ArticleBMC public health2024
Effectiveness of health management team program to enhance prevention of mother-to-child transmission of hepatitis B virus in Ningxia, China.
Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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
3 citing papers in PubMed.
- Using latent class analysis to characterize a high-misconception profile for targeted health education among HBsAg-positive pregnant women in China.Frontiers in public health · 2026Article
- Knowledge, perceptions, and health education needs regarding hepatitis B virus among HBsAg-positive pregnant women in Taiyuan, China: a cross-sectional study.BMC public health · 2025Article
- Effectiveness and implementation of decentralized, community- and primary care-based strategies in promoting hepatitis B testing uptake: a systematic review and meta-analysis.EClinicalMedicine · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
backgroundHepatitis B mother-to-child transmission interruption (PMTCT) poses a formidable challenge in underdeveloped regions of China. This study aims to evaluate the effectiveness of PMTCT and the health management team (HMT) model in Ningxia, China, as well as the risk factors for adverse outcomes.
methodsThe PMTCT + HMT model was established, and 360 pregnant women diagnosed with HBV infection in 2020-2022 were selected and divided into the control and the study groups based on different intervention modes. HBV serum markers and HBV DNA levels were assessed, the indicators of compliance behaviors and adverse outcomes were compared, and the factors influencing adverse outcomes were analyzed.
resultsThe majority of subjects were residents of the local city, married, with secondary school or higher education, and employees of public sectors. The proportion of ethnic minorities was 40.8% and 34.2% in the control group and study group. HBeAg positivity was 23.3% and 26.3%, and the proportion with HBV DNA levels ≥ 2 × 105 IU/mL was 9.2% and 7.1%. Compared with the control group (PMTCT alone), the PMTCT + HMT model led to improved maternal knowledge (17.5% vs. 57.1%), voluntary counseling (34.2% vs. 63.3%), and testing (37.5% vs. 70.4%). The incidence of adverse pregnancy outcomes ((including miscarriage, preterm birth) decreased significantly (17.5% vs. 6.2%), as did adverse neonatal outcomes (low birth weight and congenital HBV) (26.9% vs. 10.5%). Adverse outcomes were associated with low educational attainment, non-locals, unmarried status, and ethnic minority identity. Additionally, HBeAg positivity and HBV DNA levels ≥ 2 × 10
conclusionsThe PMTCT + HMT model demonstrates significant effectiveness in preventing mother-to-child transmission of hepatitis B in Ningxia. The unique demographic structure of Ningxia region is closely linked to poor outcomes, emphasizing the importance of monitoring HBeAg status and HBV DNA viral load level.
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.