Evidence map›Paper›PMID 34279825›Full record

ReviewAdvances in experimental medicine and biology2021

Genetic Aspects and Immune Responses in Covid-19: Important Organ Involvement.

Zari Naderi Ghale-Noie, Arash Salmaninejad, Robert Bergquist, Samaneh Mollazadeh, Benyamin Hoseini, Amirhossein Sahebkar

Abstract readReview
PubMed Publisher
In one paragraph

Review in Advances in experimental medicine and biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Comparison of Six Scoring Systems for Predicting In-hospital Mortality among Patients with SARS-COV2 Presenting to the Emergency Department.Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2023
    Article
  2. Article
  3. The role of HLA genotypes in understanding the pathogenesis of severe COVID-19.The Egyptian journal of medical human genetics · 2023
    Review
  4. Prediction of Patients with COVID-19 Requiring Intensive Care: A Cross-sectional Study Based on Machine-learning Approach from Iran.Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2022
    Article
  5. 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

6 authors.

Zari Naderi Ghale-NoieDepartment of Medical Genetics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
Arash SalmaninejadDepartment of Medical Genetics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
Robert BergquistFormerly UNICEF/UNDP/World Bank/WHO Special Programme for Research and Training in Tropical Diseases (TDR), World Health Organization, Geneva, Switzerland.
Samaneh MollazadehNatural Products and Medicinal Plants Research Center, North Khorasan University of Medical Sciences, Bojnurd, Iran.
Benyamin HoseiniPharmaceutical Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
Amirhossein SahebkarBiotechnology Research Center, Pharmaceutical Technology Institute, Mashhad University of Medical Sciences, Mashhad, Iran. amir_saheb2000@yahoo.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the last two decades, the world has experienced outbreaks of three major coronaviruses with high morbidity and mortality rates. The most recent of these started in the form of an unusual viral pneumonia in Wuhan, China, and now the world is facing a serious pandemic. This new disease has been called COVID-19 and is caused by the SARS-CoV-2 virus. Understanding the specific genetic and phenotypic structure of SARS-CoV-2 in COVID-19 pathogenesis is vital in finding appropriate drugs and vaccines. With this in mind, this review sheds light on the virology, genetics, immune-responses, and mechanism of action of this virus.

Indexed as

COVID-19Pneumonia, ViralChinaHumansImmunitySARS-CoV-22019-nCoVCovid-19GeneticsImmune-responsesRespiratorySARS-CoV-2

Identifiers

PMID34279825

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.