ArticleFrontiers in cellular and infection microbiology2023
The distribution of hepatitis C viral genotypes shifted among chronic hepatitis C patients in Yunnan, China, between 2008-2018.
Article in Frontiers in cellular and infection microbiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed.
- Using Phylogenetic Analysis to Detect National and International Dimensions of Hepatitis C Virus 1b Transmission Clusters - China, 1989-2021.China CDC weekly · 2025Article
- Hepatitis C virus subtype diversity and transmission clusters characteristics among drug users in Zhuhai, South China.BMC infectious diseases · 2024Article
- AUTO-TUNE: SELECTING THE DISTANCE THRESHOLD FOR INFERRING HIV TRANSMISSION CLUSTERS.bioRxiv : the preprint server for biology · 2024Article
- AUTO-TUNE: selecting the distance threshold for inferring HIV transmission clusters.Frontiers in bioinformatics · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Object: The hepatitis C virus (HCV) is prevalent across China, with a distinctive genotypic distribution that varies by geographical region and mode of transmission. Yunnan is one such geographical region wherein the local population continues to experience a high level of HCV infection, severely straining public health resources. This high prevalence is likely due to the increased incidence of intravenous drug use in that region, as Yunnan is a major point of entry for illegal heroin into China. Methods: We investigated 510 individuals with chronic HCV infections in Yunnan Province from 2008 through 2018. Using reverse transcription PCR and Sanger sequencing to amplify and sequence samples. Bayesian analyses was performed to estimate the common ancestors and Bayesian skyline plot to estimate the effective viral population size. Molecular network was conducted to explore the characteristics of HCV transmission. Results: We successfully amplified and sequenced a total of 503 viral samples and genotyped each as either 3b (37.6%), 3a (21.9%), 1b (19.3%), 2a (10.5%), HCV-6 (10.1%), or 1a (0.6%). Over this 11-year period, we observed that the proportion of 3a and 3b subtypes markedly increased and, concomitantly, that the proportion of 1b and 2a subtypes decreased. We also performed Bayesian analyses to estimate the common ancestors of the four major subtypes, 1b, 2a, 3a, and 3b. Finally, we determined that our Bayesian skyline plot and transmission network data correlated well with the changes we observed in the proportions of HCV subtypes over time. Conclusions: Taken together, our results indicate that the prevalence of HCV 3a and 3b subtypes is rapidly increasing in Yunnan, thus demonstrating a steadily growing public health requirement to implement more stringent preventative and therapeutic measures to curb the spread of the virus.
Indexed as
Identifiers
What Socratic holds
Registered trials
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 Socratic graph.