@文章{信息:doi/10.2196/25658，作者="黄云、罗崇良、蒋崇良、英、杜、景成、陶、崔、陈、勇、浩、元涛"，标题="一种预测流感疫苗接种后格林-巴综合征风险的贝叶斯网络:开发与验证研究"，期刊="JMIR公共卫生监测"，年="2022"，月="3"，日="25"，卷="8"，数="3"，页="e25658"，关键词="不良事件;贝叶斯网络;Guillain-Barr {\ ' e}综合症;风险预测;背景:确定格林-巴尔综合征(GBS)的关键因素并预测其发生对改善GBS患者的预后至关重要。然而，关于GBS的预警模型几乎没有任何出版物。在GBS风险预测中，贝叶斯网络(BN)模型是一个值得尝试的模型，在许多类似的领域，它是一个准确的、可解释的和交互敏感的图模型。目的:本研究旨在确定GBS的最显著因素，并进一步开发和验证用于预测GBS风险的BN模型。方法:提取大规模流感疫苗上市后监测数据，包括79,165美国(从1990年至2017年疫苗不良事件报告系统获得)和12,495欧洲(从2003年至2016年eudravigance系统获得)不良事件(AEs)报告，用于模型开发和验证。使用R包bnlearn构建初始BN时，包括GBS、年龄、性别和前50名流行AEs。 Results: Age, gender, and 10 AEs were identified as the most significant factors of GBS. The posttest probability of GBS suggested that male vaccinees aged 50-64 years and without erythema should be on the alert or be warned by clinicians about an increased risk of GBS, especially when they also experience symptoms of asthenia, hypesthesia, muscular weakness, or paresthesia. The established BN model achieved an area under the receiver operating characteristic curve of 0.866 (95{\%} CI 0.865-0.867), sensitivity of 0.752 (95{\%} CI 0.749-0.756), specificity of 0.882 (95{\%} CI 0.879-0.885), and accuracy of 0.882 (95{\%} CI 0.879-0.884) for predicting GBS risk during the internal validation and obtained values of 0.829, 0.673, 0.854, and 0.843 for area under the receiver operating characteristic curve, sensitivity, specificity, and accuracy, respectively, during the external validation. Conclusions: The findings of this study illustrated that a BN model can effectively identify the most significant factors of GBS, improve understanding of the complex interactions among different postvaccination symptoms through its graphical representation, and accurately predict the risk of GBS. The established BN model could further assist clinical decision-making by providing an estimated risk of GBS for a specific vaccinee or be developed into an open-access platform for vaccinees' self-monitoring. ", issn="2369-2960", doi="10.2196/25658", url="https://publichealth.www.mybigtv.com/2022/3/e25658", url="https://doi.org/10.2196/25658", url="http://www.ncbi.nlm.nih.gov/pubmed/35333192" }