Evidence map›Paper›PMID 34009129›Full record

Observational studyJMIR mHealth and uHealth2021

Performance of a Mobile Single-Lead Electrocardiogram Technology for Atrial Fibrillation Screening in a Semirural African Population: Insights From "The Heart of Ethiopia: Focus on Atrial Fibrillation" (TEFF-AF) Study.

Bradley M Pitman, Sok-Hui Chew, Christopher X Wong, Amenah Jaghoori, Shinsuke Iwai, Gijo Thomas, Andrew Chew, Prashanthan Sanders, Dennis H Lau

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in JMIR mHealth and uHealth, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.7field-weighted citation impact, top 14% 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

9 citing papers in PubMed, 14 citations in OpenAlex.

  1. Bridging the Workforce Gap in Ethiopian Catheterization Laboratories.Journal of the Society for Cardiovascular Angiography & Interventions · 2026
    Article
  2. Advancing Interventional Cardiology in Sub-Saharan Africa: The Role of Artificial Intelligence.Journal of the Society for Cardiovascular Angiography & Interventions · 2026
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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

9 authors at 2 institutions in 1 country.

Bradley M PitmanCentre for Heart Rhythm Disorders, The University of Adelaide, Adelaide, Australia.ORCID 0000-0001-6610-3473
Sok-Hui ChewFlinders University, Adelaide, Australia.ORCID 0000-0001-9568-8546
Christopher X WongCentre for Heart Rhythm Disorders, The University of Adelaide, Adelaide, Australia.ORCID 0000-0002-1913-6675
Amenah JaghooriCentre for Heart Rhythm Disorders, The University of Adelaide, Adelaide, Australia.ORCID 0000-0002-0752-3846
Shinsuke IwaiCentre for Heart Rhythm Disorders, The University of Adelaide, Adelaide, Australia.ORCID 0000-0001-7775-6429
Gijo ThomasCentre for Heart Rhythm Disorders, The University of Adelaide, Adelaide, Australia.ORCID 0000-0002-2307-1560
Andrew ChewFlinders University, Adelaide, Australia.ORCID 0000-0002-7914-591X
Prashanthan SandersCentre for Heart Rhythm Disorders, The University of Adelaide, Adelaide, Australia.ORCID 0000-0003-3803-8429
Dennis H LauCentre for Heart Rhythm Disorders, The University of Adelaide, Adelaide, Australia.ORCID 0000-0001-7753-1318
The University of Adelaide · AUFlinders University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAtrial fibrillation (AF) screening using mobile single-lead electrocardiogram (ECG) devices has demonstrated variable sensitivity and specificity. However, limited data exists on the use of such devices in low-resource countries.

objectiveThe goal of the research was to evaluate the utility of the KardiaMobile device's (AliveCor Inc) automated algorithm for AF screening in a semirural Ethiopian population.

methodsAnalysis was performed on 30-second single-lead ECG tracings obtained using the KardiaMobile device from 1500 TEFF-AF (The Heart of Ethiopia: Focus on Atrial Fibrillation) study participants. We evaluated the performance of the KardiaMobile automated algorithm against cardiologists' interpretations of 30-second single-lead ECG for AF screening.

resultsA total of 1709 single-lead ECG tracings (including repeat tracing on 209 occasions) were analyzed from 1500 Ethiopians (63.53% [953/1500] male, mean age 35 [SD 13] years) who presented for AF screening. Initial successful rhythm decision (normal or possible AF) with one single-lead ECG tracing was lower with the KardiaMobile automated algorithm versus manual verification by cardiologists (1176/1500, 78.40%, vs 1455/1500, 97.00%; P<.001). Repeat single-lead ECG tracings in 209 individuals improved overall rhythm decision, but the KardiaMobile automated algorithm remained inferior (1301/1500, 86.73%, vs 1479/1500, 98.60%; P<.001). The key reasons underlying unsuccessful KardiaMobile automated rhythm determination include poor quality/noisy tracings (214/408, 52.45%), frequent ectopy (22/408, 5.39%), and tachycardia (>100 bpm; 167/408, 40.93%). The sensitivity and specificity of rhythm decision using KardiaMobile automated algorithm were 80.27% (1168/1455) and 82.22% (37/45), respectively.

conclusionsThe performance of the KardiaMobile automated algorithm was suboptimal when used for AF screening. However, the KardiaMobile single-lead ECG device remains an excellent AF screening tool with appropriate clinician input and repeat tracing.

trial registrationAustralian New Zealand Clinical Trials Registry ACTRN12619001107112; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=378057&isReview=true.

Indexed as

Atrial FibrillationEragrostisAdultAustraliaElectrocardiographyEthiopiaHumansMaleTechnologyatrial fibrillationscreeningsingle-lead ECGsub-Saharan Africa

Identifiers

PMID34009129
PMCPMC8173399
OpenAlexW3162992777

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.