ArticleBMC infectious diseases2026
HPV genotype distribution and risk factors for cervical dysplasia among HPV-positive women with or without HIV infection in Shanghai, China.
Article in BMC infectious diseases, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
backgroundHuman papillomavirus (HPV) and human immunodeficiency virus (HIV) co-infection exerts a substantial impact on women's health globally. This study enrolled confirmed HPV-infected women in Shanghai stratified by HIV status to compare the profiles of HPV genotype distribution and cervical lesions between two groups, and to identify the risk factors for cervical dysplasia among women with HIV-HPV co-infection.
methodsA total of 238 confirmed HPV-infected women who attended the Shanghai Public Health Clinical Center between January 2019 and July 2023 were enrolled in this cross-sectional study. All participants were divided into HIV-positive and HIV-negative groups. We compared the pathological distribution characteristics, high/low-risk HPV infection patterns and cervical cytological abnormalities between the two groups. Multivariate logistic regression was used to explore risk factors for cervical dysplasia in HIV-HPV co-infected women.
resultsAmong the 238 HPV-positive patients, 47.9% (114/238) were HIV-HPV co-infected. The top five predominant HPV genotypes were HPV16, HPV52, HPV58, HPV53, and HPV18. The HIV-positive group had significantly higher rates of HR-HPV infection (χ²=4.537, p = 0.037) and multiple HR-HPV infections (χ²=15.878, p < 0.001) than the HIV-negative group. HPV33 and HPV66 were more prevalent in the HIV-positive group, and the positivity rates of HPV genotypes covered by 2-valent, 4-valent, and 9-valent HPV vaccines were all significantly higher in the HIV-positive group than in the HIV-negative group. HPV52 and HPV58 (13.10%, 11/84) were the most common genotypes in multiple HPV infections. The HIV-positive group had a significantly higher rate of cytological abnormalities (χ²=11.658, p < 0.001). Multivariate logistic regression analysis indicated that HIV RNA load > 1000 copies/µl was an independent risk factor (OR 9.845, 95%CI 1.324-73.202, p = 0.026) for cervical dysplasia in the HIV-positive group.
conclusionsWithin the HPV-positive female population, HIV-positive women exhibit higher burdens of multiple HPV infection and cervical cytological abnormalities. Elevated HIV RNA load is a key independent risk factor for cervical dysplasia in this co-infected population. Immediate initiation of antiretroviral therapy, prioritized 9-valent HPV vaccination, and regular cervical cancer screening are recommended to reduce the risk of cervical lesions and alleviate the disease burden among HIV-HPV co-infected women.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.