Evidence map›Paper›PMID 33358667›Full record

ArticleJACC. Clinical electrophysiology2021

Right Heart Strain on Presenting 12-Lead Electrocardiogram Predicts Critical Illness in COVID-19.

Mohamad Raad, Sarah Gorgis, Mohammed Dabbagh, Omar Chehab, Sachin Parikh, Gurjit Singh

Open access · greenAbstract read
In one paragraph

Article in JACC. Clinical electrophysiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
0.3field-weighted citation impact, top 30% 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, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.

  1. Are Pre-Hospitalization ECG Abnormalities Associated With Increased Mortality in COVID-19 Patients? A Quantitative Systematic Literature Review.Annals of noninvasive electrocardiology : the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc · 2024
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  5. Electrocardiogram-based mortality prediction in patients with COVID-19 using machine learning.Netherlands heart journal : monthly journal of the Netherlands Society of Cardiology and the Netherlands Heart Foundation · 2022
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Mohamad RaadDivision of Cardiology, Department of Medicine, Henry Ford Hospital, Detroit, Michigan, USA.
Sarah GorgisDivision of Cardiology, Department of Medicine, Henry Ford Hospital, Detroit, Michigan, USA.
Mohammed DabbaghDivision of Cardiology, Department of Medicine, Henry Ford Hospital, Detroit, Michigan, USA.
Omar ChehabDepartment of Medicine, Wayne State University-Detroit Medical Center, Detroit, Michigan, USA.
Sachin ParikhDivision of Cardiology, Department of Medicine, Henry Ford Hospital, Detroit, Michigan, USA.
Gurjit SinghSection of Cardiac Electrophysiology, Department of Medicine, Henry Ford Hospital, Detroit, Michigan, USA. Electronic address: Gsingh1@hfhs.org.
Henry Ford Hospital · USWayne State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis study aimed to assess the association of new right heart strain patterns on presenting 12-lead electrocardiogram (RHS-ECG) with outcomes in patients hospitalized with COVID-19.

backgroundCardiovascular comorbidities and complications, including right ventricular dysfunction, are common and are associated with worse outcomes in patients with COVID-19. The data on the clinical usefulness of the 12-lead ECG to aid with prognosis are limited.

methodsThis study retrospectively evaluated records from 480 patients who were consecutively admitted with COVID-19. ECGs obtained at presentation in the emergency department (ED) were considered index ECGs. RHS-ECG was defined by any new right-axis deviation, S

resultsECGs from the ED were available for 314 patients who were included in the analysis. Most patients were in sinus rhythm, with sinus tachycardia being the most frequent dysrhythmia. RHS-ECG findings were present in 40 (11%) patients. RHS-ECGs were significantly associated with the incidence of adverse outcomes and an independent predictor of mortality (adjusted odds ratio [adjOR]: 15.2; 95% confidence interval [CI]: 5.1 to 45.2; p < 0.001), the need for mechanical ventilation (adjOR: 8.8; 95% CI: 3.4 to 23.2; p < 0.001), and their composite (adjOR: 12.1; 95% CI: 4.3 to 33.9]; p < 0.001).

conclusionsRHS-ECG was associated with mechanical ventilation and mortality in patients admitted with COVID-19. Special attention should be taken in patients admitted with new signs of RHS on presenting ECG.

Indexed as

Critical CareElectrocardiographyArrhythmias, CardiacCOVID-19Critical IllnessEmergency Service, HospitalHumansKaplan-Meier EstimateRespiration, ArtificialRetrospective StudiesSARS-CoV-2Treatment OutcomeVentricular Dysfunction, RightCOVID-19ECGemergency departmentright heart strainright ventricular dysfunction

Identifiers

PMID33358667
PMCPMC7500909
OpenAlexW3087269031

What OpenQuestion holds

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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.