Evidence map›Paper›PMID 34373739›Full record

ReviewTheranostics2021

Obesity and severe coronavirus disease 2019: molecular mechanisms, paths forward, and therapeutic opportunities.

Tiantian Yan, Rong Xiao, Nannan Wang, Ruoyu Shang, Guoan Lin

Open access · goldAbstract readReview
In one paragraph

Review in Theranostics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
2.2field-weighted citation impact, top 10% 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

17 citing papers in PubMed, 1 synthesis or guideline pooled it, 33 citations in OpenAlex.

  1. Use of steroids in COVID-19 patients: A meta-analysis.European journal of pharmacology · 2022
    Pooled it
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Review
  10. Article
  11. Molecular and pro-inflammatory aspects of COVID-19: The impact on cardiometabolic health.Biochimica et biophysica acta. Molecular basis of disease · 2022
    Review
  12. Obesity and Coronavirus Disease 2019.Journal of translational internal medicine · 2022
    Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. 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

5 authors at 1 institution in 1 country.

Tiantian YanMilitary Burn Center, the 990th Hospital of People's Liberation Army Joint Logistics Support Force, Zhumadian, Henan, China.
Rong XiaoMilitary Burn Center, the 990th Hospital of People's Liberation Army Joint Logistics Support Force, Zhumadian, Henan, China.
Nannan WangMilitary Burn Center, the 990th Hospital of People's Liberation Army Joint Logistics Support Force, Zhumadian, Henan, China.
Ruoyu ShangState Key Laboratory of Trauma, Burns, and Combined Injury, Institute of Burn Research, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing Key Laboratory for Disease Proteomics, Chongqing, China.
Guoan LinMilitary Burn Center, the 990th Hospital of People's Liberation Army Joint Logistics Support Force, Zhumadian, Henan, China.
Army Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) appears to have higher pathogenicity among patients with obesity. Obesity, termed as body mass index greater than 30 kg/m

Indexed as

COVID-19Immunity, InnatePandemicsAnimalsComorbidityHumansObesitySeverity of Illness IndexCoronavirus disease 2019ImmunityInflammationMetabolismObesityThrombosis

Identifiers

PMID34373739
PMCPMC8343994
OpenAlexW3184443043

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.