Evidence map›Paper›PMID 36536929›Full record

ReviewInternational journal of biomaterials2022

Comparative Analysis of the Efficiency of Medicinal Plants for the Treatment and Prevention of COVID-19.

Viktor Kamkin, Aidana Kamarova, Baurzhan Shalabayev, Assyltas Kussainov, Marat Anuarbekov, Serik Abeuov

Abstract readReview
In one paragraph

Review in International journal of biomaterials, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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.

Viktor KamkinDepartment of Agrotechnology, NJSC Toraighyrov University, Pavlodar 140008, Lomov 64 St, Kazakhstan.ORCID https://orcid.org/0000-0002-2618-2194
Aidana KamarovaDepartment of Biology and Ecology, NJSC Toraighyrov University, Pavlodar 140008, Lomov 64 St, Kazakhstan.ORCID https://orcid.org/0000-0003-0620-0620
Baurzhan ShalabayevDepartment of Agrotechnology, NJSC Toraighyrov University, Pavlodar 140008, Lomov 64 St, Kazakhstan.ORCID https://orcid.org/0000-0002-4551-0042
Assyltas KussainovDepartment of Biology and Ecology, NJSC Toraighyrov University, Pavlodar 140008, Lomov 64 St, Kazakhstan.ORCID https://orcid.org/0000-0002-9216-797X
Marat AnuarbekovLLP AlemAgro Holding, Pavlodar 140000, Lugovaya 16 St, Kazakhstan.ORCID https://orcid.org/0000-0002-7425-7445
Serik AbeuovDepartment of Agrotechnology, NJSC Toraighyrov University, Pavlodar 140008, Lomov 64 St, Kazakhstan.ORCID https://orcid.org/0000-0003-2634-5835

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic has once again prompted people to resort to the remedies of folk and alternative medicine. Medicinal plants, because of their chemical composition, pharmacological properties, and the action of biologically active substances, can stop and relieve the symptoms of the disease. The purpose of the work is a comparative flora analysis of medicinal plants to identify the most prospective plant and further production of a remedy for the avoidance, treatment, and rehabilitation of COVID-19. The search for prospective medicinal plants was performed by analyzing the literature in online databases: Web of Science, Scopus, Google Scholar, and PubMed, including official WHO media sites. According to recent studies related to COVID-19, a significant number of medicinal plants with anti-inflammatory, antiviral, and immunostimulatory effects have been identified. A comparative study of nine medicinal plants was conducted to determine the most suitable medicinal plant to treat coronavirus infection. According to the results of the comparative analysis,

Identifiers

PMID36536929
PMCPMC9759393

What OpenQuestion holds

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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.