Optimizing Donor Management in Lung Transplantation

项目摘要 在美国，终末期肺病（ESLD）影响超过100万患者，并且估计每年的经济损失为100万美元。 影响超过500亿美元。肺移植（LT）是治疗ESLD的唯一有效疗法，可提高生存率 以及生活质量。捐赠器官的稀缺仍然是更广泛应用 中尉尽管存在这种差异，但只有20%的脑死亡供体被认为是LT。 两个主要因素导致供体肺利用率低。首先，虽然国际 心脏和肺移植协会提出了肺供体评估指南， 这些建议相当广泛，而且执行得很慢，导致了 评估潜在的移植器官。不幸的是，没有经过验证的仪器可用 从而妨碍有限资源的优化。第二，影响 供体质量对LT后早期移植物功能的影响尚不清楚。LT电极导线后的严重原发性移植物功能障碍（PGD） 导致严重的发病率和死亡率，并降低长期生存率。与重度PGD相关的供体因素 人们对器官移植的认识仍然不足，并导致在决定接受器官移植时出现进一步的不确定性。 在本提案中，我们将解决全国肺利用率低的两个主要原因。 目的1：建立并验证脑死亡供体肺利用的预测模型。与 可使用大型的、预先维护的数据库，为以下捐助者提供详细的捐助者信息： 肺接受或拒绝LT，我们将使用多变量分析来创建预测模型， 利用脑死亡供体肺的可能性将独立开发和验证列线图 来自其他器官采购组织（OPO）的队列，并作为电子应用程序呈现。 目的2：了解供体因素对肺移植受者早期预后的影响。我们 将在三个具有良好维护数据库的合作OPO评估肺供体。详细资料说明 90-将从机构和国家登记数据中获得接受者的日结果。我们将开发 多变量模型，以了解供体临床和CT扫描成像特征对风险的影响 早期移植物功能障碍和LT后90天的死亡率。这些模型将在外部进行验证， 以生成供体评分，从而预测移植后的肺功能。 通过开发一种工具来指导LT的供体选择，并通过描述影响早期的供体特征， 在LT接受者的结果，我们将解决两个关键问题，任何临床医生评估捐赠者提供： 我们接受这些肺吗它们能充分发挥作用吗？我们的研究结果将很容易纳入常规捐赠 护理，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。模型 所开发的技术也很容易适用于其他实体器官移植。

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.