Evidence map›Paper›PMID 36561535›Full record

ReviewResearch and reports in tropical medicine2022

Development and Application of Treatment for Chikungunya Fever.

Erin M Millsapps, Emma C Underwood, Kelli L Barr

Open access · goldAbstract readReview
In one paragraph

Review in Research and reports in tropical medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
3.2field-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

9 citing papers in PubMed, 17 citations in OpenAlex.

  1. Article
  2. Review
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  5. Article
  6. Assessment of heat-killedFrontiers in immunology · 2024
    Article
  7. Article
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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

3 authors at 1 institution in 1 country.

Erin M MillsappsCenter for Global Health and Infectious Disease Research, University of South Florida, Tampa, FL, USA.ORCID 0000-0001-9060-6329
Emma C UnderwoodCenter for Global Health and Infectious Disease Research, University of South Florida, Tampa, FL, USA.
Kelli L BarrCenter for Global Health and Infectious Disease Research, University of South Florida, Tampa, FL, USA.ORCID 0000-0001-7943-7181
University of South Florida · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The development and application of treatment for Chikungunya fever (CHIKF) remains complicated as there is no current standard treatment and many barriers to research exist. Chikungunya virus (CHIKV) causes serious global health implications due to its socioeconomic impact and high morbidity rates. In research, treatment through natural and pharmaceutical techniques is being evaluated for their efficacy and effectiveness. Natural treatment options, such as homeopathy and physiotherapy, give patients a variety of options for how to best manage acute and chronic symptoms. Some of the most used pharmaceutical therapies for CHIKV include non-steroidal anti-inflammatory drugs (NSAIDS), methotrexate (MTX), chloroquine, and ribavirin. Currently, there is no commercially available vaccine for chikungunya, but vaccine development is crucial for this virus. Potential treatments need further research until they can become a standard part of treatment. The barriers to research for this complicated virus create challenges in the efficacy and equitability of its research. The rising need for increased research to fully understand chikungunya in order to develop more effective treatment options is vital in protecting endemic populations globally.

Indexed as

arthritisCHIKVnaturalpharmaceuticaltreatment

Identifiers

PMID36561535
PMCPMC9767026
OpenAlexW4311894467

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.