A population-based cohort of drug exposures and adverse pregnancy outcomes in China (DEEP): rationale, design, and baseline characteristics

IF 7.7 1区 医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH European Journal of Epidemiology Pub Date : 2024-04-09 DOI:10.1007/s10654-024-01124-6
Jing Tan, Yiquan Xiong, Chunrong Liu, Peng Zhao, Pei Gao, Guowei Li, Jin Guo, Mingxi Li, Wanqiang Wei, Guanhua Yao, Yongyao Qian, Lishan Ye, Huanyang Qi, Hui Liu, Moliang Chen, Kang Zou, Lehana Thabane, Xin Sun
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Abstract

The DEEP cohort is the first population-based cohort of pregnant population in China that longitudinally documented drug uses throughout the pregnancy life course and adverse pregnancy outcomes. The main goal of the study aims to monitor and evaluate the safety of drug use through the pregnancy life course in the Chinese setting. The DEEP cohort is developed primarily based on the population-based data platforms in Xiamen, a municipal city of 5 million population in southeast China. Based on these data platforms, we developed a pregnancy database that documented health care services and outcomes in the maternal and other departments. For identifying drug uses, we developed a drug prescription database using electronic healthcare records documented in the platforms across the primary, secondary and tertiary hospitals. By linking these two databases, we developed the DEEP cohort. All the pregnant women and their offspring in Xiamen are provided with health care and followed up according to standard protocols, and the primary adverse outcomes – congenital malformations – are collected using a standardized Case Report Form. From January 2013 to December 2021, the DEEP cohort included 564,740 pregnancies among 470,137 mothers, and documented 526,276 live births, 14,090 miscarriages and 6,058 fetal deaths/stillbirths and 25,723 continuing pregnancies. In total, 13,284,982 prescriptions were documented, in which 2,096 chemicals drugs, 163 biological products, 847 Chinese patent medicines and 655 herbal medicines were prescribed. The overall incidence rate of congenital malformations was 2.0% (10,444/526,276), while there were 25,526 (4.9%) preterm births and 25,605 (4.9%) live births with low birth weight.

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中国药物暴露和不良妊娠结局人群队列(DEEP):原理、设计和基线特征
DEEP队列是中国首个以人群为基础、纵向记录整个孕期药物使用情况和不良妊娠结局的孕妇队列。该研究的主要目的是监测和评估中国孕妇在整个孕期使用药物的安全性。DEEP 队列主要基于中国东南部一个拥有 500 万人口的市级城市--厦门的人口数据平台。在这些数据平台的基础上,我们开发了一个孕期数据库,记录了孕产妇和其他部门的医疗服务和结果。为了识别药物使用情况,我们利用平台中记录的一级、二级和三级医院的电子医疗记录开发了药物处方数据库。通过连接这两个数据库,我们建立了 DEEP 队列。厦门的所有孕妇及其后代都按照标准方案接受医疗保健服务和随访,并使用标准病例报告表收集主要不良结局--先天性畸形。从 2013 年 1 月至 2021 年 12 月,DEEP 队列共纳入了 470,137 名母亲的 564,740 例妊娠,记录了 526,276 例活产、14,090 例流产、6,058 例胎儿死亡/死胎和 25,723 例继续妊娠。共记录处方 13 284 982 份,其中化学药品 2 096 份,生物制品 163 份,中成药 847 份,中草药 655 份。先天性畸形的总发生率为 2.0%(10 444/526 276),早产儿为 25 526 例(4.9%),低出生体重儿为 25 605 例(4.9%)。
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来源期刊
European Journal of Epidemiology
European Journal of Epidemiology 医学-公共卫生、环境卫生与职业卫生
CiteScore
21.40
自引率
1.50%
发文量
109
审稿时长
6-12 weeks
期刊介绍: The European Journal of Epidemiology, established in 1985, is a peer-reviewed publication that provides a platform for discussions on epidemiology in its broadest sense. It covers various aspects of epidemiologic research and statistical methods. The journal facilitates communication between researchers, educators, and practitioners in epidemiology, including those in clinical and community medicine. Contributions from diverse fields such as public health, preventive medicine, clinical medicine, health economics, and computational biology and data science, in relation to health and disease, are encouraged. While accepting submissions from all over the world, the journal particularly emphasizes European topics relevant to epidemiology. The published articles consist of empirical research findings, developments in methodology, and opinion pieces.
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