Evidence map›Paper›PMID 37641157›Full record

ArticleParasites & vectors2023

Diagnostic performance of Strongyloides-specific IgG4 detection in urine for diagnosis of human strongyloidiasis.

Phattharaphon Wongphutorn, Chanika Worasith, Kulthida Y Kopolrat, Chutima Homwong, Jiraporn Sithithaworn, Chatanun Eamudomkarn, Anchalee Techasen, Patcharaporn Tippayawat, Opal Pitaksakurat, Nuttanan Hongsrichan and 2 more

Open access · goldAbstract read
In one paragraph

Article in Parasites & vectors, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.2field-weighted citation impact, top 14% 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

4 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Partially purifiedMicrobiology spectrum · 2025
    Article
  3. Article
  4. Strongyloidiasis.Nature reviews. Disease primers · 2024
    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

12 authors at 3 institutions in 2 countries.

Phattharaphon WongphutornBiomedical Science Program, Graduate School, Khon Kaen University, Khon Kaen, Thailand.
Chanika WorasithDepartment of Adult Nursing, Faculty of Nursing, Khon Kaen University, Khon Kaen, Thailand.
Kulthida Y KopolratFaculty of Public Health, Kasetsart University Chalermphrakiat Sakon Nakhon Province Campus, Sakon Nakhon, Thailand.
Chutima HomwongCholangiocarcinoma Research Institute, Khon Kaen University, Khon Kaen, Thailand.
Jiraporn SithithawornFaculty of Associated Medical Sciences, Khon Kaen University, Khon Kaen, Thailand.
Chatanun EamudomkarnDepartment of Parasitology, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand.
Anchalee TechasenFaculty of Associated Medical Sciences, Khon Kaen University, Khon Kaen, Thailand.
Patcharaporn TippayawatFaculty of Associated Medical Sciences, Khon Kaen University, Khon Kaen, Thailand.
Opal PitaksakuratDepartment of Parasitology, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand.
Nuttanan HongsrichanDepartment of Parasitology, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand.
Thomas CrellenSchool of Biodiversity One Health and Veterinary Medicine, University of Glasgow, Graham Kerr Building, Glasgow, UK.
Paiboon SithithawornCholangiocarcinoma Research Institute, Khon Kaen University, Khon Kaen, Thailand. paib_sit@kku.ac.th.
Khon Kaen University · THSakon Nakhon Rajabhat University · THWellcome Centre for Molecular Parasitology · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDetection of parasite-specific IgG in urine is a sensitive method for diagnosis of strongyloidiasis and gives similar accuracy to serum IgG. However, there are no data concerning detection of IgG subclass in urine. To further explore the utility of diagnosis from urine samples, we evaluated the diagnostic performance of IgG4 in urine compared with parasitological and other immunological methods.

methodsThe urine and sera included proven strongyloidiasis (group 1, n = 93), other parasitic infections (group 2, n = 40) and parasite negatives (group 3, n = 93). The performance of Strongyloides-specific IgG4 in urine for diagnosis of strongyloidiasis using fecal examinations as the reference standard was assessed.

resultsWith fecal examination as a gold standard, Strongyloides-specific IgG4 in urine had 91.4% sensitivity and 93.2% specificity while serum IgG4 had 93.6% sensitivity and 91.0% specificity. IgG4 in both urine and serum had almost perfect diagnostic agreements with fecal examination (Cohen's kappa coefficient was > 0.8). Cross-reactivity to Opisthorchis viverrini and Taenia spp. of IgG4 in urine were 7.5% and 12.5% in serum. Concurrent analyses of total IgG in urine and serum showed that the sensitivities (97.9-100%) and specificities (88.7-91.0%) were similar (P > 0.05). The sensitivity for parasitological examination by the formalin-ethyl acetate concentration technique (FECT) was 49.5% and that for agar plate culture technique (APC) it was 92.6%.

conclusionOur findings showed that specific IgG4 detection in urine yielded similar diagnostic performance to the same biomarkers in serum. This suggests that accurate diagnosis of strongyloidiasis can be performed using urine samples and IgG4 is a valid choice of diagnostic marker. Further assessment is required to assess the utility of urine IgG4 for measuring the response treatment in strongyloidiasis.

Indexed as

Body FluidsStrongyloidiasisAnimalsCross ReactionsHumansImmunoglobulin GStrongyloidesImmunoglobulin GEnzyme-linked immunosorbent assay (ELISA)Immunoglobulin G4Strongyloides stercoralis

Identifiers

PMID37641157
PMCPMC10464225
OpenAlexW4386223668

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.