Evidence map›Paper›PMID 33055184›Full record

ArticleJournal of clinical microbiology2020

Diagnostic Accuracy of Four Commercial Triplex Immunochromatographic Tests for Rapid Detection of Rotavirus, Adenovirus, and Norovirus in Human Stool Samples.

Jérôme Kaplon, Lucie Théry, Maxime Bidalot, Nadège Grangier, Jean Frappier, Ludwig Serge Aho Glélé, Alexis de Rougemont, Katia Ambert-Balay

Open access · greenAbstract read
In one paragraph

Article in Journal of clinical microbiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.2field-weighted citation impact, top 34% 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

6 citing papers in PubMed, 18 citations in OpenAlex.

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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

8 authors at 3 institutions in 2 countries.

Jérôme KaplonNational Reference Center for Gastroenteritis Viruses, Laboratory of Biology and Pathology, University Hospital Dijon Bourgogne, Dijon, France jerome.kaplon@chu-dijon.fr.ORCID 0000-0002-8180-4152
Lucie ThéryNational Reference Center for Gastroenteritis Viruses, Laboratory of Biology and Pathology, University Hospital Dijon Bourgogne, Dijon, France.
Maxime BidalotNational Reference Center for Gastroenteritis Viruses, Laboratory of Biology and Pathology, University Hospital Dijon Bourgogne, Dijon, France.
Nadège GrangierNational Reference Center for Gastroenteritis Viruses, Laboratory of Biology and Pathology, University Hospital Dijon Bourgogne, Dijon, France.
Jean FrappierNational Reference Center for Gastroenteritis Viruses, Laboratory of Biology and Pathology, University Hospital Dijon Bourgogne, Dijon, France.
Ludwig Serge Aho GléléHospital Epidemiology and Infection Control Department, University Hospital Dijon Bourgogne, Dijon, France.
Alexis de RougemontNational Reference Center for Gastroenteritis Viruses, Laboratory of Biology and Pathology, University Hospital Dijon Bourgogne, Dijon, France.
Katia Ambert-BalayNational Reference Center for Gastroenteritis Viruses, Laboratory of Biology and Pathology, University Hospital Dijon Bourgogne, Dijon, France.
Laboratoire National de Référence · MAProcédés Alimentaires et Microbiologiques · FRCHU Dijon Bourgogne · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Noroviruses (NoV), rotaviruses (RVA), and adenoviruses (AdV) are the main viral agents responsible for acute gastroenteritis (AGE) in humans. We aimed to determine the diagnostic accuracy of four commercial immunochromatographic tests (ICTs) intended for the rapid and simultaneous detection of these three pathogens. Diagnostic accuracy of bioNexia Noro/Rota-Adeno (bioMérieux), Immunoquick NoRotAdeno (Biosynex), Rota+Adeno+Noro combo card (CerTest Biotec), and Rida Quick Rota/Adeno/Noro Combi (R-Biopharm) ICTs was assessed retrospectively using a collection of 160 stool specimens (including 43 RVA-, 47 AdV-, and 42 NoV-positive samples) from French patients with AGE and using molecular methods as the reference standard. For RVA, the four ICTs demonstrated similar high sensitivity (93%) and excellent specificity (97.4 to 100%). For AdV, the four ICTs demonstrated similar poor sensitivity (54.3 to 58.7%) but excellent specificity (95.5 to 100%). They performed the best in AdV-F species (sensitivity, 80.8 to 84.6%) and worst in AdV non-F species (sensitivity, 22.2 to 27.8%). For NoV, the Rida Quick Rota/Adeno/Noro combi ICT exhibited high sensitivity (87.5%), but the sensitivity of the three others was poor (42.5 to 47.5%). The four ICTs exhibited high specificity (96.6 to 99.1%). Diagnostic accuracy was genogroup dependent. When we tested genogroup I NoV, the Rida Quick Rota/Adeno/Noro Combi ICT presented high sensitivity (90%), while the three other ICTs presented poor sensitivity (10 to 30%); when we tested genogroup II NoV, sensitivity was similar for the four ICTs (65 to 85%). In conclusion, the four ICTs are suitable first-line tests for the rapid diagnosis of RVA infections. The four ICTs are not suitable for the routine diagnosis of AdV infections but could provide a rapid response in case of positivity, notably in the context of AGE. Only the Rida Quick Rota/Adeno/Noro Combi ICT is suitable for the rapid detection of NoV, while the sensitivity for the detection of genogroup I NoV needs to be improved for the 3 other ICTs before being implemented in the routine diagnosis of NoV.

Indexed as

NorovirusRotavirusRotavirus InfectionsAdenoviridaeFecesHumansRetrospective StudiesSensitivity and Specificityadenovirusenteric virusesgastroenteritisimmunochromatographynorovirusrotavirussensitivity and specificity

Identifiers

PMID33055184
PMCPMC7771454
OpenAlexW3093442694

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.