Evidence map›Paper›PMID 34150910›Full record

ArticleJournal of immunology research2021

Analysis of Lymphocyte Subpopulations and Cytokines in COVID-19-Associated Pneumonia and Community-Acquired Pneumonia.

Guohong Liu, Xianghu Jiang, Xiaojiao Zeng, Yunbao Pan, Haibo Xu

Open access · goldAbstract read
In one paragraph

Article in Journal of immunology research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.0field-weighted citation impact, top 21% 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

9 citing papers in PubMed, 18 citations in OpenAlex.

  1. The prognostic value of serum apolipoprotein A1 levels in elderly patients withFrontiers in cellular and infection microbiology · 2025
    Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Review
  8. Review
  9. Article
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 1 institution in 1 country.

Guohong LiuDepartment of Radiology, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, Hubei, China.
Xianghu JiangDepartment of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, Hubei, China.
Xiaojiao ZengDepartment of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, Hubei, China.
Yunbao PanDepartment of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, Hubei, China.ORCID https://orcid.org/0000-0002-6311-2945
Haibo XuDepartment of Radiology, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, Hubei, China.
Wuhan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe 2019 novel coronavirus SARS-CoV-2 caused large outbreaks of COVID-19 worldwide. COVID-19 resembles community-acquired pneumonia (CAP). Our aim was to identify lymphocyte subpopulations to distinguish between COVID-19 and CAP.

methodsWe compared the peripheral blood lymphocytes and their subsets in 296 patients with COVID-19 and 130 patients with CAP. Parameters for independent prediction of COVID-19 were calculated by logistic regression.

resultsThe main lymphocyte subpopulations (CD3

conclusionsLymphopenia is an important part of SARS-CoV-2 infection, and lymphocyte subsets and cytokines may be useful to predict the severity and clinical outcomes of the disease.

Indexed as

CD4-CD8 RatioAdultAgedCommunity-Acquired InfectionsCOVID-19COVID-19 TestingFemaleHumansInterferon-gammaLymphocyte SubsetsLymphopeniaMaleMiddle AgedPneumoniaPrognosisSARS-CoV-2IFNG protein, humanInterferon-gammaTNF protein, humanTumor Necrosis Factor-alpha

Identifiers

PMID34150910
PMCPMC8197671
OpenAlexW3173074814

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.