Evidence map›Paper›PMID 32774170›Full record

ReviewClinical and molecular allergy : CMA2020

A gendered magnifying glass on COVID-19.

Lorenzo Salvati, Benedetta Biagioni, Emanuele Vivarelli, Paola Parronchi

Abstract readReview
In one paragraph

Review in Clinical and molecular allergy : CMA, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
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  5. Review
  6. Article
  7. Gender and genetic factors impacting COVID-19 severity.Journal of family medicine and primary care · 2021
    Review
  8. Review
  9. Article
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  11. Review
  12. Article
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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

4 authors.

Lorenzo SalvatiDepartment of Experimental and Clinical Medicine, University of Florence, Largo Brambilla 3, 50134 Florence, Italy.
Benedetta BiagioniDepartment of Experimental and Clinical Medicine, University of Florence, Largo Brambilla 3, 50134 Florence, Italy.
Emanuele VivarelliDepartment of Experimental and Clinical Medicine, University of Florence, Largo Brambilla 3, 50134 Florence, Italy.
Paola ParronchiDepartment of Experimental and Clinical Medicine, University of Florence, Largo Brambilla 3, 50134 Florence, Italy.ORCID 0000-0002-9184-5089

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

COVID-19 pandemia is affecting Countries worldwide with a gendered death excess as being a male represents, especially in the 50-69 years age group, an unfavourable factor. Females are constitutionally prone to defend themselves against pathogens with a stronger efficiency than males. As a fact, several genes involved into the regulation of the innate and adaptive immune response are strategically placed on the X-chromosome and, among them, pathogen-related receptors (PRRs), such as Toll-like receptor 7, suitable to recognize ssRNAs and trigger a gendered successful anti-viral fight. On the other hand, a more regulated IL-6 production and a more contained inflammation after the encounter of a pathogen supply score points in favour of the female sex in the view that an abnormal and exaggerated cytokine release does represent the hallmark of the deathful SARS-CoV-2 infection. The sex-prevalent expression of the attachment and permissive molecules ACE2 and TMPRSS2 further supports the concept of a male-oriented vulnerability. In this review, the possible role of biological and immunological sex differences into the higher morbidity and mortality of SARS-CoV-2 between females and males are discussed.

Indexed as

COVID-19FemaleGenderIL-6SARS-CoV-2SexTLR7X chromosome

Identifiers

PMID32774170
PMCPMC7402393

What OpenQuestion holds

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Registered trials

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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.