Evidence map›Paper›PMID 20222172›Full record

ArticleWorld journal of gastroenterology2010

Establishment of a new quantitative detection approach to adefovir-resistant HBV and its clinical application.

Wei-Feng Zhao, You-Lin Shao, Liang-Yun Chen, Jin-Hua Wu, Yi-Ling Zhu, Jian-He Gan, Hui Xiong

Open access · hybridAbstract read
In one paragraph

Article in World journal of gastroenterology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 41% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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

7 authors at 1 institution in 1 country.

Wei-Feng ZhaoShanghai Laboratory of Disease and Health Genomics, Chinese National Human Genome Center, Shanghai 201203, China.
You-Lin Shao
Liang-Yun Chen
Jin-Hua Wu
Yi-Ling Zhu
Jian-He Gan
Hui Xiong
Chinese National Human Genome Center · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimTo establish the more feasible and sensitive assessment approach to the detection of adefovir (ADV) resistance-associated hepatitis B virus (HBV) quasispecies.

methodsBased on the characteristics of rtA181V/T and rtN236T mutations, a new approach based on real-time fluorescent quantitative polymerase chain reaction (RT-PCR) was established for the detection of ADV-resistant HBV quasispecies, total HBV DNA, rtA181 and rtN236 mutations in blood samples from 32 chronic hepatitis B (CHB) patients with unsatisfactory curative effect on ADV and compared with routine HBV DNA sequencing.

resultsBoth the sensitivity and specificity of this new detection approach to ADV-resistant HBV quasispecies were 100%, which were much higher than those of direct HBV DNA sequencing. The approach was able to detect 0.1% of mutated strains in a total plasmid population. Among the 32 clinical patients, single rtA181 and rtN236T mutation and double rtA181T and rtN236T mutations were detected in 20 and 8, respectively, while ADV-resistant mutations in 6 (including, rtA181V/T mutation alone in 5 patients) and no associated mutations in 26.

conclusionThis new approach is more feasible and efficient to detect ADV-resistant mutants of HBV and ADV-resistant mutations before and during ADV treatment with a specificity of 100% and a sensitivity of 100%.

Indexed as

Antiviral AgentsDrug Resistance, ViralOrganophosphonatesAdenineAdultDNA, ViralFemaleHepatitis B, ChronicHepatitis B virusHumansMaleMiddle AgedMutationPolymerase Chain ReactionSensitivity and SpecificitySequence Analysis, DNAadefovirAdenineAntiviral AgentsDNA, ViralOrganophosphonates

Identifiers

PMID20222172
PMCPMC2839181
OpenAlexW1988061256

What OpenQuestion holds

Textmetadata
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Registered trials

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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.