Cardiovascular Health After Placental Abruption (CHAP)

摘要 胎盘早剥是一种产科并发症，定义为胎盘过早分离。尽管它的病因难以捉摸， 它被认为是急性刺激的结果--母婴的缺血、炎症和氧化应激。 界面相关的蜕膜动脉破裂，导致(早产)胎盘分离。的研究。 胎盘早剥与母婴长期心血管和出血/血栓脑血管事件 拟议项目的中心重点。我们将研究胎膜早剥对心血管疾病发生率的长期影响。 以及妇女及其子女的脑血管发病率和死亡率。我们还将调查两国的关系 胎膜早剥的临床分类(轻度和重度)，基于连续妊娠的胎膜早剥的风险，以及 双胎妊娠中早产对心脑血管事件发生率的影响。我们将承担一项因果关系 进行调解分析，以评估可通过(I)早产和 (2)小于胎龄儿的出生。我们将根据早剥的临床分类进行这一分析，并估计 在对所衡量的(社会-人口特征，包括产妇)进行纠正后的调解程度 吸烟、并存的医疗条件和产科事件)，以及未经测量的混乱。这是一个独特的方面 项目将通过支持向量机和深度学习算法的应用来识别以下子集 胎盘早剥和心脑血管死亡率和发病率的高危妇女。最后，我们将检查 母亲的种族/民族和社会经济地位是否是两者之间联系的影响衡量因素 早搏和心脑血管事件的风险。我们建议通过一个大型的 基于人群的流行病学研究，利用心肌梗死数据采集系统(MIDAS)的数据， 新泽西州所有非联邦急性护理医院收治的所有确诊为心血管疾病的患者的全州数据库， 纵向随访长达30年。Midas的数据将与新泽西州的胎儿死亡和活产联系在一起- 婴儿死亡数据与1980-2017年间相关的孕产妇和新生儿住院数据创建了 美国最大和最全面的数据库，以评估怀孕期间的哨兵事件传递的程度 对妇女和儿童晚年健康的持久风险。该项目将提供前所未有的机会来解决 分娩后妇女的公共健康、政策影响和临床筛查建议 关于心脑血管疾病的风险易感性。

Abstract Placental abruption is an obstetrical complication defined as premature placental separation. Despite its elusive etiology, it is believed to be the consequence of acute stimuli – ischemia, inflammation, and oxidative stress at the maternal‐fetal interface – associated with rupture of the decidual artery, resulting in (premature) placental separation. The study of abruption and maternal and newborn long‐term cardiovascular and hemorrhagic/thrombotic cerebrovascular events is the central focus of the proposed project. We will examine the long‐term impact of abruption on rates of cardiovascular and cerebrovascular morbidity and mortality in women and in their children. We will also investigate the relationship of clinical classification (mild and severe forms) of abruption, risks based on abruption across successive pregnancies, and abruption in twin pregnancies, on rates of cardiovascular and cerebrovascular events. We will undertake a causal mediation analysis to evaluate the extent to which these associations may be mediated through (i) preterm delivery and (ii) small for gestational age births. We will perform this analysis by clinical classification of abruption and estimate the extent of mediation following corrections for both measured (socio‐demographic characteristics, including maternal smoking, comorbid medical conditions, and obstetrical events), and unmeasured confounding. A unique aspect of this project will be to identify, through applications of Support Vector Machines and Deep Learning algorithms, subsets of women at high risk for abruption and cardiovascular and cerebrovascular mortality and morbidity. Finally, we will examine whether maternal race/ethnicity and socioeconomic status are effect measure modifiers of the association between abruption and risks of cardiovascular and cerebrovascular events. We propose to address these aims through a large population‐based epidemiologic study, utilizing data from the Myocardial Infarction Data Acquisition System (MIDAS), a New Jersey statewide database of all patients admitted to all non‐federal acute care hospitals in NJ with a CVD diagnosis, with longitudinal follow‐up of up to 30 years. The MIDAS data will be linked to the NJ fetal death and linked live birth‐ infant death data with associated maternal and newborn hospitalization data between 1980‐2017 to create one of the largest and most comprehensive databases in the US to evaluate the extent to which sentinel events in pregnancy impart lasting risk for women's and children's health later in life. This project will provide unprecedented opportunities to address public health, policy implications and clinical screening recommendations of women during the period following delivery regarding risk susceptibility to cardiovascular and cerebrovascular disease.