Evidence map›Paper›PMID 34204163›Full record

ReviewCells2021

Towards Goals to Refine Prophylactic and Therapeutic Strategies Against COVID-19 Linked to Aging and Metabolic Syndrome.

Chong-Hyun Shin, Ki-Hye Kim, Subbiah Jeeva, Sang-Moo Kang

Abstract readHistorical ArticleReview
In one paragraph

Review in Cells, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Role of autophagy in lung diseases and ageing.European respiratory review : an official journal of the European Respiratory Society · 2022
    Review
  3. Article
  4. Article
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.

Chong-Hyun ShinCenter for Inflammation, Immunity & Infection, Institute for Biomedical Sciences, Georgia State University, Atlanta, GA 30303, USA.ORCID 0000-0002-6385-5992
Ki-Hye KimCenter for Inflammation, Immunity & Infection, Institute for Biomedical Sciences, Georgia State University, Atlanta, GA 30303, USA.
Subbiah JeevaCenter for Inflammation, Immunity & Infection, Institute for Biomedical Sciences, Georgia State University, Atlanta, GA 30303, USA.
Sang-Moo KangCenter for Inflammation, Immunity & Infection, Institute for Biomedical Sciences, Georgia State University, Atlanta, GA 30303, USA.ORCID 0000-0001-6198-331X

Funding

NIH HHS AI093772
6 · The paper itself

Abstract

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) gave rise to the coronavirus disease 2019 (COVID-19) pandemic. A strong correlation has been demonstrated between worse COVID-19 outcomes, aging, and metabolic syndrome (MetS), which is primarily derived from obesity-induced systemic chronic low-grade inflammation with numerous complications, including type 2 diabetes mellitus (T2DM). The majority of COVID-19 deaths occurs in people over the age of 65. Individuals with MetS are inclined to manifest adverse disease consequences and mortality from COVID-19. In this review, we examine the prevalence and molecular mechanisms underlying enhanced risk of COVID-19 in elderly people and individuals with MetS. Subsequently, we discuss current progresses in treating COVID-19, including the development of new COVID-19 vaccines and antivirals, towards goals to elaborate prophylactic and therapeutic treatment options in this vulnerable population.

Indexed as

AgingChemopreventionCOVID-19History, 21st CenturyHumansMetabolic SyndromePatient Care PlanningPrevalencePrognosisSeverity of Illness IndexVulnerable PopulationsagingCOVID-19diabetesmetabolic syndromeobesitySARS-CoV-2therapeutic drugsvaccines

Identifiers

PMID34204163
PMCPMC8227274

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.