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
{"title":"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","authors":"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","doi":"10.1007/s10654-024-01124-6","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":11907,"journal":{"name":"European Journal of Epidemiology","volume":"26 1","pages":""},"PeriodicalIF":7.7000,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A population-based cohort of drug exposures and adverse pregnancy outcomes in China (DEEP): rationale, design, and baseline characteristics\",\"authors\":\"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\",\"doi\":\"10.1007/s10654-024-01124-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>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. 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A population-based cohort of drug exposures and adverse pregnancy outcomes in China (DEEP): rationale, design, and baseline characteristics
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.
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.