Department of epidemiology and infection control. Dijon university hospital, Dijon, France.
Department of obstetrics and gynecology. Dijon university hospital, Dijon, France.
Infect Dis Now. 2022 May;52(3):123-128. doi: 10.1016/j.idnow.2022.02.009. Epub 2022 Feb 16.
Wei et al. have published a meta-analysis (MA), which aimed to evaluate the association between SARS-CoV-2 infection during pregnancy and adverse pregnancy outcomes. Using classical random-effects model, they found that SARS-CoV-2 infection was associated with preeclampsia, preterm birth and stillbirth. Performing MA with low event rates or with few studies may be challenging insofar as MA relies on several within and between-study distributional assumptions. The objective was to assess the robustness of the results provided by Wei et al. METHODS: We performed a sensitivity analysis using frequentist and Bayesian meta-analysis methods. We also estimated fragility indexes.
For eclampsia, the confidence intervals of most frequentist models contain 1. All beta-binomial models (Bayesian) lead to credible intervals containing 1. The prediction interval, based on DL method, ranges from 0.75 to 2.38. The fragility index is 2 for the DL method. For preterm, the confidence (credible) intervals exclude 1. The prediction interval is broad, ranging from 0.84 to 20.61. The fragility index ranges from 27 to 10. For stillbirth, the confidence intervals of most frequentist models contain 1. Six Bayesian MA models lead to credible intervals containing 1. The prediction interval ranges from 0.52 to 8.49. The fragility index is 3.
Given the available data and the results of our broad sensitivity analysis, we can suggest that SARS-CoV-2 infection during pregnancy is associated with preterm, and that it may be associated with preeclampsia. For stillbirth, more data are needed as none of the Bayesian analyses are conclusive.
Wei 等人发表了一项荟萃分析(MA),旨在评估孕妇感染 SARS-CoV-2 与不良妊娠结局之间的关联。他们使用经典的随机效应模型发现,SARS-CoV-2 感染与子痫前期、早产和死产有关。使用低事件率或研究较少的 MA 可能具有挑战性,因为 MA 依赖于几个研究内和研究间的分布假设。目的是评估 Wei 等人提供的结果的稳健性。
我们使用频率论和贝叶斯荟萃分析方法进行敏感性分析。我们还估计了脆弱性指数。
对于子痫前期,大多数频率论模型的置信区间包含 1。所有贝叶斯 beta-binomial 模型(贝叶斯)导致可信区间包含 1。基于 DL 方法的预测区间范围从 0.75 到 2.38。DL 方法的脆弱性指数为 2。对于早产,置信(可信)区间排除 1。预测区间很宽,范围从 0.84 到 20.61。脆弱性指数从 27 到 10。对于死产,大多数频率论模型的置信区间包含 1。6 个贝叶斯 MA 模型导致可信区间包含 1。预测区间范围从 0.52 到 8.49。脆弱性指数为 3。
鉴于现有数据和我们广泛的敏感性分析结果,我们可以建议孕妇感染 SARS-CoV-2 与早产有关,并且可能与子痫前期有关。对于死产,需要更多的数据,因为没有一个贝叶斯分析是结论性的。