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一项研究印度早产多维相关因素的妊娠队列研究:研究设计、实施及参与者的基线特征。

A Pregnancy Cohort to Study Multidimensional Correlates of Preterm Birth in India: Study Design, Implementation, and Baseline Characteristics of the Participants.

机构信息

Translational Health Science and Technology Institute, National Capital Region Biotech Cluster, Faridabad, Delhi NCR, India.

National Institute of Biomedical Genomics, Kalyani, West Bengal, India.

出版信息

Am J Epidemiol. 2019 Apr 1;188(4):621-631. doi: 10.1093/aje/kwy284.

Abstract

Globally, preterm birth is a major public health problem. In India, 3.6 million of the 27 million infants born annually are preterm. Risk stratification of women based on multidimensional risk factors assessed during pregnancy is critical for prevention of preterm birth. A cohort study of pregnant women was initiated in May 2015 at the civil hospital in Gurugram, Haryana, India. Women are enrolled within 20 weeks of gestation and are followed until delivery and once postpartum. The objectives are to identify clinical, epidemiologic, genomic, epigenomic, proteomic, and microbial correlates; discover molecular-risk markers by using an integrative -omics approach; and generate a risk-prediction algorithm for preterm birth. We describe here the longitudinal study design, methodology of data collection, and the repositories of data, biospecimens, and ultrasound images being created. A total of 4,326 pregnant women, with documented evidence of recruitment before 20 weeks of gestation, have been enrolled through March 2018. We report baseline characteristics and outcomes of the first 2,000 enrolled participants. A high frequency of preterm births (14.9% among 1,662 live births) is noteworthy. The cohort database and the repositories will become global resources to answer critical questions on preterm birth and other birth outcomes.

摘要

全球范围内,早产是一个主要的公共卫生问题。在印度,每年 2700 万出生的婴儿中,有 360 万是早产儿。对孕妇进行基于妊娠期间评估的多维风险因素的风险分层,对于预防早产至关重要。一项针对孕妇的队列研究于 2015 年 5 月在印度哈里亚纳邦古尔冈的公立医院启动。孕妇在妊娠 20 周内入组,并一直随访至分娩和产后。研究目的是确定临床、流行病学、基因组、表观基因组、蛋白质组和微生物相关因素;通过整合组学方法发现分子风险标志物;并生成早产风险预测算法。本文介绍了纵向研究设计、数据收集方法以及正在创建的数据、生物样本和超声图像存储库。截至 2018 年 3 月,共有 4326 名孕妇通过记录在案的妊娠 20 周前入组证明入组。我们报告了前 2000 名入组参与者的基线特征和结局。早产发生率很高(1662 例活产中有 14.9%),这值得关注。该队列数据库和存储库将成为全球资源,用于回答关于早产和其他分娩结局的关键问题。

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