Evidence map›Paper›PMID 37366526›Full record

ReviewHeliyon2023

Plausibility of natural immunomodulators in the treatment of COVID-19-A comprehensive analysis and future recommendations.

Raushanara Akter, Md Rashidur Rahman, Zainab Syed Ahmed, Afrina Afrose

Open access · goldAbstract readReview
In one paragraph

Review in Heliyon, 2023. 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
3.6field-weighted citation impact, top 8% 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

5 citing papers in PubMed, 9 citations in OpenAlex.

  1. Review
  2. Review
  3. Exploring the Medicinal and Nutraceutical Frontiers ofCurrent topics in medicinal chemistry · 2025
    Review
  4. Review
  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

4 authors at 1 institution in 1 country.

Raushanara AkterSchool of Pharmacy, Brac University, 66 Mohakhali, Dhaka, Bangladesh.
Md Rashidur RahmanDepartment of Pharmacy, Faculty of Biological Science and Technology, Jashore University of Science and Technology, Jashore, 7408, Bangladesh.
Zainab Syed AhmedSchool of Pharmacy, Brac University, 66 Mohakhali, Dhaka, Bangladesh.
Afrina AfroseSchool of Pharmacy, Brac University, 66 Mohakhali, Dhaka, Bangladesh.
BRAC University · BD

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic has inflicted millions of deaths worldwide. Despite the availability of several vaccines and some special drugs approved for emergency use to prevent or treat this disease still, there is a huge concern regarding their effectiveness, adverse effects, and most importantly, their efficacy against the new variants. A cascade of immune-inflammatory responses is involved with the pathogenesis and severe complications with COVID-19. People with dysfunctional and compromised immune systems display severe complications, including acute respiratory distress syndrome, sepsis, multiple organ failure etc., when they get infected with the SARS-CoV-2 virus. Plant-derived natural immune-suppressant compounds, such as resveratrol, quercetin, curcumin, berberine, luteolin, etc., have been reported to inhibit pro-inflammatory cytokines and chemokines. Therefore, natural products with immunomodulatory and anti-inflammatory potential could be plausible targets to treat this contagious disease. This review aims to delineate the clinical trials status and outcomes of natural compounds with immunomodulatory potential in COVID-19 patients along with the outcomes of their

Indexed as

COVID-19CytokinesImmunomodulatorsNatural compoundsPandemicSARS-CoV-2

Identifiers

PMID37366526
PMCPMC10284624
OpenAlexW4381550851

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.