Evidence map›Paper›PMID 34048510›Full record

ArticleEuropean heart journal. Digital health2021

Electrocardiogram machine learning for detection of cardiovascular disease in African Americans: the Jackson Heart Study.

James D Pollard, Kazi T Haq, Katherine J Lutz, Nichole M Rogovoy, Kevin A Paternostro, Elsayed Z Soliman, Joseph Maher, Joo A C Lima, Solomon K Musani, Larisa G Tereshchenko

Erratum issuedAbstract read
In one paragraph

Article in European heart journal. Digital health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–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

9 citing papers in PubMed.

  1. Article
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  6. Digitizing ECG image: A new method and open-source software code.Computer methods and programs in biomedicine · 2022
    Article
  7. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

James D PollardUniversity of Mississippi Medical Center, 2500 N State St, Jackson, MS 39216, USA.ORCID https://orcid.org/0000-0001-5359-2861
Kazi T HaqDepartment of Medicine, Knight Cardiovascular Institute, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, UHN62, Portland, OR 97239, USA.
Katherine J LutzDepartment of Medicine, Knight Cardiovascular Institute, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, UHN62, Portland, OR 97239, USA.ORCID https://orcid.org/0000-0002-0685-8273
Nichole M RogovoyDepartment of Medicine, Knight Cardiovascular Institute, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, UHN62, Portland, OR 97239, USA.
Kevin A PaternostroDepartment of Medicine, Knight Cardiovascular Institute, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, UHN62, Portland, OR 97239, USA.
Elsayed Z SolimanDivision of Public Health Sciences and Department of Medicine, Cardiology Section, Epidemiological Cardiology Research Center, Wake Forest School of Medicine, 475 Vine St, Winston-Salem, NC 27101, USA.ORCID https://orcid.org/0000-0001-5632-8150
Joseph MaherUniversity of Mississippi Medical Center, 2500 N State St, Jackson, MS 39216, USA.
Joo A C LimaCardiovascular Division, Department of Medicine, Johns Hopkins School of Medicine, 733 N Broadway, Baltimore, MD 21205, USA.
Solomon K MusaniUniversity of Mississippi Medical Center, 2500 N State St, Jackson, MS 39216, USA.
Larisa G TereshchenkoDepartment of Medicine, Knight Cardiovascular Institute, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, UHN62, Portland, OR 97239, USA.ORCID https://orcid.org/0000-0002-6976-1313

Funding

Novel ECG Measures and Risk of Sudden Cardiac DeathR01HL118277 · NHLBI · OREGON HEALTH & SCIENCE UNIVERSITY · PI TERESHCHENKO, LARISA GENNADIEVNA · 2013 to 2016
$1.5M
Novel ECG measures and risk of sudden cardiac deathR56HL118277 · NHLBI · OREGON HEALTH & SCIENCE UNIVERSITY · PI TERESHCHENKO, LARISA GENNADIEVNA · 2018 to 2018
$396k
NHLBI NIH HHS HHSN268201800010INHLBI NIH HHS HHSN268201800011CNHLBI NIH HHS HHSN268201800011INHLBI NIH HHS HHSN268201800012CNHLBI NIH HHS HHSN268201800012INHLBI NIH HHS HHSN268201800014CNHLBI NIH HHS HHSN268201800014INHLBI NIH HHS HHSN268201800015INHLBI NIH HHS R01 HL118277NHLBI NIH HHS R56 HL118277NIMHD NIH HHS HHSN268201800013I
6 · The paper itself

Abstract

aimsAlmost half of African American (AA) men and women have cardiovascular disease (CVD). Detection of prevalent CVD in community settings would facilitate secondary prevention of CVD. We sought to develop a tool for automated CVD detection. METHODS AND

resultsParticipants from the Jackson Heart Study (JHS) with analysable electrocardiograms (ECGs) (

conclusionsSimple model (age and QRS-T angle) can be used for prevalent CVD detection in limited-resources community settings, which opens an avenue for secondary prevention of CVD in underserved communities.

Indexed as

Cardiovascular diseaseECGMachine learningQRS-T angle

Identifiers

PMID34048510
PMCPMC8139412

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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.