Evidence map›Paper›PMID 14715747›Full record

ArticleJournal of clinical microbiology2004

Hepatitis C genotyping by denaturing high-performance liquid chromatography.

Michael Liew, Maria Erali, Sam Page, David Hillyard, Carl Wittwer

Open access · greenAbstract read
In one paragraph

Article in Journal of clinical microbiology, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
0.8field-weighted citation impact, top 26% 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

13 citing papers in PubMed, 30 citations in OpenAlex.

  1. Review
  2. [Distribution of HCV genotypes in Chinese Han population with chronic hepatitis C].Zhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences · 2015
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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

5 authors at 2 institutions in 1 country.

Michael LiewInstitute for Clinical and Experimental Pathology, ARUP Laboratories, Salt Lake City, Utah 84108-122, USA. liewm@aruplab.com
Maria Erali
Sam Page
David Hillyard
Carl Wittwer
ARUP Laboratories (United States) · USUniversity of Utah · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Determination of the hepatitis C virus (HCV) genotype for infected patients increasingly has become accepted as the standard of care. Genotype assignment helps in assessing disease prognosis and assists in establishing the appropriate duration of treatment. The great genetic diversity of HCV, with 11 major genotypes and >70 subtypes, contributes to the technical difficulty of genotype testing. While the "gold standard" for testing is nucleic acid sequencing, a variety of hybridization assays, including the line probe assay, have been developed to provide more rapid and accessible forms of testing. The aim of this study was to determine whether denaturing high-performance liquid chromatography (dHPLC) could be used as a clinical method for distinguishing HCV genotypes 1, 2, 3, and 4. A portion of the 5' untranslated region of the HCV genome was amplified by heminested multiplex reverse transcription PCR. The two amplicons then were analyzed by dHPLC analysis and compared to the genotypes determined by sequence analysis. After 115 specimens were analyzed as standards, 200 masked specimens (specimens whose identity was not known before testing) were analyzed to determine the concordance of the assay. The assay had a concordance of 96% at the genotype level and a concordance of 87% at the subtype level. However, the dHPLC method was not as accurate as other reported methods of HCV genotyping. This is the first time that HCV genotyping has been performed by dHPLC.

Indexed as

5' Untranslated RegionsBase SequenceChromatography, High Pressure LiquidGenotypeHepacivirusMolecular Sequence Data5' Untranslated Regions

Identifiers

PMID14715747
PMCPMC321670
OpenAlexW2137336792

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.