Evidence map›Paper›PMID 37505661›Full record

ReviewTropical medicine and infectious disease2023

Chikungunya Virus Diagnosis: A Review of Current Antigen Detection Methods.

Fredy Brice Nemg Simo, Felicity Jane Burt, Nigel Aminake Makoah

Open access · goldAbstract readReview
In one paragraph

Review in Tropical medicine and infectious disease, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
5.5field-weighted citation impact, top 4% 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

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.

  1. Pooled it
  2. Review
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  5. Review
  6. Review
  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 2 institutions in 1 country.

Fredy Brice Nemg SimoDivision of Virology, Faculty of Health Sciences, University of The Free State, Bloemfontein 9301, Free State, South Africa.
Felicity Jane BurtDivision of Virology, Faculty of Health Sciences, University of The Free State, Bloemfontein 9301, Free State, South Africa.ORCID 0000-0002-7238-7799
Nigel Aminake MakoahDivision of Virology, Faculty of Health Sciences, University of The Free State, Bloemfontein 9301, Free State, South Africa.
University of the Free State · ZANational Health Laboratory Service · ZA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chikungunya is a mosquito-borne viral disease caused by the chikungunya virus (CHIKV). CHIKV is expanding at an alarming rate, potentially spreading and establishing endemicity in new areas where competent vectors are present. The dramatic spread of CHIKV in recent years highlights the urgent need to take precautionary measures and investigate options for control. It is crucial in developing nations where diagnostic tools are limited, and symptoms are similar to other prevalent diseases such as malaria and dengue. The most reliable method for diagnosing chikungunya virus is viral gene detection by RT-PCR. Alternative methods like detecting human antibody and viral antigen can also be used, especially in areas where resources are limited. In this review, we summarize the limited data on antigen detection immunoassays. We further explain the essential structural elements of the virus to help comprehend the scientific concepts underlying the testing methods, as well as future methods and diagnostic approaches under investigation.

Indexed as

chikungunya antigen detectionchikungunya virusdiagnosisenzyme linked immunosorbent assaylateral flow assay

Identifiers

PMID37505661
PMCPMC10383795
OpenAlexW4384525234

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.