Impact of Disparities Affecting Survival among Advanced Heart Failure Patients and Transplant Recipients

描述：当前的心脏移植分配系统和新推荐的系统 根据等待名单的存活率优先考虑患者，不考虑移植后的死亡风险， 移植的可能性。此外，它主要通过使用设备来定义移植的医疗紧急性 而不是医学疾病的客观证据。不幸的是，许多心力衰竭患者在等待名单上死亡， 包括不成比例的女性，西班牙裔和患有某些心脏病的患者，如限制性心脏病患者， 心肌病移植后也存在生存差异。该项目的长期目标是 优化晚期心力衰竭治疗的时机，以提高生存率并最大限度地减少器官浪费。的 这项研究的目的是确定心脏移植患者存活率差异的危险因素， 候选人和移植后，并创造工具，将改善治疗结果，同时最大限度地减少 器官浪费中心假设是，一个更好的心脏移植分配系统需要了解 人口差异如何影响患者选择、等待名单死亡率和移植后死亡率。的理由 因为这项拟议中的研究是，在生存率方面存在已知的差异（性别、种族和心脏病类型）， 晚期心力衰竭患者（移植前和移植后）的风险预测模型的建立 已经成功地降低了肺、肝和肾移植等待名单的死亡率。具体目标是 研究建议是：1）确定心脏移植候选人生存差异的风险因素， 移植后使用国家移植数据库2）开发一种方法来动态更新移植后的风险， 使用来自多个移植中心的数据，包括潜在的预后风险， 我们的国家移植数据库中没有的因素，3）创建一个数学模型， 估计等待名单和移植后死亡率，以优化移植时机。方法是创新的 因为它利用了新的数学方法，并试图改变目前的心力衰竭研究和临床 通过考虑人口差异而不是仅仅根据驱逐决定来实践范例 分数、冠状动脉疾病的存在和疾病的阶段。拟议的研究意义重大， 因为很少有研究探讨晚期心力衰竭的人群差异， 与等待名单上的死亡率和移植后的不良结果相关。该提案将评估 人口差异（即性别、种族、心脏病类型、器官的实验室测量）的复杂相互作用 功能障碍，以及合并症的影响），因为它们与等待名单上的死亡率，移植的时机， 和移植后的死亡率。如果我们提案的目标得以实现，我们的研究有可能 使临床医生和研究人员能够在正确的时间为正确的患者提供正确的治疗。

DESCRIPTION: The current heart transplant allocation system and the newly recommended one prioritizes patients based on waitlist survival and does not take into account risk of death after transplant or likelihood of transplantation. Furthermore, it defines medical urgency for transplantation mainly by use of devices and not by objective evidence of medical illness. Unfortunately, many heart failure patients die on the waitlist, including a disproportionate number of women, Hispanics, and patients with certain heart diseases like restrictive cardiomyopathy. After transplantation there are also survival disparities. The long-term goal of this project is to optimize timing for advanced heart failure therapy in order to improve survival and minimize organ wastage. The objective of this research application is to identify risk factors for disparities in survival among heart transplant candidates and post-transplantation and to create tools that will improve outcome in therapy while minimizing organ wastage. The central hypothesis is that a better heart transplant allocation system requires knowledge of how population differences affect patient selection, waitlist mortality, and post-transplant mortality. The rationale for the proposed research is that there are known disparities (sex, race, and type of heart disease) in survival among advanced heart failure patients (pre- and post-transplantation) and creation of risk prediction models have successfully reduced waitlist mortality for lung, liver, and kidney transplantation. The specific aims of this research proposal are: 1) to identify risk factors for disparities in survival among heart transplant candidates and post-transplantation using the national transplant database 2) to develop a method to dynamically update risk of waitlist mortality across time using data from multiple transplant centers that includes potential prognistic risk factors not available in our national transplant database and 3) to create a mathematical model that simultaneous estimates waitlist and post-transplant mortality to optimize timing of transplantation. The approach is innovative because it utilizes new mathematical approaches and seeks to shift current heart failure research and clinical practice paradigms by taking into account population differences rather than basing decisions solely on ejection fraction, presence of coronary artery disease, and stages of disease. The proposed research is significant, because few studies have explored population differences in advanced heart failure to determine the factors associated with mortality on the waitlist and poor outcome post-transplantation. This proposal will evaluate the complex interplay of population differences (i.e sex, race, type of heart disease, laboratory measures of organ dysfunction, and influences of co-morbidities) as they relate to mortality on the waitlist, timing of transplantation, and mortality after transplantation. If the aims of our proposal are achieved, our research has the potential to empower clinicians and researchers to provide the right therapies for the right patient at the right time.