The impact of body composition on peri-operative and patient-centered outcomes in lung transplantation.

项目摘要 肺移植的目的是延长生存时间，减轻残疾，提高健康相关生活质量(HRQL)。 尽管许多人做得很好，但围手术期并发症有所增加，三分之一的患者在前三年内死亡。 移植后数年和20-40%的幸存者没有报告患者报告的结果(PRO)有所改善 如功能和HRQL。这种缺乏改善的原因通常是未知的。因此，RFA- 022-002强调身体成分和职业作为进一步调查和干预的关键优先领域。 在使用BMI、CT扫描和DXA的早期工作中，我们的研究小组表明肥胖和骨质疏松症在肺部普遍存在 并且是脆弱、原发移植物功能障碍(PGD)和死亡率的危险因素。我们也 强调了更广泛地实施这些模式的挑战，并引入了生物电阻抗 (BIA)作为一种先进的身体成分量化方法，克服了这些挑战。我们 BIA证明肥胖和石棺减少是PGD和等待死亡的危险因素。我们的预赛 数据表明，骨质型肥胖可能是一种新的表型，其围手术期风险较高。 并发症。移植后，PGD和其他围术期并发症会导致残疾、HRQL差、 移植后死亡。尽管PRO在临床上处于首位，但关于PERS影响的唯一经验数据 围手术期并发症来自于我们的单中心工作。专业人士需要响应的数据 缺乏围手术期并发症，阻碍了知情选择用于未来研究的PRO。最后， 定义从移植前到移植后早期影响专业人员的因素和事件 确定干预目标的优先顺序，并通过预测丰富提高临床试验效率。致信地址 在这些问题上，我们将招募803名肺移植候选人，并在目标1中定义骨钙素的影响 围手术期和产后6个月的肥胖、骨质疏松症和肥胖症。我们假设有石棺生成 肥胖会增加围术期并发症的风险，包括PGD，即使在正常的患者中也是如此 体重指数。在目标2中，我们将定义PRO措施对PGD和其他围手术期的反应性 并发症。目标2将提供必要的基础经验数据，以便为以下项目提供适当的专业选择 未来的观察性和干预性研究。目标3，将开发里程碑式的预测模型 术前、围手术期和术后早期的因素，以确定术后6个月和时间预后较差的组 移植后长达3年的移植失败。建立围手术期和术后早期预后的新模型 预测哪些人有不良结局的风险将为所需的预后充实策略提供信息。 提高肺移植临床试验效率。总之，我们通过以下方式解决RFA HL-22-022中的关键优先事项 以创新和可扩展的方式检查身体成分；为未来的研究确定高收益的专业人员 并产生基础知识，为未来的肺移植研究和试验提供信息。

PROJECT ABSTRACT Lung transplantation aims to extend survival, relieve disability, and improve health-related quality of life (HRQL). Although many do well, perioperative complications have increased, one third of patients die within the first three post-transplant years and 20-40% of survivors do not report improvements in patient-reported outcomes (PROs) such as functioning and HRQL. Reasons for this lack of improvement are generally unknown. As a result, RFA- 022-002 highlights body composition and PROs as key priority areas for further investigation and intervention. In earlier work using BMI, CT scans, and DXA, our group showed that obesity and sarcopenia are prevalent in lung transplant candidates and are risk factors for frailty, primary graft dysfunction (PGD), and mortality. We also highlighted, the challenges to more widely implementing these modalities and introduced bioelectrical impedance (BIA) as a method of advanced body composition quantification that overcomes these challenges. We demonstrated that obesity and sarcopenia by BIA are risk factors for PGD, and wait-list death. Our preliminary data suggests that sarcopenic obesity may be a novel phenotype at heightened risk for perioperative complications. After transplant, PGD and other perioperative complications contribute to disability, poor HRQL, and death after transplant. Despite the clinical primacy of PROs, the only empirical data on the impact of perioperative complications on PROs comes from our single-center work. Data on which PROs are responsive to perioperative complications is lacking, hindering informed selection of PROs for use in future research. Finally, defining the factors and events from before through early after transplant that impact PROs can identify and prioritize targets for intervention and improve clinical trial efficiency through prognostic enrichment. To address these problems, we will enroll 803 lung transplant candidates and, in Aim 1, will define the impact of sarcopenic obesity, sarcopenia, and adiposity on peri-operative and PROs at 6-months. We hypothesize that sarcopenic obesity will confer heightened risk for perioperative complications, including PGD, even in patients with normal BMI. In Aim 2, we will define the responsiveness of PRO measures to PGD and other perioperative complications. Aim 2 will provide the foundational empirical data needed to inform appropriate PRO selection for future observational and interventional studies. Aim 3, will develop landmark prediction models accounting for pre-, peri- and early post-operative factors to identify groups with worse post-operative PROs at 6-months and time to graft failure up to 3-years after transplant. Developing new modeling of peri- and early post-operative outcomes to predict which individuals are at risk for poor outcomes will inform the prognostic enrichment strategies needed to improve clinical trial efficiency in lung transplant. In sum, we address key priorities in RFA HL-22-022 by examining body composition in an innovative and scalable manner; identifying high yield PROs for future studies and generating foundational knowledge to inform future studies and trials in lung transplantation.