Evidence map›Paper›PMID 33426973›Full record

ArticleAnnals of medicine2021

Chest CT features associated with the clinical characteristics of patients with COVID-19 pneumonia.

Ruichao Niu, Shuming Ye, Yongfeng Li, Hua Ma, Xiaoting Xie, Shilian Hu, Xiaoming Huang, Yangshu Ou, Jie Chen

Open access · goldAbstract read
In one paragraph

Article in Annals of medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
3.1field-weighted citation impact, top 8% 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

15 citing papers in PubMed, 23 citations in OpenAlex.

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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

9 authors at 8 institutions in 1 country.

Ruichao NiuDepartment of Respiratory Medicine, Xiangya Hospital, Central South University, Changsha, PR China.
Shuming YeDepartment of Respiratory Medicine, Wuhan First Hospital/Wuhan Hospital of Traditional Chinese and Western Medicine, Wuhan, PR China.
Yongfeng LiDepartment of Respiratory Medicine, Anyang District Hospital, Anyang, PR China.
Hua MaDepartment of Infectious Disease, People's Hospital of Liuyang City, Liuyang, PR China.
Xiaoting XieDepartment of Respiratory Medicine, People's Hospital of Ningxiang City, Ningxiang, PR China.
Shilian HuDepartment of Radiology and Imaging, The Third Hospital of Yongzhou City, Yongzhou, PR China.
Xiaoming HuangDepartment of Radiology and Imaging, Traditional Chinese Medicine Hospital of Leiyang City, Hengyang, PR China.
Yangshu OuDepartment of Respiratory Medicine, Xiangya Hospital, Central South University, Changsha, PR China.
Jie ChenDepartment of Respiratory Medicine, Xiangya Hospital, Central South University, Changsha, PR China.
Central South University · CNAnyang Hospital of Traditional Chinese Medicine · CNAnyang Tumor Hospital · CNChangzhou Third People's Hospital · CNFuyang City People's Hospital · CNJiangxi Pingxiang People's Hospital · CNWuhan City Chinese Medicine Hospital · CNXiangya Hospital Central South University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesCoronavirus disease 2019 (COVID-19) has rapidly swept across the world. This study aimed to explore the relationship between the chest CT findings and clinical characteristics of COVID-19 patients.

methodsPatients with COVID-19 confirmed by next-generation sequencing or RT-PCR who had undergone more than 4 serial chest CT procedures were retrospectively enrolled.

resultsThis study included 361 patients - 192 men and 169 women. On initial chest CT, more lesions were identified as multiple bilateral lungs lesions and localised in the peripheral lung. The predominant patterns of abnormality were ground-glass opacities (GGO) (28.5%), consolidation (13.0%), nodule (23.0%), fibrous stripes (5.3%) and mixed (30.2%). Severe cases were more common in patients with a mixed pattern (21.1%) and less common in patients with nodules (2.4%). During follow-up CT, the mediumtotal severity score (TSS) in patients with nodules and fibrous strips was significantly lower than that in patients with mixed patterns in all three stages (

conclusionChest CT plays an important role in diagnosing COVID-19. The CT features may vary by age. Different CT features are not only associated with clinical manifestation but also patient prognosis. Key messages The initial chest CT findings of COVID-19 could help us monitor and predict the outcome. Nodules were more common in non severe cases and had a favorable prognosis. The mixed pattern was more common in severe cases and usually had a relatively poor outcome.

Indexed as

Tomography, X-Ray ComputedAdolescentAdultCOVID-19FemaleHumansMaleMiddle AgedRetrospective StudiesThoraxYoung Adultcomputed tomographyCOVID-19pneumoniaSARS-CoV-2 imaging features

Identifiers

PMID33426973
PMCPMC7877953
OpenAlexW3120657361

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.