Evidence map›Paper›PMID 33142125›Full record

SynthesisClinical imaging2021

Chest CT findings of coronavirus disease 2019 (COVID-19): A comprehensive meta-analysis of 9907 confirmed patients.

Ahmadreza Zarifian, Mohammad Ghasemi Nour, Arash Akhavan Rezayat, Reza Rahimzadeh Oskooei, Bita Abbasi, Ramin Sadeghi

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Clinical imaging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Observational
  2. Article
  3. Observational
  4. Article
  5. Article
  6. Temporal changes of lung computed tomography findings pulmonary COVID-19 infection.Journal of medical imaging and radiation sciences · 2022
    Observational
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Covid-19 imaging: A narrative review.Annals of medicine and surgery (2012) · 2021
    Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Ahmadreza ZarifianClinical Research Unit, Mashhad University of Medical Sciences, Mashhad, Iran; Student Research Committee, Faculty of Medicine, Mashhad University of Medical Science, Mashhad, Iran.
Mohammad Ghasemi NourStudent Research Committee, Faculty of Medicine, Mashhad University of Medical Science, Mashhad, Iran.
Arash Akhavan RezayatStudent Research Committee, Faculty of Medicine, Mashhad University of Medical Science, Mashhad, Iran.
Reza Rahimzadeh OskooeiStudent Research Committee, Faculty of Medicine, Mashhad University of Medical Science, Mashhad, Iran.
Bita AbbasiDepartment of Radiology, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran. Electronic address: AbbasiB@mums.ac.ir.
Ramin SadeghiNuclear Medicine Research Center, Mashhad University of Medical Sciences, Mashhad, Khorasan Razavi, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesWe performed a systematic review and meta-analysis of the prevalence of chest CT findings in patients with confirmed COVID-19 infection.

methodsSystematic review of the literature was performed using PubMed, Scopus, Embase, and Google Scholar to retrieve original studies on chest CT findings of patients with confirmed COVID-19, available up to 10 May 2020. Data on frequency and distribution of chest CT findings were extracted from eligible studies, pooled and meta-analyzed using random-effects model to calculate the prevalence of chest CT findings.

resultsOverall, 103 studies (pooled population: 9907 confirmed COVID-19 patients) were meta-analyzed. The most common CT findings were ground-glass opacities (GGOs) (77.18%, 95%CI = 72.23-81.47), reticulations (46.24%, 95%CI = 38.51-54.14), and air bronchogram (41.61%, 95%CI = 32.78-51.01). Pleural thickening (33.35%, 95%CI = 21.89-47.18) and bronchial wall thickening (15.48%, 95%CI = 8.54-26.43) were major atypical and airway findings. Lesions were predominantly distributed bilaterally (75.72%, 95%CI = 70.79-80.06) and peripherally (65.64%, 95%CI = 58.21-72.36), while 8.20% (95%CI = 6.30-10.61) of patients had no abnormal findings and pre-existing lung diseases were present in 6.01% (95%CI = 4.37-8.23).

conclusionsThe most common CT findings in COVID-19 are GGOs with/without consolidation, reticulations, and air bronchogram, which often involve both lungs with peripheral distribution. However, COVID-19 might present with atypical manifestations or no abnormal findings in chest CT, which deserve clinicians' notice.

Indexed as

COVID-19HumansLungRetrospective StudiesSARS-CoV-2ThoraxTomography, X-Ray ComputedComputed tomographyCoronavirusCOVID-19Meta-analysisThorax

Identifiers

PMID33142125
PMCPMC7585632

What OpenQuestion holds

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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.