Evidence map›Paper›PMID 32387247›Full record

ArticleHeart rhythm2020

Enhanced electrocardiographic monitoring of patients with Coronavirus Disease 2019.

Shashank Jain, Virginia Workman, Raj Ganeshan, Edinrin R Obasare, Alicia Burr, Ralph M DeBiasi, James V Freeman, Joseph Akar, Rachel Lampert, Lynda E Rosenfeld

Abstract read
In one paragraph

Article in Heart rhythm, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 4 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

31 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Article
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  7. Observational
  8. Review
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  10. Deep-learning model for screening sepsis using electrocardiography.Scandinavian journal of trauma, resuscitation and emergency medicine · 2021
    Article
  11. Article
  12. Article
  13. Prolonged QT predicts prognosis in COVID-19.Pacing and clinical electrophysiology : PACE · 2021
    Article
  14. Review
  15. Review
  16. Article
  17. Article
  18. Repositioned Drugs for COVID-19-the Impact on Multiple Organs.SN comprehensive clinical medicine · 2021
    Review
  19. Review
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Shashank JainSection of Cardiovascular Medicine, Yale University School of Medicine, New Haven, Connecticut.
Virginia WorkmanSection of Cardiovascular Medicine, Yale University School of Medicine, New Haven, Connecticut.
Raj GaneshanSection of Cardiovascular Medicine, Yale University School of Medicine, New Haven, Connecticut.
Edinrin R ObasareSection of Cardiovascular Medicine, Yale University School of Medicine, New Haven, Connecticut.
Alicia BurrSection of Cardiovascular Medicine, Yale University School of Medicine, New Haven, Connecticut.
Ralph M DeBiasiSection of Cardiovascular Medicine, Yale University School of Medicine, New Haven, Connecticut.
James V FreemanSection of Cardiovascular Medicine, Yale University School of Medicine, New Haven, Connecticut.
Joseph AkarSection of Cardiovascular Medicine, Yale University School of Medicine, New Haven, Connecticut.
Rachel LampertSection of Cardiovascular Medicine, Yale University School of Medicine, New Haven, Connecticut.
Lynda E RosenfeldSection of Cardiovascular Medicine, Yale University School of Medicine, New Haven, Connecticut. Electronic address: lynda.rosenfeld@yale.edu.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
NCATS NIH HHS UL1 TR001863
6 · The paper itself

Abstract

Background: Many of the drugs being used in the treatment of the ongoing pandemic coronavirus disease 2019 (COVID-19) are associated with QT prolongation. Expert guidance supports electrocardiographic (ECG) monitoring to optimize patient safety. Objective: The purpose of this study was to establish an enhanced process for ECG monitoring of patients being treated for COVID-19. Methods: We created a Situation Background Assessment Recommendation tool identifying the indication for ECGs in patients with COVID-19 and tagged these ECGs to ensure prompt over reading and identification of those with QT prolongation (corrected QT interval > 470 ms for QRS duration ≤ 120 ms; corrected QT interval > 500 ms for QRS duration > 120 ms). This triggered a phone call from the electrophysiology service to the primary team to provide management guidance and a formal consultation if requested. Results: During a 2-week period, we reviewed 2006 ECGs, corresponding to 524 unique patients, of whom 103 (19.7%) met the Situation Background Assessment Recommendation tool-defined criteria for QT prolongation. Compared with those without QT prolongation, these patients were more often in the intensive care unit (60 [58.3%] vs 149 [35.4%]) and more likely to be intubated (32 [31.1%] vs 76 [18.1%]). Fifty patients with QT prolongation (48.5%) had electrolyte abnormalities, 98 (95.1%) were on COVID-19-related QT-prolonging medications, and 62 (60.2%) were on 1-4 additional non-COVID-19-related QT-prolonging drugs. Electrophysiology recommendations were given to limit modifiable risk factors. No patient developed torsades de pointes. Conclusion: This process functioned efficiently, identified a high percentage of patients with QT prolongation, and led to relevant interventions. Arrhythmias were rare. No patient developed torsades de pointes.

Indexed as

BetacoronavirusElectrocardiographyAgedAged, 80 and overArrhythmias, CardiacCoronavirus InfectionsCOVID-19FemaleHumansMaleMiddle AgedPandemicsPneumonia, ViralRetrospective StudiesRisk FactorsSARS-CoV-2COVID-19ECGHydroxychloroquineQT prolongationTorsades de pointes

Identifiers

PMID32387247
PMCPMC7200355

What OpenQuestion holds

Textmetadata
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.