Evidence map›Paper›PMID 42504293›Full record

ArticleInfection and drug resistance2026

Analysis of Risk Factors for High versus Low HIV Exposure in Neonates and Development of a Predictive Nomogram Model.

Li Li, JinXiu Lin, XinXin Huang, Mian Pan

Abstract read
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Article in Infection and drug resistance, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

4 authors.

Li LiDepartment of Obstetrics, Fujian Maternity and Child Health Hospital, Fuzhou, Fujian Province, People's Republic of China.ORCID 0000-0003-2676-9101
JinXiu LinDepartment of Obstetrics, Fujian Maternity and Child Health Hospital, Fuzhou, Fujian Province, People's Republic of China.
XinXin HuangCollege of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, Fujian Province, People's Republic of China.
Mian PanDepartment of Obstetrics, Fujian Maternity and Child Health Hospital, Fuzhou, Fujian Province, People's Republic of China.ORCID 0000-0002-1698-4994

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To investigate prenatal factors associated with high-risk HIV exposure in neonates at the time of delivery, and to construct a nomogram prediction model for assessing the risk level of neonates' HIV exposure. Methods: This retrospective study included clinical data from 928 cases of HIV-exposed neonates. Participants were categorized into high and low HIV exposure risk groups according to their risk status at delivery. Sociodemographic factors, antenatal records, and antiretroviral therapy (ART) use during pregnancy were analyzed across exposure groups. Independent predictors of high neonatal HIV exposure were determined via multivariate logistic regression. Internal validation was performed using the bootstrap method, and model calibration was assessed using a calibration curve. Results: Among the 928 neonates born to HIV-positive women, 458 were categorized as high-risk and 470 as low-risk for HIV exposure. There were significant differences between the two groups in terms of sociodemographic data, prenatal care, and the use of antiviral drugs et al. Findings from the regression indicated that maternal ethnicity, maternal education level, HIV diagnosis before pregnancy, gestational age at first prenatal visit, and number of antenatal visits are independent predictors of high HIV exposure in neonates. Based on these variables, a nomogram model was constructed for assessing the risk level of neonates' HIV exposure. The result showed a C-index of 0.954 (95% CI:0.942-0.966), indicated relatively high discriminative ability. Internal validation using bootstrap sampling demonstrated good agreement between predicted and observed high-exposure probabilities, as shown by the calibration curve. Conclusion: The nomogram developed in this study offers a tool to predict the risk of HIV exposure in neonates born to HIV-positive mothers. Encouraging pregnant women at risk of HIV infection to get early screening, and guiding HIV-positive pregnant women to receive regular prenatal care can substantially reduce the risk of newborns being exposed to HIV during the perinatal period.

Indexed as

high exposure riskHIVmother-to-child transmissionNeonatenomogram prediction model

Identifiers

PMID42504293
PMCPMC13401873

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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.