Optimizing Donor Management in Lung Transplantation

项目摘要 终末期肺部疾病(ESLD)在美国影响着100多万患者，估计每年有 影响超过500亿美元。肺移植(LT)是治疗ESLD的唯一治疗方法，可提高存活率 以及生活质量。供体器官的匮乏仍然是更广泛应用的主要障碍 中校。尽管存在这种差异，但只有20%的脑死亡捐赠者被考虑接受移植。 供者肺利用率低的主要原因有两个。首先，虽然国际 心脏和肺移植学会提出了肺捐赠者评估指南，这些 建议相当广泛，并且以不同的方式实现，这导致了 对潜在移植器官的评估。不幸的是，没有经过验证的仪器可用 告知供者肺的利用情况，从而阻碍有限资源的优化。第二，中国经济的影响 供体质量对肝移植术后早期移植物功能的影响尚不清楚。肝移植导联术后严重的原发移植物功能障碍 导致显著的发病率和死亡率，并降低长期存活率。与重度PGD相关的供体因素 仍然没有得到充分的了解，并导致在决定接受器官方面进一步不确定。 在这项提案中，我们将解决全国肺利用率低的两个主要原因。 目的1：建立和验证脑死亡供体肺利用的预测模型。与 访问预期维护的大型数据库，为以下捐赠者提供详细的捐赠者级别信息 接受或拒绝接受肺移植，我们将使用多变量分析来创建预测模型 脑死亡捐赠者利用肺的可能性。诺模图将独立开发和验证 来自其他器官采购组织的队列，并以电子应用程序的形式提供。 目的2：了解供体因素对肺移植受者早期预后的影响。我们 将在三个有良好维护的数据库的合作OPO评估肺捐赠者。有关以下内容的详细信息 受助者的90天结果将从机构和国家登记数据中获得。我们将发展 多变量模型了解供者临床和CT扫描影像特征对风险的影响 肝移植术后早期移植物功能障碍和90天死亡率。这些模型将经过外部验证，并将用于 以产生一个可以预测移植后肺功能的捐赠者评分。 通过开发一种工具来指导移植供者的选择，并通过描述影响早期影响的供者特征 关于移植受者的结局，我们将为任何评估供体提供的临床医生解决两个关键问题： 我们接受这些肺吗？它们会充分发挥作用吗？我们的发现将很容易被纳入常规捐赠者 并将指导LT临床医生和政策制定者对稀缺资源进行最佳管理。模特们 所开发的技术也很容易适用于其他固体器官移植。

Project Summary End-stage lung disease (ESLD) affects over 1 million patients in the U.S. and has an estimated annual economic impact exceeding $ 50 billion. Lung transplantation (LT), the only curative therapy for ESLD, improves survival as well as quality of life. Scarcity of donor organs remains the predominant barrier towards wider application of LT. Despite this discrepancy, only 20% of brain dead donors are considered for LT. Two predominant factors account for the low lung utilization rates in donors. Firstly, though the International Society for Heart and Lung Transplantation has proposed guidelines for lung donor assessment, these recommendations are fairly broad and are variably implemented, leading to significant heterogeneity in assessment of organs for potential transplantation. Unfortunately, there are no validated instruments available to inform donor lung utilization, thereby hampering optimization of a limited resource. Secondly, the impact of donor quality on early graft function after LT is unknown. Severe primary graft dysfunction (PGD) after LT leads to significant morbidity and mortality and lowers long-term survival. Donor factors associated with severe PGD remain inadequately understood and lead to further uncertainty in the decision to accept organs. In this proposal we will address both the principal reasons for low lung utilization rates nationally. Aim 1: To develop and validate a predictive model for lung utilization in brain dead donors. With the access to large, prospectively maintained database providing detailed donor level information for donors whose lungs were accepted or declined for LT, we will use multivariable analyses to create a predictive model for likelihood of lung utilization from a brain dead donor. A nomogram will be developed and validated in independent cohorts from other organ procurement organizations (OPOs) and presented as an electronic app. Aim 2: To understand the impact of donor factors on early outcomes in lung transplant recipients. We will evaluate lung donors at three collaborating OPOs with well-maintained databases. Detailed information on 90-day outcomes in recipients will be obtained from institutional and national registry data. We will develop multivariable models to understand the impact of donor clinical and CT scan imaging characteristics on the risk of early graft dysfunction and 90-day mortality after LT. The models will be externally validated and will be used to generate a donor score that can predict lung performance after transplant. By developing a tool to guide donor selection for LT and by delineating donor characteristics that impact early outcomes in LT recipients, we will address two critical questions for any clinician evaluating a donor offer: Can we accept these lungs? Will they function adequately? Our findings will be easily incorporated into routine donor care and will guide LT clinicians and policymakers in optimal management of a scarce resource. The models developed would also be readily adaptable for other solid organ transplants.