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Precision Volume Management During Maintenance Hemodialysis

维持性血液透析期间的精确容量管理

基本信息

批准号：
9909170
负责人：
Hao Wang
金额：
$ 7.04万
依托单位：
UNIVERSITY OF PENNSYLVANIA
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-07-01 至 2021-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9909170
关键词：
Adoption Adverse event Aftercare Award Biometry Blood Plasma Volume Blood Pressure Blood Vessels Clinical Data Data Collection Data Set Degree program Development Dialysis procedure End stage renal failure Event Excision Fellowship Future Goals Heart Rate Hematocrit procedure Hemodialysis Hypotension Hypovolemia Interview Kidney Kidney Diseases Kidney Failure Life Liquid substance Maintenance Master&apos s Degree Measures Methods Modeling Monitor Morbidity - disease rate National Research Service Awards Nature Nurses Outcome Outpatients Patient Care Patient-Focused Outcomes Patients Pattern Perception Plasma Privatization Provider Quality of life Recovery Research Research Methodology Risk Adjustment Risk Factors Role Statistical Models Stress Structural Models Technology Time Tissues Training United States Update Weight Work care delivery clinical application clinical epidemiology experience hazard health related quality of life hemodynamics improved innovation insight interstitial mortality mortality risk new technology non-invasive monitor novel predictive modeling programs protocol development research and development resilience time use uptake usability

项目摘要

Project Summary More than 400,000 people currently receive maintenance hemodialysis in the United States. While this therapy is life-extending, clinical outcomes and quality of life are poor. Current strategies to remove fluid with hemodialysis are imprecise, and events both during hemodialysis (e.g., intra-dialytic hypotension) and after (e.g., prolonged recovery time) are common complications associated with significant morbidity and mortality. Unfortunately, these events are challenging to predict with standard methods for hemodynamic monitoring. All of this highlights a need for greater precision in monitoring and improvement in fluid removal on hemodialysis. Continuous hematocrit monitors have been developed to non-invasively monitor relative changes in intravascular volume during a hemodialysis session. Yet, adoption of this technology into decisions on fluid management has been mixed. This is largely due to a lack of data to show a consistent association with intra- dialytic hypotension or improved clinical outcomes. However, studies have largely focused on plasma volume, but hypovolemia is not the only cause of hypotension. In order to leverage the full potential of this technology, we plan to incorporate changes in plasma volume with the rate of fluid removal during hemodialysis to yield a semi-continuous measure of the rate of vascular refilling from the interstitial tissue - termed plasma refill rate - as a dynamic measure of patient resilience. Examining patterns of plasma refill rate offers a unique opportunity to evaluate changes in patient resilience throughout a hemodialysis treatment that has yet to be fully explored. Additionally, the clinical impact of a new technology requires understanding of its ease of integration into the workflow. As such, for this work we will use two complementary approaches. Using a large dataset, we will examine the relationship between plasma refill rate and intra-dialytic hypotension by (1) determining if low plasma refill rates are associated with the number of hemodialysis sessions with intra-dialytic hypotension and (2) to develop a model using time-updated variables to predict the time to development of intra-dialytic hypotension. Concurrently, we will collect primary data to (3) evaluate the association between plasma refill rate and recovery time and (4) explore provider perspectives on the usability of this technology. Through these parallel projects we will improve our understanding of subtle hemodynamic changes that will inform future studies and fuel work towards precision volume management in maintenance hemodialysis. Moreover, if we find a critical role of plasma refill rate in the prediction of intra-dialytic hypotension or recovery time, we can leverage the semi-continuous nature of this technology to alter the user interface and improve delivery of care. In conjunction with formal coursework in a master's program for clinical epidemiology, the proposed application for the NRSA fellowship award will provide Dr. Wang with intensive training in advanced biostatistics, expertise in statistical modeling, primary data collection, and facilitate the establishment of a research niche in dialysis technology and end-stage kidney disease.

项目摘要目前在美国有超过40万人接受维持性血液透析。虽然这治疗是延长生命，临床结果和生活质量差。目前的战略，以消除液体，血液透析是不精确的，并且血液透析期间的事件（例如，透析中低血压）和 (e.g.,恢复时间延长）是与显著发病率和死亡率相关的常见并发症。不幸的是，这些事件很难用血流动力学监测的标准方法预测。所有这突出了需要更高的监测精度和改善血液透析中的液体清除。连续血细胞比容监测器已经被开发用于非侵入性地监测血细胞比容的相对变化。血液透析期间的血管内容量。然而，将这项技术应用于流体的决策，管理是混合的。这在很大程度上是由于缺乏数据来显示与内部的一致关联，透析低血压或改善临床结局。然而，研究主要集中在血浆容量，但低血容量并不是低血压的唯一原因。为了充分利用这项技术的潜力，我们计划将血液透析过程中血浆容量的变化与液体清除率结合起来，从间质组织的血管再填充速率的半连续测量-称为血浆再填充速率- 作为病人恢复力的动态测量。检查血浆再灌注率的模式提供了一个独特的机会评价血液透析治疗过程中患者恢复力的变化，这一点尚未得到充分探索。此外，新技术的临床影响需要了解其集成到工作流程。因此，在这项工作中，我们将使用两种互补的方法。使用大型数据集，我们将检查血浆再充盈率和透析中低血压之间的关系，通过（1）确定是否低血浆再充盈率与透析中低血压的血液透析次数相关， (2)开发一个使用时间更新变量的模型，以预测透析中发生的时间低血压同时，我们将收集原始数据，以（3）评估血浆再充盈与速率和恢复时间，以及（4）探索供应商对该技术可用性的看法。通过这些并行项目，我们将提高我们对微妙的血流动力学变化的理解，这将为未来的研究提供信息。维持性血液透析中精确容量管理的研究和推动工作。此外，如果我们发现血浆再充盈率在预测透析中低血压或恢复时间中的关键作用，我们可以利用该技术的半连续性质来改变用户界面并改善护理的提供。结合临床流行病学硕士课程的正式课程，申请NRSA奖学金将为王博士提供先进的强化培训，生物统计学，统计建模的专业知识，主要数据收集，并促进建立一个透析技术和终末期肾病的研究领域。