Association Between Endotype of Prematurity and Cystic Periventricular Leukomalacia: A Bayesian Model-Averaged Meta-Analysis

早产内型与囊性脑室周围白质软化症的关联:贝叶斯模型平均荟萃分析

阅读:1

Abstract

Introduction: Pathophysiological pathways-or endotypes-leading to prematurity can be clustered into two groups: infection/inflammation and dysfunctional placentation. We aimed to perform a systematic review and meta-analysis of studies exploring the association between these endotypes and cystic periventricular leukomalacia (cPVL). Methods: PubMed and Embase were searched for observational studies examining preterm infants and reporting data on the association between endotype of prematurity and cPVL. Chorioamnionitis represented the infectious-inflammatory endotype, while dysfunctional placentation proxies were hypertensive disorders of pregnancy (HDPs) and small for gestational age (SGA)/intrauterine growth restriction (IUGR). Bayesian model-averaged (BMA) meta-analysis was used to calculate Bayes factors (BFs). The BF(10) is the ratio of the probability of the data under the alternative hypothesis (H(1;) presence of association) over the probability of the data under the null hypothesis (H(0;) absence of association). Results: Of 1141 potentially relevant studies; 67 (108,571 infants) were included. The BMA analysis showed strong evidence in favor of a positive association between chorioamnionitis and cPVL (OR 1.58; 95% CrI 1.12 to 2.20; BF(10) = 20.5) and extreme evidence in favor of a negative association between HDPs and cPVL (OR 0.63; 95% CrI 0.54 to 0.75; BF(10) = 2937). The evidence for the SGA/IUGR group was inconclusive (OR 0.87; 95% CrI 0.75 to 1.01; BF(10) = 1.41). Conclusions: This Bayesian meta-analysis provides evidence indicative of an association between antenatal infection-inflammation and an increased risk of developing cPVL in preterm infants. Conversely, infants exposed to HDPs are less likely to develop cPVL.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。