Evidence map›Paper›PMID 35481559›Full record

ArticleJMIR formative research2022

Atrial Fibrillation Detection With an Analog Smartwatch: Prospective Clinical Study and Algorithm Validation.

David Campo, Valery Elie, Tristan de Gallard, Pierre Bartet, Tristan Morichau-Beauchant, Nicolas Genain, Antoine Fayol, David Fouassier, Adrien Pasteur-Rousseau, Etienne Puymirat and 1 more

Registry-linked trialAbstract read
In one paragraph

Article in JMIR formative research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04351386 (Validation Study of the Watch HWA09 and Its Softwares ECG-SW1 and PPG-SW1 for the Detection of Atrial Fibrillation), which is not on this map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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.

NCT04351386 completednot on this map

Validation Study of the Watch HWA09 and Its Softwares ECG-SW1 and PPG-SW1 for the Detection of Atrial Fibrillation

TypeobservationalSponsorWithingsRan2019 to 2021Enrolled283ConditionsAtrial Fibrillation, Arrythmia, CardiacArmsAF Detection
3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

11 authors.

David CampoWithings, Issy Les Moulineaux, France.ORCID https://orcid.org/0000-0001-8650-8953
Valery ElieWithings, Issy Les Moulineaux, France.ORCID https://orcid.org/0000-0002-8500-8516
Tristan de GallardWithings, Issy Les Moulineaux, France.ORCID https://orcid.org/0000-0002-1401-373X
Pierre BartetWithings, Issy Les Moulineaux, France.ORCID https://orcid.org/0000-0001-8449-5765
Tristan Morichau-BeauchantIntensive Care Unit, Centre Cardiologique du Nord, Sainte-Denis, France.ORCID https://orcid.org/0000-0001-9890-4590
Nicolas GenainWithings, Issy Les Moulineaux, France.ORCID https://orcid.org/0000-0003-4508-8424
Antoine FayolCardiology Intensive Care Unit, Hopital Europeen Georges Pompidou, Paris, France.ORCID https://orcid.org/0000-0003-4608-2649
David FouassierInstitut Coeur Paris Centre Turin, Paris, France.ORCID https://orcid.org/0000-0003-4247-491X
Adrien Pasteur-RousseauInstitut Coeur Paris Centre Floréal, Bagnolet, France.ORCID https://orcid.org/0000-0001-9216-2231
Etienne PuymiratCardiology Intensive Care Unit, Hopital Europeen Georges Pompidou, Paris, France.ORCID https://orcid.org/0000-0002-0533-9682
Julien NahumIntensive Care Unit, Centre Cardiologique du Nord, Sainte-Denis, France.ORCID https://orcid.org/0000-0002-1158-5513

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAtrial fibrillation affects approximately 4% of the world's population and is one of the major causes of stroke, heart failure, sudden death, and cardiovascular morbidity. It can be difficult to diagnose when asymptomatic or in the paroxysmal stage, and its natural history is not well understood. New wearables and connected devices offer an opportunity to improve on this situation.

objectiveWe aimed to validate an algorithm for the automatic detection of atrial fibrillation from a single-lead electrocardiogram taken with a smartwatch.

methodsEligible patients were recruited from 4 sites in Paris, France. Electrocardiograms (12-lead reference and single lead) were captured simultaneously. The electrocardiograms were reviewed by independent, blinded board-certified cardiologists. The sensitivity and specificity of the algorithm to detect atrial fibrillation and normal sinus rhythm were calculated. The quality of single-lead electrocardiograms (visibility and polarity of waves, interval durations, heart rate) was assessed in comparison with the gold standard (12-lead electrocardiogram).

resultsA total of 262 patients (atrial fibrillation: n=100, age: mean 74.3 years, SD 12.3; normal sinus rhythm: n=113, age: 61.8 years, SD 14.3; other arrhythmia: n=45, 66.9 years, SD 15.2; unreadable electrocardiograms: n=4) were included in the final analysis; 6.9% (18/262) were classified as Noise by the algorithm. Excluding other arrhythmias and Noise, the sensitivity for atrial fibrillation detection was 0.963 (95% CI lower bound 0.894), and the specificity was 1.000 (95% CI lower bound 0.967). Visibility and polarity accuracies were similar (1-lead electrocardiogram: P waves: 96.9%, QRS complexes: 99.2%, T waves: 91.2%; 12-lead electrocardiogram: P waves: 100%, QRS complexes: 98.8%, T waves: 99.5%). P-wave visibility accuracy was 99% (99/100) for patients with atrial fibrillation and 95.7% (155/162) for patients with normal sinus rhythm, other arrhythmias, and unreadable electrocardiograms. The absolute values of the mean differences in PR duration and QRS width were <3 ms, and more than 97% were <40 ms. The mean difference between the heart rates from the 1-lead electrocardiogram calculated by the algorithm and those calculated by cardiologists was 0.55 bpm.

conclusionsThe algorithm demonstrated great diagnostic performance for atrial fibrillation detection. The smartwatch's single-lead electrocardiogram also demonstrated good quality for physician use in daily routine care.

trial registrationClinicalTrials.gov NCT04351386; http://clinicaltrials.gov/ct2/show/NCT04351386.

Indexed as

algorithmatrial fibrillationautomatic detectioncardiaccardiologycardiovasculardiagnosisdigital healthECGelectrocardiogramheart diseaseheart failuremHealthmobile healthmorbidityphysiciansensorsmart technologysmartwatchwearable

Identifiers

PMID35481559
PMCPMC9675016

What OpenQuestion holds

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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.