Evidence map›Paper›PMID 29911153›Full record

ArticleVirusdisease2018

Comparison of a rapid immuno-chromatography assay with a standard ELISA for the detection of IgM and IgG antibodies against dengue viruses.

Kalamathy Murugananthan, Pethirupillai A D Coonghe, Natkunam Ketheesan, Faseeha Noordeen

Open access · greenAbstract read
In one paragraph

Article in Virusdisease, 2018. 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
0.5field-weighted citation impact, top 30% 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, 7 citations in OpenAlex.

  1. Article
  2. Article
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  4. Observational
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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

4 authors at 3 institutions in 2 countries.

Kalamathy Murugananthan1Department of Microbiology, Faculty of Medicine, University of Jaffna, Jaffna, Sri Lanka.
Pethirupillai A D Coonghe2Community and Family Medicine, Faculty of Medicine, University of Jaffna, Jaffna, Sri Lanka.
Natkunam Ketheesan3College of Public Health, Medical and Veterinary Sciences, James Cook University, Townsville, QLD Australia.
Faseeha Noordeen5Department of Microbiology, Faculty of Medicine, University of Peradeniya, Peradeniya, Sri Lanka.
University of Jaffna · LKJames Cook University · AUUniversity of Peradeniya · LK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A total of 765 blood samples collected from dengue suspected patients admitted to a Teaching Hospital in Sri Lanka were used to compare a rapid ICT assay with a standard ELISA for the detection of anti-dengue virus (DENV) IgM and IgG. Detection accuracy indices including sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), Chi square and Cohen's kappa values were determined for the ICT assay using the ELISA as a comparator for the detection of anti-DENV IgM and IgG. The rapid ICT assay showed a sensitivity of 64%, specificity of 75%, NPV of 68% and PPV of 72% for anti-DENV IgM detection. However, all the accuracy indices were relatively higher for the anti-DENV IgG detection by the ICT assay than those for anti-DENV IgM detection. Despite the low sensitivity for anti-DENV IgM detection by the ICT assay, considering the limitations in using ELISAs in resource limited regions, rapid ICT assays would be useful for the detection of more recent DENV infections. As many patients present after fever days 5 in the study area, anti-DENV IgM/IgG would be the suitable marker to be detected by rapid ICT assays in such areas.

Indexed as

Anti-DENV IgM/IgGDengueELISARapid immuno-chromatography assays

Identifiers

PMID29911153
PMCPMC6003062
OpenAlexW2800495034

What OpenQuestion holds

Textmetadata
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.