Early Warning system for detecting pre-eclampsia

描述(申请人提供)：先兆子痫是一种妊娠期高血压疾病，是世界各地孕产妇和新生儿发病率和死亡率的主要原因，每年造成约76,000名孕产妇和500,000名婴儿死亡。作为一种异质性且知之甚少的疾病，其发病机制和可能的治疗方法是一个活跃的研究领域。虽然这种疾病的大部分发病率和死亡率可以通过三级护理中心的密切监测和治疗来预防，但诊断延迟和无法准确预测哪些女性将进展为严重形式的非典型表现使治疗复杂化。此外，许多妇女在延长产前入院、监测和误导治疗的并发症方面接受不必要的治疗，费用不计其数。准确诊断先兆子痫的技术，或者更好地预测哪些女性会患上这种疾病，将加强治疗并挽救生命。目前的研究重点是血流中的一系列生物标志物；这是一个可行的机会，尽管成本很高，但它既可以预测，也可以提高诊断准确性。目前的提议寻求一种成本低得多的替代方案。先兆子痫的血管紊乱在症状出现前几个月就会出现。早期的工作表明，通过分析产妇心血管系统的特征，这些变化是可以检测到的。目前的项目将开发和测试一种廉价、可重复使用、非侵入性的设备，该设备可以准确地诊断先兆子痫。该装置采用单个心电导联和脉搏血氧饱和度探头。软件算法从这两种技术中提取了80多个特征。该项目的阶段包括1)使用台式系统收集100名确诊为先兆子痫和100名正常分娩的临产产妇的数据；2)使用回归和非线性技术改进初步算法；3)开发该设备的微型原型并验证性能。对于第二阶段，将在另外两项研究中使用该装置：(1)纵向数据收集 (2)在分娩病房进行大规模的数据收集，以开发区分轻度子痫前期患者和那些将继续发展为重度疾病的患者的算法。最终目标是一种小型、廉价、可重复使用的非侵入性设备，用于诊所、急诊科和分娩病房，以预测和诊断先兆子痫，并区分未来的轻度和重度疾病。该设备的成本允许每次使用成本低至5美分。它将支持关于患者管理的更好决策，包括监测水平、交付计划和治疗干预。

DESCRIPTION (provided by applicant): Preeclampsia, a hypertensive disorder of pregnancy, is a leading cause of maternal and neonatal morbidity and mortality around the world, responsible for approximately 76,000 maternal and 500,000 infant deaths per year. As a heterogeneous and poorly understood disorder, its pathogenesis and possible treatments are an area of active research. While the majority of morbidity and mortality from the disorder can be prevented with close monitoring and treatment in a tertiary care center, atypical presentations with delayed diagnosis and inability to accurately predict which women will progress to a severe form complicates management. Additionally, many women are treated unnecessarily at untold cost in prolonged antepartum admissions, monitoring, and complications from misguided therapy. Technology to accurately diagnose preeclampsia, or better yet predict which women will develop the disease, would enhance treatment and save lives. Current research focuses on an array of biomarkers in the bloodstream; a viable, if expensive, opportunity for both prediction and improved diagnostic accuracy. The current proposal seeks a much less costly alternative. The vascular derangement that underlies preeclampsia develops months before the onset of symptoms. Early work shows these changes are detectable by analyzing features of the maternal cardiovascular system. The current project will develop and test an inexpensive, reusable, non-invasive device that accurately diagnoses preeclampsia. The device employs a single ECG lead and a pulse oximetry probe. Software algorithms extract more than 80 features from these two technologies. The phases of the project include 1) collect data on 100 preeclamptic and 100 control parturients in labor & delivery with known diagnosis, using a bench-top system; 2) refine preliminary algorithms with regression and nonlinear techniques; 3) develop a miniaturized prototype of the device and validate performance. For Phase II the device will be employed in two additional studies: (1) longitudinal data collection in prenatal clinic patients to refine algorithms for prediction of preeclampsia months before onset and (2) large-scale data collection in delivery wards for development of algorithms that distinguish mild preeclamptics from those who will go on to develop severe disease. The eventual goal is a small, inexpensive, reusable, non-invasive device for use in clinics, emergency departments and delivery wards to predict and diagnose preeclampsia and differentiate future mild and severe disease. The cost of the device allows for a per use cost of as little as five cents. It will support better decision making regarding patient management including level of monitoring, delivery planning and therapeutic interventions.