Evidence map›Paper›PMID 32837983›Full record

ReviewGenes & diseases2020

Coronavirus disease 2019 (COVID-19): cytokine storms, hyper-inflammatory phenotypes, and acute respiratory distress syndrome.

Shi-Hui Lin, Yi-Si Zhao, Dai-Xing Zhou, Fa-Chun Zhou, Fang Xu

Open access · diamondAbstract readReview
In one paragraph

Review in Genes & diseases, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed, 1 pooled it
1.5field-weighted citation impact, top 10% 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

40 citing papers in PubMed, 1 synthesis or guideline pooled it, 74 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

5 authors at 2 institutions in 1 country.

Shi-Hui LinDepartment of Critical Care Medicine, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Yi-Si ZhaoDepartment of Critical Care Medicine, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Dai-Xing ZhouDepartment of Critical Care Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Fa-Chun ZhouDepartment of Critical Care Medicine, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Fang XuDepartment of Critical Care Medicine, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
The Affiliated Yongchuan Hospital of Chongqing Medical University · CNTongji Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Coronavirus Disease 2019 (COVID-19) was first identified in China at the end of 2019. Acute respiratory distress syndrome (ARDS) represents the most common and serious complication of COVID-19. Cytokine storms are a pathophysiological feature of COVID-19 and play an important role in distinguishing hyper-inflammatory subphenotypes of ARDS. Accordingly, in this review, we focus on hyper-inflammatory host responses in ARDS that play a critical role in the differentiated development of COVID-19. Furthermore, we discuss inflammation-related indicators that have the potential to identify hyper-inflammatory subphenotypes of COVID-19, especially for those with a high risk of ARDS. Finally, we explore the possibility of improving the quality of monitoring and treatment of COVID-19 patients and in reducing the incidence of critical illness and mortality via better distinguishing hyper- and hypo-inflammatory subphenotypes of COVID-19.

Indexed as

Acute respiratory distress syndromeCOVID-19Cytokine stormHyper-inflammatory host responseSARS-CoV-2

Identifiers

PMID32837983
PMCPMC7323676
OpenAlexW3039343775

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.