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Hepatitis C Virus in mainland China with an emphasis on genotype and subtype distribution

Overview of attention for article published in Virology Journal, February 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

news
1 news outlet
twitter
1 tweeter
facebook
1 Facebook page

Citations

dimensions_citation
27 Dimensions

Readers on

mendeley
15 Mendeley
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Title
Hepatitis C Virus in mainland China with an emphasis on genotype and subtype distribution
Published in
Virology Journal, February 2017
DOI 10.1186/s12985-017-0710-z
Pubmed ID
Authors

Yu Zhang, Li-Min Chen, Miao He

Abstract

Due to the low fidelity of the RNA-dependent RNA polymerase, Hepatitis C virus (HCV) mutates quite frequently. There are seven genetically divergent genotypes (GTs) distributed in the world, each of which contains several closely related subtypes. The peer-reviewed literatures reporting the prevalence rate of HCV GTs in Chinese hospitalized patients were identified by systematic searching of three electronic databases, and the prevalence rates were pooled through 137 qualified studies. The significant difference between HCV GT and HCV viral load and severity of hepatitis were analyzed under Chi-squared or Fisher's exact test. Data from epidemiological studies on hospitalized patients demonstrated that HCV GTs 1-6 have been found in China, of which 1b (62.78%(95% CI: 59.54-66.02%)) and 2a (17.39% (95% CI: 15.67-19.11%)) are the two predominant subtypes. HCV GTs and subtypes exhibits significant regional divergence. In North, Northwest, Northeast, East (except Jiangxi province) and Central China (except Hunan province), HCV-1b, 2a remain the two predominant subtypes; South China shows the most abundant genetic diversity that 14 subtypes were found, and HCV-3 in the Southwest China remains higher prevalent subtype than the other regions. In addition, co-infection in Liaoning province of Northeast China is the most diverse with 10 co-infection types, and Tibet has the highest rate of co-infection. The associations between HCV GTs and patients group, severity of illness and antiviral treatment efficacy were also discussed in this review.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 20%
Other 2 13%
Student > Bachelor 2 13%
Researcher 2 13%
Student > Postgraduate 2 13%
Other 2 13%
Unknown 2 13%
Readers by discipline Count As %
Medicine and Dentistry 6 40%
Social Sciences 2 13%
Immunology and Microbiology 1 7%
Agricultural and Biological Sciences 1 7%
Biochemistry, Genetics and Molecular Biology 1 7%
Other 1 7%
Unknown 3 20%

Attention Score in Context

This research output has an Altmetric Attention Score of 10. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 December 2017.
All research outputs
#1,319,418
of 12,231,187 outputs
Outputs from Virology Journal
#114
of 2,064 outputs
Outputs of similar age
#46,310
of 259,569 outputs
Outputs of similar age from Virology Journal
#3
of 60 outputs
Altmetric has tracked 12,231,187 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,064 research outputs from this source. They receive a mean Attention Score of 3.5. This one has done particularly well, scoring higher than 94% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 259,569 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 60 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.