Ulster University, United Kingdom.
INSERM, Centre Hospitalier Universitaire de Toulouse, France.
Paediatr Perinat Epidemiol. 2022 Jul;36(4):493-507. doi: 10.1111/ppe.12840. Epub 2022 Mar 2.
The COVID-19 pandemic has accelerated pregnancy outcome research, but little attention has been given specifically to the risk of congenital anomalies (CA) and first trimester exposures.
We reviewed the main data sources and study designs used internationally, particularly in Europe, for CA research, and their strengths and limitations for investigating COVID-19 disease, medications and vaccines.
We classify research designs based on four data sources: a) spontaneous adverse event reporting, where study subjects are positive for both exposure and outcome, b) pregnancy exposure registries, where study subjects are positive for exposure, c) congenital anomaly registries, where study subjects are positive for outcome and d) population healthcare data where the entire population of births is included, irrespective of exposure and outcome.
Each data source allows different study designs, including case series, exposed pregnancy cohorts (with external comparator), ecological studies, case-control studies and population cohort studies (with internal comparator).
The quality of data sources for CA studies is reviewed in relation to criteria including diagnostic accuracy of CA data, size of study population, inclusion of terminations of pregnancy for foetal anomaly, inclusion of first trimester COVID-19-related exposures and use of an internal comparator group. Multinational collaboration models are reviewed.
Pregnancy exposure registries have been the main design for COVID-19 pregnancy studies, but lack detail regarding first trimester exposures relevant to CA, or a suitable comparator group. CA registries present opportunities for improving diagnostic accuracy in COVID-19 research, especially when linked to other data sources. Availability of inpatient hospital medication use in population healthcare data is limited. More use of ongoing mother-baby linkage systems would improve research efficiency. Multinational collaboration delivers statistical power.
Challenges and opportunities exist to improve research on CA in relation to the COVID-19 pandemic and future pandemics.
COVID-19 大流行加速了妊娠结局研究,但很少有专门关注先天性异常 (CA) 和早孕暴露风险的研究。
我们回顾了国际上(特别是欧洲)用于 CA 研究的主要数据来源和研究设计,以及它们在研究 COVID-19 疾病、药物和疫苗方面的优势和局限性。
我们根据四个数据来源对研究设计进行分类:a) 自发不良事件报告,研究对象同时对暴露和结局呈阳性,b) 妊娠暴露登记,研究对象对暴露呈阳性,c) 先天性异常登记,研究对象对结局呈阳性,d) 人群医疗保健数据,包括所有出生人口,无论是否有暴露和结局。
每个数据来源都允许不同的研究设计,包括病例系列、暴露妊娠队列(有外部对照)、生态研究、病例对照研究和人群队列研究(有内部对照)。
我们根据 CA 研究数据来源的标准,包括 CA 数据的诊断准确性、研究人群的大小、包括因胎儿异常而终止妊娠、包括早孕与 COVID-19 相关的暴露以及使用内部对照组,对其进行了审查。还审查了跨国合作模式。
妊娠暴露登记一直是 COVID-19 妊娠研究的主要设计,但缺乏与 CA 相关的早孕暴露的详细信息,或缺乏合适的对照人群。先天性异常登记为改善 COVID-19 研究中的诊断准确性提供了机会,尤其是当与其他数据来源相结合时。人群医疗保健数据中可获得的住院患者药物使用情况有限。更多地利用正在进行的母婴联系系统将提高研究效率。跨国合作提供了统计能力。
在 COVID-19 大流行和未来的大流行中,在 CA 方面的研究存在挑战和机遇。