Evidence map›Paper›PMID 32592709›Full record

SynthesisChest2020

Chest CT Imaging Signature of Coronavirus Disease 2019 Infection: In Pursuit of the Scientific Evidence.

Hugo J A Adams, Thomas C Kwee, Derya Yakar, Michael D Hope, Robert M Kwee

Open access · hybridAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Chest, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
66citing papers in PubMed, 2 pooled it
12.1field-weighted citation impact, top 1% 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

66 citing papers in PubMed, 2 syntheses or guidelines pooled it, 121 citations in OpenAlex.

  1. Pooled it
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  18. Changes in diagnostic usefulness of the JRS scoring system in COVID-19 pneumonia by SARS-CoV-2 vaccination.Journal of infection and chemotherapy : official journal of the Japan Society of Chemotherapy · 2022
    Article
  19. Observational
  20. Article

6 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 4 institutions in 2 countries.

Hugo J A AdamsDepartment of Radiology and Nuclear Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands.
Thomas C KweeDepartment of Radiology, Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands. Electronic address: thomaskwee@gmail.com.
Derya YakarDepartment of Radiology, Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
Michael D HopeDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA; Radiology Service, Veterans Affairs Medical Center, San Francisco, CA.
Robert M KweeDepartment of Radiology, Zuyderland Medical Center, Heerlen/Sittard/Geleen, The Netherlands.
University Medical Center Groningen · NLUniversity of Amsterdam · NLUniversity of California, San Francisco · USZuyderland Medisch Centrum · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChest CT may be used for the diagnosis of coronavirus disease 2019 (COVID-19), but clear scientific evidence is lacking. Therefore, we systematically reviewed and meta-analyzed the chest CT imaging signature of COVID-19. RESEARCH QUESTION: What is the chest CT imaging signature of COVID-19 infection? STUDY DESIGN AND

methodsA systematic literature search was performed for original studies on chest CT imaging findings in patients with COVID-19. Methodologic quality of studies was evaluated. Pooled prevalence of chest CT imaging findings were calculated with the use of a random effects model in case of between-study heterogeneity (predefined as I

resultsTwenty-eight studies were included. The median number of patients with COVID-19 per study was 124 (range, 50-476), comprising a total of 3,466 patients. Median prevalence of symptomatic patients was 99% (range, >76.3%-100%). Twenty-seven of the studies (96%) had a retrospective design. Methodologic quality concerns were present with either risk of or actual referral bias (13 studies), patient spectrum bias (eight studies), disease progression bias (26 studies), observer variability bias (27 studies), and test review bias (14 studies). Pooled prevalence was 10.6% for normal chest CT imaging findings. Pooled prevalences were 90.0% for posterior predilection, 81.0% for ground-glass opacity, 75.8% for bilateral abnormalities, 73.1% for left lower lobe involvement, 72.9% for vascular thickening, and 72.2% for right lower lobe involvement. Pooled prevalences were 5.2% for pleural effusion, 5.1% for lymphadenopathy, 4.1% for airway secretions/tree-in-bud sign, 3.6% for central lesion distribution, 2.7% for pericardial effusion, and 0.7% for cavitation/cystic changes. Pooled prevalences of other CT imaging findings ranged between 10.5% and 63.2%.

interpretationStudies on chest CT imaging findings in COVID-19 suffer from methodologic quality concerns. More high-quality research is necessary to establish diagnostic CT criteria for COVID-19. Based on the available evidence that requires cautious interpretation, several chest CT imaging findings appear to be suggestive of COVID-19, but normal chest CT imaging findings do not exclude COVID-19, not even in symptomatic patients.

Indexed as

Tomography, X-Ray ComputedBetacoronavirusCoronavirus InfectionsCOVID-19HumansLungLymphadenopathyPandemicsPericardial EffusionPleural EffusionPneumonia, ViralSARS-CoV-2ThoraxchestCOVID-19CTmeta-analysissystematic review

Identifiers

PMID32592709
PMCPMC7314684
OpenAlexW3049147554

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.