Evidence map›Paper›PMID 33553391›Full record

ReviewWorld journal of clinical cases2021

Clinical features and potential mechanism of coronavirus disease 2019-associated liver injury.

Mei-Wen Han, Ming Wang, Meng-Ying Xu, Wei-Peng Qi, Peng Wang, Dong Xi

Abstract readReview
In one paragraph

Review in World journal of clinical cases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

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

7 citing papers in PubMed.

  1. Article
  2. Review
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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

6 authors.

Mei-Wen HanInstitute of Infectious Disease, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei Province, China.
Ming WangInstitute of Infectious Disease, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei Province, China.
Meng-Ying XuInstitute of Infectious Disease, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei Province, China.
Wei-Peng QiInstitute of Infectious Disease, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei Province, China.
Peng WangInstitute of Infectious Disease, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei Province, China.
Dong XiInstitute of Infectious Disease, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei Province, China. xidong@tjh.tjmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2, has posed a serious threat to global public health security. With the increase in the number of confirmed cases globally, the World Health Organization has declared the outbreak of COVID-19 an international public health emergency. Despite atypical pneumonia as the primary symptom, liver dysfunction has also been observed in many clinical cases and is associated with the mortality risk in patients with COVID-19, like severe acute respiratory syndrome and Middle East respiratory syndrome. Here we will provide a schematic overview of the clinical characteristics and the possible mechanisms of liver injury caused by severe acute respiratory syndrome coronavirus 2 infection, which may provide help for optimizing the management of liver injury and reducing mortality in COVID-19 patients.

Indexed as

COVID-19Liver injuryNovel coronavirusSARS-CoV-2

Identifiers

PMID33553391
PMCPMC7829721

What OpenQuestion holds

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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.