Evidence map›Paper›PMID 33790623›Full record

ArticleJournal of inflammation research2021

Longitudinal Chest CT Features in Severe/Critical COVID-19 Cases and the Predictive Value of the Initial CT for Mortality.

Hailan Li, Shiyong Luo, Youming Zhang, Xiaoyi Xiao, Huaping Liu

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Article in Journal of inflammation research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
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2citing 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

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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

2 citing papers in PubMed.

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4 · The record

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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

5 authors.

Hailan Li *Department of Radiology, Hunan Provincial People's Hospital (The First Affiliated Hospital of Hunan Normal University), Changsha, 410000, Hunan Province, People's Republic of China.
Shiyong Luo *Department of Radiology, Wuhan Third Hospital (Tongren Hospital of Wuhan University), Wuhan, 430060, Hubei Province, People's Republic of China.
Youming ZhangDepartment of Radiology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, People's Republic of China.
Xiaoyi XiaoDepartment of Radiology, The Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan Province, People's Republic of China.
Huaping LiuDepartment of Radiology, The Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan Province, People's Republic of China.ORCID 0000-0002-1434-7553

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo evaluate longitudinal computed tomography (CT) features and the predictive value of the initial CT and clinical characteristics for mortality in patients with severe/critical coronavirus disease 2019 (COVID-19) pneumonia.

methodsA retrospective analysis was performed on patients with COVID-19 pneumonia confirmed by laboratory. By excluding mild and common patients, 155 severe/critical patients with definite outcome were finally enrolled. A total of 516 CTs of 147 patients were divided into four stages according to the time after onset (stage 1, 1-7 days; stage 2, 8-14 days; stage 3, 15-21 days, and stage 4, >21 days). The evolving imaging features between the survival and non-survival groups were compared by using Chi-square, Fisher's exact test, student's

resultsGround-glass opacities (GGO) patterns were predominant for stages 1 and 2 for both groups (both

conclusionLongitudinal imaging features demonstrated differences between the two groups, which may help determine the patient's prognosis. The initial CT score combined with age, AST, and neutrophil count is an excellent predictor for mortality in COVID-19 patients.

Indexed as

chest CT scoreCOVID-19mortalitymultivariate combined analysisrisk factorsSARS-CoV-2

Identifiers

PMID33790623
PMCPMC8007600

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