Evidence map›Paper›PMID 32283052›Full record

SynthesisJournal of the American College of Radiology : JACR2020

Coronavirus Disease 2019 (COVID-19) CT Findings: A Systematic Review and Meta-analysis.

Cuiping Bao, Xuehuan Liu, Han Zhang, Yiming Li, Jun Liu

Open access · bronzeAbstract readMeta-AnalysisSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Journal of the American College of Radiology : JACR, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 230 papers, 16 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
230citing papers in PubMed, 16 pooled it
10.2field-weighted citation impact, top 2% 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

230 citing papers in PubMed, 16 syntheses or guidelines pooled it, 451 citations in OpenAlex.

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  13. Chest CT abnormalities in COVID-19: a systematic review.International journal of medical sciences · 2021
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170 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 1 institution in 1 country.

Cuiping BaoDepartment of Radiology, Tianjin Union Medical Center, Tianjin, China.
Xuehuan LiuDepartment of Radiology, Tianjin Union Medical Center, Tianjin, China.
Han ZhangDepartment of Radiology, Tianjin Union Medical Center, Tianjin, China.
Yiming LiDepartment of Radiology, Tianjin Union Medical Center, Tianjin, China. Electronic address: riminglee@126.com.
Jun LiuDepartment of Radiology, Tianjin Union Medical Center, Tianjin, China. Electronic address: cjr.liujun@vip.163.com.
Tianjin People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo date, considerable knowledge gaps remain regarding the chest CT imaging features of coronavirus disease 2019 (COVID-19). We performed a systematic review and meta-analysis of results from published studies to date to provide a summary of evidence on detection of COVID-19 by chest CT and the expected CT imaging manifestations.

methodsStudies were identified by searching PubMed database for articles published between December 2019 and February 2020. Pooled CT positive rate of COVID-19 and pooled incidence of CT imaging findings were estimated using a random-effect model.

resultsA total of 13 studies met inclusion criteria. The pooled positive rate of the CT imaging was 89.76% and 90.35% when only including thin-section chest CT. Typical CT signs were ground glass opacities (83.31%), ground glass opacities with mixed consolidation (58.42%), adjacent pleura thickening (52.46%), interlobular septal thickening (48.46%), and air bronchograms (46.46%). Other CT signs included crazy paving pattern (14.81%), pleural effusion (5.88%), bronchiectasis (5.42%), pericardial effusion (4.55%), and lymphadenopathy (3.38%). The most anatomic distributions were bilateral lung infection (78.2%) and peripheral distribution (76.95%). The incidences were highest in the right lower lobe (87.21%), left lower lobe (81.41%), and bilateral lower lobes (65.22%). The right upper lobe (65.22%), right middle lobe (54.95%), and left upper lobe (69.43%) were also commonly involved. The incidence of bilateral upper lobes was 60.87%. A considerable proportion of patients had three or more lobes involved (70.81%).

conclusionsThe detection of COVID-19 chest CT imaging is very high among symptomatic individuals at high risk, especially using thin-section chest CT. The most common CT features in patients affected by COVID-19 included ground glass opacities and consolidation involving the bilateral lungs in a peripheral distribution.

Indexed as

BetacoronavirusCoronavirus InfectionsCOVID-19FemaleHumansMalePandemicsPneumonia, ViralRadiography, ThoracicSARS-CoV-2Sensitivity and SpecificityTomography, X-Ray ComputedCOVID-19CT imaging findingsground glass opacitiesmeta-analysisthin-section chest CT

Identifiers

PMID32283052
PMCPMC7151282
OpenAlexW3012931235

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.