the eMotion Faros 360, and 0% and 100% with the other CPDSs (analysis period: 127 heart rate signals + 2 min). When applied to routine electrocardiograms, the algorithm correctly detected AFib in 71/73 patients. Different analysis periods (127 heart rate signals +1 or 3 min) only slightly changed the sensitivities with the Polar V800 and eMotion Faros 360 and had no effect on the sensitivities with the other CPDSs.

conclusionAFib screening using the applied algorithm is feasible with the Polar V800 and eMotion Faros 360 (which provide RR interval data) but not with the other CPDSs (which provide pre-processed heart rate time series).ClinicalTrials.gov identifier: NCT02875106.

Indexed as

algorithmsAtrial fibrillationelectrocardiographyobservational studysensitivitysinus rhythm

Identifiers

PMID34104466
PMCPMC8145579
OpenAlexW3164125431

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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.