Evidence map›Paper›PMID 33949212›Full record

ReviewAmerican journal of physiology. Lung cellular and molecular physiology2021

The effect of estrogen in coronavirus disease 2019.

Qing Ma, Zhuo-Wen Hao, Yan-Feng Wang

Open access · greenAbstract readReview
In one paragraph

Review in American journal of physiology. Lung cellular and molecular physiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
4.4field-weighted citation impact, top 5% 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

12 citing papers in PubMed, 30 citations in OpenAlex.

  1. Article
  2. Estrogen and viral infection.Frontiers in immunology · 2025
    Review
  3. Article
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Testosterone in COVID-19: An Adversary Bane or Comrade Boon.Frontiers in cellular and infection microbiology · 2021
    Review
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

3 authors at 2 institutions in 1 country.

Qing MaInstitute of Hepatobiliary Diseases of Wuhan University, Zhongnan Hospital of Wuhan University, Wuhan, China.
Zhuo-Wen HaoInstitute of Hepatobiliary Diseases of Wuhan University, Zhongnan Hospital of Wuhan University, Wuhan, China.
Yan-Feng WangInstitute of Hepatobiliary Diseases of Wuhan University, Zhongnan Hospital of Wuhan University, Wuhan, China.
Zhongnan Hospital of Wuhan University · CNWuhan University · CN

Funding

Wuhan University (WHU) 2042020kfxg19
6 · The paper itself

Abstract

The outcomes of coronavirus disease 2019 (COVID-19) vary between men and women. Some statistical reports have shown that men have a higher risk of developing COVID-19 and suffer from worse outcomes than females. Although there are many factors that can explain the high prevalence of COVID-19 in men, such as lifestyle habits and the different profile of comorbidities among sexes, the distinctions between male and female immune systems cannot be ignored. It has been sufficiently shown that sex differences have a critical influence on the shaping of immune response, which then leads to different pathogenesis in infectious diseases. Compared with males, females typically have a more effective innate and adaptive immune response to viral infections in COVID-19. What's more, there is a growing body of evidence showing that estrogen exerts an effect on the regulation of immune response. This article examines the effect and mechanism of estrogen on COVID-19.

Indexed as

Adaptive ImmunityImmunity, InnateSex CharacteristicsCOVID-19EstrogensFemaleHumansMaleSARS-CoV-2EstrogensCOVID-19estrogenimmune responseSARS-CoV-2sex difference

Identifiers

PMID33949212
PMCPMC8270516
OpenAlexW3158525249

What OpenQuestion holds

Textmetadata
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.