Cardiovascular Disease in Pregnancy and the Postpartum Period in Maryland

心血管疾病（CVD）是妊娠相关死亡的主要原因， 导致美国严重孕产妇发病率（SMM）。妊娠相关死亡率 和SMM在过去二十年中一直在增加。这项研究将探讨医院的遭遇 在所有育龄妇女（15-49岁）中诊断为CVD，随后重点关注 孕妇和产后妇女。更具体地说，我们将探讨前之间的关系， 妊娠期CVD、SMM和产后期后CVD。我们将使用来自一个家庭的数据， 马里兰州数据库，包括医院出院和急诊的宇宙 部门（艾德）在2013-2019年期间访问该州。我们的主要分析样本将包括 在马里兰州至少有一次医院就诊（住院或艾德就诊）的所有育龄女性 数据仅来自在此期间有一次或多次分娩住院的妇女。 同一时期将包括二次分析样本。我们将得出两个结果指标， 主要和相关的CVD遭遇措施，以及SMM和CVD-SMM措施，使用 疾病控制和预防中心基于ICD的算法。经过探索性分析，我们 我们将使用专门为纵向数据开发的统计方法来解决我们的具体问题。 目标。值得注意的是，生存分析技术将用于检查到医院就诊的时间 研究期间不同时间CVD风险的各种感兴趣亚群的CVD诊断， 调查期间;以及，针对关键（时变）患者和医院调整的随机效应模型 特征将被拟合，以检查是否以前的CVD医院遇到或显着的 CVD医院就诊模式可预测分娩期间与产后期间的SMM/CVD-SMM 住院，以及SMM/CVD-SMM是否预测随后的CVD医院就诊。对我们 知识，这将是第一个以人群为基础的研究，以检查医院遇到的心血管疾病 在所有育龄妇女中的诊断，也是第一个探索产前 妊娠期CVD、SMM和产后期后CVD采用纵向方法。我们 研究结果将在同行评审的文献中传播，并通过在科学会议上的介绍传播。 会议.这项试点研究将为旨在设计更大规模的赠款申请提供初步数据， 干预措施，以预防妇女在其生命过程中的心血管疾病。

Cardiovascular disease (CVD) is the leading cause of pregnancy-related mortality and an important contributor to severe maternal morbidity (SMM) in the United States. Both pregnancy-related mortality and SMM have been increasing over the past two decades. This study will examine hospital encounters with a CVD diagnosis in all women of reproductive age (15-49 years), with a subsequent focus on pregnant and postpartum women. More specifically, we will explore relationships between pre- pregnancy CVD, SMM and CVD beyond the postpartum period. We will use data from a family of Maryland state databases that comprise the universe of hospital discharges and emergency Department (ED) visits in the state during 2013-2019. Our primary analytic sample will be comprised of all women of reproductive age with at least one hospital encounter (inpatient or ED visit) in Maryland hospitals during this period; data from only women with one or more delivery hospitalizations during the same period will comprise a secondary analytic sample. We will derive two outcome measures, a primary and an associated CVD encounter measure, as well as SMM and CVD-SMM measures using Centers for Disease Control and Prevention’s ICD-based algorithm. Following exploratory analyses, we will use statistical methods developed specifically for use with longitudinal data to address our specific aims. Of note, survival analysis techniques will be employed to examine time to hospital encounters with CVD diagnosis for the various subpopulations of interest at different times of CVD risk during the period of investigation; and, random effects models adjusted for key (time-varying) patient and hospital characteristics will be fitted to examine whether a previous CVD hospital encounter or a significant pattern of CVD hospital encounter predicts SMM/CVD-SMM during delivery vs. postpartum hospitalizations, and whether SMM/CVD-SMM predicts a subsequent CVD hospital encounter. To our knowledge, this will be the first population-based study to examine hospital encounters with a CVD diagnosis in all women of reproductive age and also the first to explore relationships between pre- pregnancy CVD, SMM and CVD beyond the postpartum period using a longitudinal approach. Our results will be disseminated in the peer-reviewed literature and through presentations at scientific meetings. This pilot study will provide preliminary data for larger grant applications aiming to design interventions to prevent CVD in women over their life course.