ReviewJournal of translational medicine2024
Enhancing HIV/STI decision-making: challenges and opportunities in leveraging predictive models for individuals, healthcare providers, and policymakers.
Review in Journal of translational medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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
2 citing papers in PubMed.
- Analysis of the spatio-temporal pattern and evolutionary trends of syphilis at township level in Xining City, Qinghai Province, China from 2008 to 2024.Scientific reports · 2026Article
- Findings from a transformer-based prediction model: social norms and confidentiality are associated with STIs risk in British men and women.BMC public health · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The prevention and control of human immunodeficiency virus and sexually transmitted infections (HIV/STI) face challenges worldwide, especially in China. Prediction tools, which analyze medical data and information to make future predictions, were once mainly used in HIV/STI research to help make diagnostic or prognostic decisions, has have now extended to the public as a freely accessible tool. This article provides an overview of the different roles of prediction tools in preventing and controlling HIV/STI from the perspectives of individuals, healthcare providers, and policymakers. For individuals, prediction tools serve as a risk assessment solution that assess their risk and consciously improve risk reception or change risky behaviors. For researchers, prediction tools are powerful for assisting in identifying risk factors and predicting patients' infection risk, which can inform timely and accurate intervention planning in the future. In order to achieve the best performance, current research increasingly underscores the necessity of considering multiple levels of information, such as socio-behavioral data, in developing a robust prediction tool. In addition, it is also crucial to conduct trials in clinical settings to validate the effectiveness of prediction tools. Many studies only use theoretical parameters such as model accuracy to estimate its predictive. If these improvements are made, the application of prediction tools could be a potentially inspiring solution in the prevention and control of HIV/STI, and an opportunity for achieving the World Health Organization's agenda to end the HIV/STI epidemic by 2030.
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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.