采用多元分析法评估与婴儿神经发育不良相关的产前危险因素。
Assessing for prenatal risk factors associated with infant neurologic morbidity using a multivariate analysis.
机构信息
Division of Neonatology, Department of Pediatrics, University of California, San Francisco, CA, USA.
California Preterm Birth Initiative, University of California San Francisco, San Francisco, CA, USA.
出版信息
J Perinatol. 2023 Dec;43(12):1486-1493. doi: 10.1038/s41372-023-01820-3. Epub 2023 Nov 10.
OBJECTIVE
To characterize the biochemical and demographic profiles of pregnant people with maternal immune activation (MIA) and identify the prenatal characteristics associated with neurologic morbidity in offspring.
STUDY DESIGN
This was a retrospective cohort study of 602 mother-infant dyads with births between 2009 and 2010 in California. Multivariable logistic regression was used to build a MIA vulnerability profile including mid-pregnancy biochemical markers and maternal demographic characteristics, and its relationship with infant neurologic morbidity was examined.
RESULTS
Of the 602 mother-infant dyads, 80 mothers and 61 infants had diagnoses suggestive of MIA and neurologic morbidity, respectively. Our model, including two demographic and seven biochemical characteristics, identified mothers with MIA with good performance (AUC:0.814; 95% CI:0.7-0.8). Three demographic and five inflammatory markers together identified 80% of infants with neurological morbidity (AUC:0.802, 95% CI:0.7-0.8).
CONCLUSION
Inflammatory environment in mothers with pre-existing risk factors like obesity, poverty, and prematurity renders offspring more susceptible to neurologic morbidities.
目的
描述母体免疫激活（MIA）孕妇的生化和人口统计学特征，并确定与后代神经发育不良相关的产前特征。
研究设计
这是一项回顾性队列研究，纳入了 2009 年至 2010 年期间在加利福尼亚州出生的 602 对母婴对子。采用多变量逻辑回归建立 MIA 易感性模型，包括妊娠中期生化标志物和母体人口统计学特征，并检查其与婴儿神经发育不良的关系。
结果
在 602 对母婴对子中，80 名母亲和 61 名婴儿分别被诊断为存在 MIA 和神经发育不良。我们的模型包括两个人口统计学特征和七个生化特征，能够很好地识别出存在 MIA 的母亲（AUC：0.814；95%CI：0.7-0.8）。三个人口统计学特征和五个炎症标志物一起可以识别出 80%存在神经发育不良的婴儿（AUC：0.802，95%CI：0.7-0.8）。
结论
患有肥胖、贫困和早产等已有风险因素的母亲的炎症环境使后代更容易发生神经发育不良。
Zotero 插件