Evidence map›Paper›PMID 32280076›Full record

ArticleJournal of X-ray science and technology2020

Clinical and computed tomographic (CT) images characteristics in the patients with COVID-19 infection: What should radiologists need to know?

Pinggui Lei, Zhaoshu Huang, Guoli Liu, Pingxian Wang, Wen Song, Jujiang Mao, Guiquan Shen, Shi Zhou, Wei Qian, Jun Jiao

Open access · bronzeAbstract read
In one paragraph

Article in Journal of X-ray science and technology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 6 pooled it
3.5field-weighted citation impact, top 7% 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

25 citing papers in PubMed, 6 syntheses or guidelines pooled it, 42 citations in OpenAlex.

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  19. MinIP technique may be helpful in diagnosing COVID-19.Diagnostic and interventional radiology (Ankara, Turkey) · 2020
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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

10 authors at 2 institutions in 2 countries.

Pinggui LeiDepartment of Radiology, the Affiliated Hospital of Guizhou Medical University. Guiyang, China.
Zhaoshu HuangDepartment of Radiology, the Affiliated Hospital of Guizhou Medical University. Guiyang, China.
Guoli LiuDepartment of Radiology, the Affiliated Hospital of Guizhou Medical University. Guiyang, China.
Pingxian WangDepartment of Medical Insurance, the Affiliated Hospital of Guizhou Medical University, Guiyang, China.
Wen SongDepartment of Radiology, the Affiliated Hospital of Guizhou Medical University. Guiyang, China.
Jujiang MaoDepartment of Radiology, the Affiliated Hospital of Guizhou Medical University. Guiyang, China.
Guiquan ShenDepartment of Radiology, the Affiliated Hospital of Guizhou Medical University. Guiyang, China.
Shi ZhouDepartment of Radiology, the Affiliated Hospital of Guizhou Medical University. Guiyang, China.
Wei QianDepartment of Electrical and Computer Engineering, College of Engineering, University of Texas, El Paso, TX, USA.
Jun JiaoDepartment of Radiology, the Affiliated Hospital of Guizhou Medical University. Guiyang, China.
Guiyang Medical University · CNThe University of Texas at El Paso · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo evaluate the clinical and computed tomographic (CT) features in the patients with COVID-19 pneumonia confirmed by the real-time reverse transcriptase polymerase chain reaction (rRT-PCR) amplification of the viral DNA from a sputum sample. MATERIAL AND

methodsClinical information and CT findings of a total of 14 patients with COVID-19 infection (age range, 12-83 years; females 6) were analyzed retrospectively. The clinical information includes the history of exposure, laboratory results, and the symptoms (such as fever, cough, headache, etc.); CT findings of chest include the extension and distribution of lesion, the ground-glass opacity (GGO), consolidation, bronchovascular enlarged, irregular linear appearances, pleural effusion, and lymphadenopathy.

resultsEight patients had the exposure history for recent travel to Wuhan of Hubei province (8/14, 57%), 6 had the exposure to patients with COVID-19 infection. Significant statistical differences were observed in lymphocyte percentage decreased and C-reactive protein elevated (p = 0.015). Seven patients had fever, 7 had cough, 2 had headache, 3 had fatigue, 1 had body soreness, 3 had diarrhea, and 2 had no obvious symptoms. In chest CT examination, 10 patients were positive (10/14, 71.43%). Among these patients, 9 had lesions involving both lungs (9/10, 90%), 8 had lesions involving 4 to 5 lobes (8/10, 80%). Most of lesions were distributed peripherally and the most significant lesions were observed in the right lower lobe in 9 patients (9/10, 90%). Nodules were observed in 5 patients (5/10, 50%); GGO, consolidation, and bronchovascular enlarged were shown in 9 patients (9/10, 90%); irregular linear appearances were revealed in 7 patients (7/10, 70%); and pleural effusions were exhibited in 2 patients (2/10, 20%). Last, no patients showed lymphadenopathy.

conclusionThere were some typical CT features for diagnosis of COVID-19 pneumonia. The radiologists should know these CT findings and clinical information, which could help for accurate analysis in the patients with 2019 novel coronavirus infection.

Indexed as

BetacoronavirusAdolescentAdultAgedAged, 80 and overChildCoronavirus InfectionsCOVID-19FemaleHumansLungMaleMiddle AgedPandemicsPneumonia, ViralRadiologistscomputed tomographic findingsCOVID-19 infectionNovel coronavirusvirus pneumonia

Identifiers

PMID32280076
PMCPMC7369068
OpenAlexW3015419675

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.