Evidence map›Paper›PMID 39640283›Full record

SynthesisFrontiers in oncology2024

The correlation between vaginal pathogens and high-risk human papilloma virus infection: a meta-analysis of case-control studies.

Jun Yang, Xin Long, Sijing Li, Min Zhou, Li-Na Hu

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
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

7 citing papers in PubMed.

  1. Article
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  6. Review
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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.

Jun YangDepartment of Obstetrics and Gynecology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Xin LongDepartment of Obstetrics and Gynecology, Women and Children's Hospital of Chongqing Medical University, Chongqing, China.
Sijing LiDepartment of Obstetrics and Gynecology, Women and Children's Hospital of Chongqing Medical University, Chongqing, China.
Min ZhouDepartment of Obstetrics and Gynecology, Women and Children's Hospital of Chongqing Medical University, Chongqing, China.
Li-Na HuThe Center for Reproductive Medicine, Obstetrics and Gynecology Department, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Systematic study on the relationship between vaginal microbiota and high-risk human papillomavirus infection (HR-HPV) is limited. Hence, the aim of this study is to investigate the correlation between vaginal microbiota and HR-HPV infection through a meta-analysis of case-control studies. Methods: Chinese Journal Full-text database, Wanfang database, PubMed database, VIP Chinese Science and Technology Journal database, Web of Science, ScienceDirect, ProQuest, JSTOR, Wiley, and IEEE Xplore were synthetically searched for studies about the correlation between vaginal microbiota and HR-HPV infection. Revman 5.3 software was used to assess the relationship between vaginal microbiota and HPV infection through meta-analysis. Finally, forest map was used to calculate the results and funnel plot was applied to test the publication bias. Results: Fourteen independent studies were admitted in this study, containing a total of 21, 446 women in gynecological outpatients. Compared with HR-HPV negative group, the prevalence of bacterial vaginosis (BV) [odds ratio (OR)=2.45, 95% confidence intervals (CI): 1.83-3.27, Conclusions: Vaginal pathogens are closely related to HR-HPV infection. When BV, UU, and CT are abnormal, the risk of HR-HPV infection is increased.

Indexed as

bacterial vaginosisHR-HPVmeta-analysisvaginal infectionvaginal microbiotavaginal pathogens

Identifiers

PMID39640283
PMCPMC11618108

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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.