Evidence map›Paper›PMID 33529266›Full record

ArticlePloS one2021

General medical publications during COVID-19 show increased dissemination despite lower validation.

Nan Gai, Kazuyoshi Aoyama, David Faraoni, Neil M Goldenberg, David N Levin, Jason T Maynes, Mark J McVey, Farrukh Munshey, Asad Siddiqui, Timothy Switzer and 1 more

Abstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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

2 citing papers in PubMed.

  1. Article
  2. Review
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

11 authors.

Nan GaiDepartment of Anesthesia and Pain Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada.
Kazuyoshi AoyamaDepartment of Anesthesia and Pain Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada.
David FaraoniDepartment of Anesthesia and Pain Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada.
Neil M GoldenbergDepartment of Anesthesia and Pain Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada.
David N LevinDepartment of Anesthesia and Pain Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada.
Jason T MaynesDepartment of Anesthesia and Pain Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada.
Mark J McVeyDepartment of Anesthesia and Pain Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada.
Farrukh MunsheyDepartment of Anesthesia and Pain Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada.
Asad SiddiquiDepartment of Anesthesia and Pain Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada.
Timothy SwitzerDepartment of Anesthesia and Pain Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada.
Benjamin E SteinbergDepartment of Anesthesia and Pain Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada.ORCID 0000-0002-3070-0548

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic has yielded an unprecedented quantity of new publications, contributing to an overwhelming quantity of information and leading to the rapid dissemination of less stringently validated information. Yet, a formal analysis of how the medical literature has changed during the pandemic is lacking. In this analysis, we aimed to quantify how scientific publications changed at the outset of the COVID-19 pandemic.

methodsWe performed a cross-sectional bibliometric study of published studies in four high-impact medical journals to identify differences in the characteristics of COVID-19 related publications compared to non-pandemic studies. Original investigations related to SARS-CoV-2 and COVID-19 published in March and April 2020 were identified and compared to non-COVID-19 research publications over the same two-month period in 2019 and 2020. Extracted data included publication characteristics, study characteristics, author characteristics, and impact metrics. Our primary measure was principal component analysis (PCA) of publication characteristics and impact metrics across groups.

resultsWe identified 402 publications that met inclusion criteria: 76 were related to COVID-19; 154 and 172 were non-COVID publications over the same period in 2020 and 2019, respectively. PCA utilizing the collected bibliometric data revealed segregation of the COVID-19 literature subset from both groups of non-COVID literature (2019 and 2020). COVID-19 publications were more likely to describe prospective observational (31.6%) or case series (41.8%) studies without industry funding as compared with non-COVID articles, which were represented primarily by randomized controlled trials (32.5% and 36.6% in the non-COVID literature from 2020 and 2019, respectively).

conclusionsIn this cross-sectional study of publications in four general medical journals, COVID-related articles were significantly different from non-COVID articles based on article characteristics and impact metrics. COVID-related studies were generally shorter articles reporting observational studies with less literature cited and fewer study sites, suggestive of more limited scientific support. They nevertheless had much higher dissemination.

Indexed as

BibliometricsCOVID-19Periodicals as TopicCommunicationCross-Sectional StudiesHumansPandemicsPeer Review, ResearchPrincipal Component Analysis

Identifiers

PMID33529266
PMCPMC7853485

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.