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Cited by 29Viral Infections and Immunology ResearchInfectious Encephalopathies and EncephalitisMolecular Biology Techniques and Applications

The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.

Improved diagnosis on a daily basis of enterovirus meningitis using a one‐step real‐time RT‐PCR assay

Abstract

The detection of the enterovirus genome in cerebrospinal fluid (CSF) by PCR techniques has proved to be more sensitive than traditional cell culture for the diagnosis of enterovirus meningitis. However, PCR assays are time consuming and labor intensive, particularly if separate hybridization steps are used to confirm the specificity of positive findings. The aim of this study was to develop a one‐step real‐time RT‐PCR assay with LightCycler (LC) technology that was sensitive, rapid, and easy to perform in routine practice. The enterovirus detection limit was determined by testing 10‐fold limiting dilution series of cell culture stocks with the echovirus 25 (E‐25) prototype strain and with the third European Union Quality Control Concerted Action (EU‐QCCA) enterovirus proficiency panel. A total of 100 CSF specimens were investigated in a comparative study. With the E‐25 strain, the detection limit of the real‐time assay was 286 TCID 50/ml (50% tissue culture infective dose). When samples of the EU‐QCCA panel were tested, our assay gave identical results (detection limit down to 3.6 TCID 50/ml) to those of the reference laboratory, which used one‐step RT‐PCR assay. When CSF specimens were tested, there was a correlation between the real‐time assay and the conventional in‐house assay in 96 of 100 CSFs tested. This one‐step real‐time assay allows rapid enterovirus detection in CSF since results are obtained in 3 hr as against 36 hr with the “in‐house” RT‐PCR assay. This new assay is now being used in routine practice, and allows diagnosis on a daily basis. J. Med. Virol. 74:604–611, 2004. © 2004 Wiley‐Liss, Inc.

Overview

Integrity signals

Registry

Crossref · 10.1002/jmv.20217

Cites

26 of 26 references verified0 citation errors · 0 not checkable

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Citations

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Metadata

Authors
Archimbaud, C., Mirand, A., Chambon, M., Regagnon, C., Bailly, J., Peigue‐Lafeuille, H., & Henquell, C.
Affiliations
Centre Hospitalier Universitaire de Clermont-Ferrand (FR)
Corresponding author
Archimbaud, Christine
Venue
Journal of Medical Virology
Publisher
Wiley
Published
2004-10-13
Volume
74
Issue
4
Pages
604-611
ISSN
  • 0146-6615 (ISSN-L)
  • 1096-9071
OpenAlex
W2125092867
Cited by
28
References
26
Citations by year
2024: 1 · 2023: 1 · 2021: 1 · 2018: 1 · 2017: 1 · 2013: 5 · 2012: 1
FWCI
2.86
Type
journal article
Language
en
Open access
closed
Locations
  • Journal of Medical Virology (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Medicine › Infectious Diseases › Viral Infections and Immunology Research
  • Health Sciences › Medicine › Infectious Diseases › Infectious Encephalopathies and Encephalitis
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Molecular Biology Techniques and Applications
Keywords
enterovirus meningitis, enterovirus detection, cerebrospinal fluid, LightCycler, detection limit, rapid diagnosis
MeSH terms
Cerebrospinal Fluid, Enterovirus Infections, Enterovirus, Humans, Meningitis, Viral, RNA, Viral, Sensitivity and Specificity, Time Factors, Polymerase Chain Reaction

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.