Evidence map›Paper›PMID 40624568›Full record

ArticleVirology journal2025

Epidemiological characteristics and genotype distribution of human papillomavirus infection in Yangpu district, Shanghai, 2020-2024.

Zien Cheng, Yu Zhao, Ting Xu, Liting Wu, Hongdan Zhao, Jia Li

Abstract read
In one paragraph

Article in Virology journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Zien Cheng *Medical Laboratory, Shidong Hospital Affiliated to University of Shanghai for Science and Technology, Shanghai, 200438, China.
Yu Zhao *Medical Laboratory, Shidong Hospital Affiliated to University of Shanghai for Science and Technology, Shanghai, 200438, China.
Ting XuMedical Laboratory, Shidong Hospital Affiliated to University of Shanghai for Science and Technology, Shanghai, 200438, China.
Liting WuMedical Laboratory, Shidong Hospital Affiliated to University of Shanghai for Science and Technology, Shanghai, 200438, China.
Hongdan ZhaoMedical Laboratory, Shidong Hospital Affiliated to University of Shanghai for Science and Technology, Shanghai, 200438, China.
Jia LiMedical Laboratory, Shidong Hospital Affiliated to University of Shanghai for Science and Technology, Shanghai, 200438, China. 1124lijia@163.com.

Funding

Hospital-level Project of Shanghai Yangpu District Shidong Hospital YJYB2Sub-project of Medical Service and Security Capacity Improvement Project Z155080000004-05Yangpu District Dual-Commission Project YPQ202414, YPM202314Yangpu District Key Discipline Project 22YPZB03
6 · The paper itself

Abstract

objectiveTo analyze the positive rate and genotype distribution of human papillomavirus (HPV) infection in Yangpu District, Shanghai, and to provide a scientific basis for the prevention and treatment of cervical cancer and related diseases.

methodsA retrospective analysis was conducted on HPV genotyping data from 19,142 outpatients, inpatients, and health examinees at Shanghai Shidong Hospital from 2020 to 2024. Overall infection rate, genotype distribution, age-specific positivity, and annual trends were evaluated.

resultsAmong 19,142 specimens, 4,421 tested positive for HPV, yielding a total positive rate of 23.10%. The top five prevalent genotypes were HPV-52 (21.72%), HPV-53 (11.94%), HPV-58 (10.19%), HPV-51 (8.02%), and HPV-39 (6.86%). Dominant genotypes varied across years. Age-specific infection rates followed an approximate U-shaped curve, with peaks in the ≤ 20-year group (57.69%) and the 61-70-year group (29.72%). Among mixed infections (28.70% of positives), single infections predominated (71.30%). The most common co-infection combinations were HPV-52 + HPV-53 and HPV-52 + HPV-58. High-risk age groups for HPV infection were 31-40, 51-60, and 61-70 years.

conclusionThe HPV infection rate in Yangpu District, Shanghai, was 23.10%, primarily driven by single-genotype infections. HPV-52, -53, and - 58 were the dominant genotypes, with significant age-specific variations. These findings underscore the need for enhanced HPV vaccination promotion and targeted preventive strategies.

Indexed as

GenotypePapillomaviridaePapillomavirus InfectionsAdolescentAdultAgedAged, 80 and overChildChinaCoinfectionFemaleHumansMiddle AgedPrevalenceRetrospective StudiesYoung AdultEpidemiologyGenotypeHuman papillomavirusInfection rate

Identifiers

PMID40624568
PMCPMC12232720

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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.