Evidence map›Paper›PMID 28775064›Full record

ArticleJournal of the American Heart Association2017

Ectopy on a Single 12-Lead ECG, Incident Cardiac Myopathy, and Death in the Community.

Kaylin T Nguyen, Eric Vittinghoff, Thomas A Dewland, Jonathan W Dukes, Elsayed Z Soliman, Phyllis K Stein, John S Gottdiener, Alvaro Alonso, Lin Y Chen, Bruce M Psaty and 2 more

Open access · goldAbstract readMulticenter Study
In one paragraph

Article in Journal of the American Heart Association, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 2 pooled it
2.5field-weighted citation impact, top 9% 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

27 citing papers in PubMed, 2 syntheses or guidelines pooled it, 51 citations in OpenAlex.

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  10. Predictors of Myocardial Fibrosis Detected by CMR in Patients With Idiopathic PVCs.Annals of noninvasive electrocardiology : the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc · 2024
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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

12 authors at 9 institutions in 1 country.

Kaylin T NguyenElectrophysiology Section, Division of Cardiology, University of California, San Francisco, San Francisco, CA.
Eric VittinghoffDepartment of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA.
Thomas A DewlandKnight Cardiovascular Institute, Oregon Health & Science University, Portland, OR.
Jonathan W DukesElectrophysiology Section, Division of Cardiology, University of California, San Francisco, San Francisco, CA.
Elsayed Z SolimanDivision of Public Health Sciences, Department of Epidemiology and Prevention, Epidemiological Cardiology Research Center, Wake Forest School of Medicine, Winston-Salem, NC.
Phyllis K SteinDivision of Cardiology, Washington University School of Medicine, St Louis, MO.
John S GottdienerDivision of Cardiovascular Medicine, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD.
Alvaro AlonsoDepartment of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA.
Lin Y ChenCardiovascular Division, Department of Medicine, University of Minnesota, Minneapolis, MN.
Bruce M PsatyCardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Services, University of Washington, Seattle, WA.
Susan R HeckbertDepartment of Epidemiology and Cardiovascular Health Research Unit, University of Washington, Seattle, WA.
Gregory M MarcusElectrophysiology Section, Division of Cardiology, University of California, San Francisco, San Francisco, CA marcusg@medicine.ucsf.edu.
University of California, San Francisco · USEmory University · USGroup Health Cooperative · USOregon Health & Science University · USUniversity of Maryland, Baltimore · USUniversity of Minnesota · USUniversity of Washington · USWake Forest University · USWashington University in St. Louis · US

Funding

American Heart Association-American Stroke Association 16EIA26410001
6 · The paper itself

Abstract

backgroundAtrial fibrillation and heart failure are 2 of the most common diseases, yet ready means to identify individuals at risk are lacking. The 12-lead ECG is one of the most accessible tests in medicine. Our objective was to determine whether a premature atrial contraction observed on a standard 12-lead ECG would predict atrial fibrillation and mortality and whether a premature ventricular contraction would predict heart failure and mortality. METHODS AND

resultsWe utilized the CHS (Cardiovascular Health) Study, which followed 5577 participants for a median of 12 years, as the primary cohort. The ARIC (Atherosclerosis Risk in Communities Study), the replication cohort, captured data from 15 792 participants over a median of 22 years. In the CHS, multivariable analyses revealed that a baseline 12-lead ECG premature atrial contraction predicted a 60% increased risk of atrial fibrillation (hazard ratio, 1.6; 95% CI, 1.3-2.0;

conclusionsBased on a single standard ECG, a premature atrial contraction predicted incident atrial fibrillation and death and a premature ventricular contraction predicted incident heart failure and death, suggesting that this commonly used test may predict future disease.

Indexed as

AgedAtrial FibrillationAtrial Premature ComplexesCardiomyopathiesElectrocardiographyFemaleHeart FailureHumansIncidenceMaleMiddle AgedPrognosisProspective StudiesRisk FactorsUnited StatesVentricular Premature Complexesatrial fibrillationheart failuremortalitypremature atrial contractionspremature ventricular contractions

Identifiers

PMID28775064
PMCPMC5586444
OpenAlexW2742432928

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.