Evidence map›Paper›PMID 39493661›Full record

ArticleInternational journal of women's health2024

Cross-Sectional Study on the Correlation Between Vaginal Microecology and High-Risk Human Papillomavirus Infection: Establishment of a Clinical Prediction Model.

Hua-Mei Liu, Fan Zhang, Heng-Yun Cai, Yu-Mei Lv, Meng-Yuan Pi

Abstract read
In one paragraph

Article in International journal of women's health, 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.

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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.

Hua-Mei LiuDepartment of Gynecology and Obstetrics, Xiangyang Hospital of Integrated Chinese and Western Medicine, Xiangyang, Hubei, 441004, People's Republic of China.
Fan ZhangDepartment of Gynecology and Obstetrics, Xiangyang Hospital of Integrated Chinese and Western Medicine, Xiangyang, Hubei, 441004, People's Republic of China.
Heng-Yun CaiDepartment of Gynecology and Obstetrics, Xiangyang Hospital of Integrated Chinese and Western Medicine, Xiangyang, Hubei, 441004, People's Republic of China.
Yu-Mei LvDepartment of Clinical Laboratory, Xiangyang Hospital of Integrated Chinese and Western Medicine, Xiangyang, Hubei, 441004, People's Republic of China.
Meng-Yuan PiDepartment of Gynecology and Obstetrics, Xiangyang Hospital of Integrated Chinese and Western Medicine, Xiangyang, Hubei, 441004, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: High-risk human papillomavirus (HR-HPV) is a significant risk factor for cervical precancerous lesions and cancer. This study aimed to investigate the relationship between vaginal microecology and HR-HPV infection and to evaluate the clinical applicability of vaginal microecology in predicting HR-HPV infection. Patients and Methods: Overall, 2000 women with simultaneously detected vaginal discharge and cervical HPV were selected between March 2022 and March 2023, including 241 and 1759 cases in the HR-HPV positive and HPV negative groups, respectively. Results: No significant differences were found in age, vulvovaginal candidiasis, trichomonas vaginitis, and β-N-acetylglucosaminosidase between the two groups (P>0.05). Significant differences were observed in Conclusion: Overall, vaginal microecology imbalance was closely associated with cervical HR-HPV infection, particularly BV and AV. The logistic regression model for the risk of HR-HPV infection based on six predictive factors (BV, AV, LE, SNA,

Indexed as

decision treehigh-risk human papillomaviruslogistic regressionrandom forestvaginal microecology

Identifiers

PMID39493661
PMCPMC11531725

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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.