Evidence map›Paper›PMID 38801762›Full record

ArticleJMIR research protocols2024

Mobile Electrocardiograms in the Detection of Subclinical Atrial Fibrillation in High-Risk Outpatient Populations: Protocol for an Observational Study.

Ajay Mittal, Yasmine Elkaldi, Susana Shih, Riken Nathu, Mark Segal

Abstract read
In one paragraph

Article in JMIR research protocols, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing 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.

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

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

  1. Pooled it
  2. 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

5 authors.

Ajay MittalCollege of Medicine, University of Florida, Gainesville, FL, United States.ORCID 0009-0004-7021-3121
Yasmine Elkaldi *College of Medicine, University of Florida, Gainesville, FL, United States.ORCID 0009-0000-6617-1396
Susana Shih *College of Osteopathic Medicine, Nova Southeastern University, Fort Lauderdale, FL, United States.ORCID 0009-0000-3145-5743
Riken Nathu *College of Medicine, University of Florida, Gainesville, FL, United States.ORCID 0000-0002-8873-5145
Mark Segal *College of Medicine, University of Florida, Gainesville, FL, United States.ORCID 0000-0002-5502-2042

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSingle-lead, smartphone-based mobile electrocardiograms (ECGs) have the potential to provide a noninvasive, rapid, and cost-effective means of screening for atrial fibrillation (AFib) in outpatient settings. AFib has been associated with various comorbid diseases that prompt further investigation and screening methodologies for at-risk populations. A simple 30-second sinus rhythm strip from the KardiaMobile ECG (AliveCor) can provide an effective screen for cardiac rhythm abnormalities.

objectiveThe aim of this study is to demonstrate the feasibility of performing Kardia-enabled ECG recordings routinely in outpatient settings in high-risk populations and its potential use in uncovering previous undiagnosed cases of AFib. Specific aim 1 is to determine the feasibility and accuracy of performing routine cardiac rhythm sampling in patients deemed at high risk for AFib. Specific aim 2 is to determine whether routine rhythm sampling in outpatient clinics with high-risk patients can be used cost-effectively in an outpatient clinic without increasing the time it takes for the patient to be seen by a physician.

methodsParticipants were recruited across 6 clinic sites across the University of Florida Health Network: University of Florida Health Nephrology, Sleep Center, Ophthalmology, Urology, Neurology, and Pre-Surgical. Participants, aged 18-99 years, who agreed to partake in the study were given a consent form and completed a questionnaire regarding their past medical history and risk factors for cardiovascular disease. Single-lead, 30-second ECGs were taken by the KardiaMobile ECG device. If patients are found to have newly diagnosed AFib, the attending physician is notified, and a 12-lead ECG or standard ECG equivalent will be ordered.

resultsAs of March 1, 2024, a total of 2339 participants have been enrolled. Of the data collected thus far, the KardiaMobile rhythm strip reported 381 abnormal readings, which are pending analysis from a cardiologist. A total of 78 readings were labeled as possible AFib, 159 readings were labeled unclassified, and 49 were unreadable. Of note, the average age of participants was 61 (SD 10.25) years, and the average self-reported weight was 194 (SD 14.26) pounds. Additionally, 1572 (67.25%) participants report not regularly seeing a cardiologist. Regarding feasibility, the average length of enrolling a patient into the study was 3:30 (SD 0.5) minutes after informed consent was completed, and medical staff across clinic sites (n=25) reported 9 of 10 level of satisfaction with the impact of the screening on clinic flow.

conclusionsPreliminary data show promise regarding the feasibility of using KardiaMobile ECGs for the screening of AFib and prevention of cardiological disease in vulnerable outpatient populations. The use of a single-lead mobile ECG strip can serve as a low-cost, effective AFib screen for implementation across free clinics attempting to provide increased health care accessibility. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/52647.

Indexed as

Atrial FibrillationElectrocardiographyAdolescentAdultAgedAged, 80 and overFeasibility StudiesFemaleHumansMaleMiddle AgedObservational Studies as TopicOutpatientsSmartphoneYoung Adultappappsatrial fibrillationcardiologycontrolled trialcontrolled trialsdigital healthECGeffectivenesselectrocardiogramfeasibilityKardiaMobile single-lead ECGsmobile ECGmobile healthmobile phoneoutpatientrandomizedsmartphone

Identifiers

PMID38801762
PMCPMC11165282

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Registered trials

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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.