Evidence map›Paper›PMID 33209422›Full record

ArticleJournal of thoracic disease2020

Preliminary investigation of relationship between clinical indicators and CT manifestation patterns of COVID-19 pneumonia improvement.

Nannan Shi, Fengxiang Song, Fengjun Liu, Pengrui Song, Yang Lu, Qinguo Hou, Xinyan Hua, Yun Ling, Jiulong Zhang, Chao Huang and 5 more

Open access · diamondAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of thoracic disease, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.0field-weighted citation impact, top 59% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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

15 authors at 4 institutions in 1 country.

Nannan ShiDepartment of Radiology, Shanghai Public Health Clinical Center, Shanghai, China.
Fengxiang SongDepartment of Radiology, Shanghai Public Health Clinical Center, Shanghai, China.
Fengjun LiuDepartment of Radiology, Shanghai Public Health Clinical Center, Shanghai, China.
Pengrui SongDepartment of Radiology, Shanghai Public Health Clinical Center, Shanghai, China.
Yang LuDepartment of Radiology, Shanghai Public Health Clinical Center, Shanghai, China.
Qinguo HouDepartment of Radiology, Shanghai Public Health Clinical Center, Shanghai, China.
Xinyan HuaDepartment of Radiology, Shanghai Public Health Clinical Center, Shanghai, China.
Yun LingDepartment of Infectious Disease, Shanghai Public Health Clinical Center, Shanghai, China.
Jiulong ZhangDepartment of Radiology, Shanghai Public Health Clinical Center, Shanghai, China.
Chao HuangShanghai Key Laboratory of Artificial Intelligence for Medical Image and Knowledge Graph, Shanghai, China.
Lei ShiShanghai Key Laboratory of Artificial Intelligence for Medical Image and Knowledge Graph, Shanghai, China.
Zhiyong ZhangFudan University, Shanghai, China.
Fei ShanDepartment of Radiology, Shanghai Public Health Clinical Center, Shanghai, China.
Qi ZhangShanghai Key Laboratory of Artificial Intelligence for Medical Image and Knowledge Graph, Shanghai, China.
Yuxin ShiDepartment of Radiology, Shanghai Public Health Clinical Center, Shanghai, China.
Shanghai Public Health Clinical Center · CNBeijing Academy of Artificial Intelligence · CNFudan University · CNHongzhiwei Technology (China) · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo retrospectively evaluate several clinical indicators related to the improvement of COVID-19 pneumonia on CT.

methodsA total of 62 patients with COVID-19 pneumonia were included. The CT scores based on lesion patterns and distributions in serial CT were investigated. The improvement and deterioration of pneumonia was assessed based on the changes of CT scores. Grouped by using the temperature, serum lymphocytes and high sensitivity CRP (hs-CRP) on admission respectively, the CT scores on admission, at peak time and at discharge were evaluated. Correlation analysis was carried out between the time to onset of pneumonia resolution on CT images and the recovery time of temperature, negative conversion of viral nucleic acid, serum lymphocytes and hs-CRP.

resultsThe CT scores of the fever group and lymphopenia group were significantly higher than those of normal group on admission, at peak time and at discharge; and the CT scores of normal hs-CRP group were significantly lower than those of the elevated hs-CRP group at peak time and at discharge (P all<0.05). The time to onset of pneumonia resolution on CT image was moderately correlated with negative conversion duration of viral nucleic acid (r =0.501, P<0.05) and the recovery time of hs-CPR (r =0.496, P<0.05).

conclusionsCOVID-19 pneumonia patients with no fever, normal lymphocytes and hs-CRP had mild lesions on admission, and presented with more absorption and fewer pulmonary lesions on discharge. The negative conversion duration of viral nucleic acid and the recovery time of hs-CPR may be the indicator of the pneumonia resolution.

Indexed as

computed tomographyCoronavirus Disease 2019 (COVID-19)pneumonia improvement

Identifiers

PMID33209422
PMCPMC7656389
OpenAlexW3087859581

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.