Evidence map›Paper›PMID 33294461›Full record

ReviewJournal of diabetes research2020

The Impact of Diabetes Mellitus in COVID-19: A Mechanistic Review of Molecular Interactions.

Habib Yaribeygi, Thozhukat Sathyapalan, Tannaz Jamialahmadi, Amirhossein Sahebkar

Open access · goldAbstract readReview
In one paragraph

Review in Journal of diabetes research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
0.7field-weighted citation impact, top 18% 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

10 citing papers in PubMed, 27 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Observational
  6. Role of microRNAs in COVID-19 with implications for therapeutics.Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie · 2021
    Review
  7. Article
  8. Review
  9. Review
  10. 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

4 authors at 3 institutions in 2 countries.

Habib YaribeygiResearch Center of Physiology, Semnan University of Medical Sciences, Semnan, Iran.ORCID https://orcid.org/0000-0002-1706-6212
Thozhukat SathyapalanAcademic Diabetes, Endocrinology and Metabolism, Hull York Medical School, University of Hull, UK.
Tannaz JamialahmadiDepartment of Food Science and Technology, Quchan Branch, Islamic Azad University, Quchan, Iran.
Amirhossein SahebkarBiotechnology Research Center, Pharmaceutical Technology Institute, Mashhad University of Medical Sciences, Mashhad 9177948564, Iran.ORCID https://orcid.org/0000-0002-8656-1444
Mashhad University of Medical Sciences · IRSemnan University of Medical Sciences · IRUniversity of Hull · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ongoing pandemic of COVID-19 is now the major issue in global health. Evidence implies that patients with diabetes are at a higher risk of severe disease or death due to COVID-19 than individuals without diabetes. However, the underlying mechanism for this differential effect in individuals with and without diabetes is not clearly understood. We have reviewed the pathophysiological pathways which may facilitate the entry of virus or an increase in its infectivity in host cells in the diabetic milieu. We suggest that the preexisting pathological pathways in patients with poorly controlled diabetes increase the risk of infectivity and are responsible for the higher levels of tissue injury and death in patients with diabetes.

Indexed as

SARS-CoV-2ApoptosisBlood GlucoseComorbidityCOVID-19Diabetes MellitusHumansInflammationOxidative StressRenin-Angiotensin SystemBlood Glucose

Identifiers

PMID33294461
PMCPMC7691013
OpenAlexW3102838795

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.