Redefining cardiovascular risk assessment in dialysis patients (ROCK-D) study

项目总结/摘要 目前尚无针对慢性肾病（CKD）患者的心血管（CV）风险预测工具 在临床实践中，事实上，CKD患者CV风险分层的最佳方法尚不确定， 由于缺乏公开的数据而备受争议和混淆。传统的风险预测模型 CKD患者CV事件的预测准确性失败，低估风险高达50%。这是 这是非常有问题的，因为CVD是CKD死亡的主要原因。这迫使临床医生 考虑替代方法，如冠状动脉钙化（CAC）评分评估（通过 心脏CT）或心肌纤维化（通过原生T1 MRI）作为风险分层工具，但是， 关于其在CKD中的预后效用的相当大的临床平衡。此外，新出现的证据表明， 提示静息状态下CV结构的评估，而不是在压力下确定功能， 运动，可能不足以准确反映CKD中过早CV死亡的风险。虽然 运动已被证明是未来CV事件的最有效预测因素之一，但很少在 CKD患者。我们小组最近的工作表明，CV功能能力的全球指数（如 通过运动峰值时的摄氧量（VO 2）进行评估），使用心肺运动试验（CPET）可提供 准确评估CKD患者CV风险的潜在解决方案。如果CPET可以用来准确预测 未来的心血管事件和风险分层CKD患者，这可能会改变实践的影响。潜在 应用包括识别患者以进行更早或更密集的医疗或透析治疗， 在术前风险评估中， 大手术，并帮助指导选择患者进行冠状动脉造影。的总体目标 因此，拟定的研究旨在确定CV风险的最佳诊断试验和CV功能指数 歧视和歧视。该建议的中心假设是， 在预测晚期心血管疾病患者未来的CV事件方面，CPET将优于其他诊断性试验上级。 CKD。本研究是一项概念验证的单中心前瞻性研究，将招募总共n=140例 不同种族和人种的晚期CKD 5D期（血液透析）患者。所有患者将进行 功能（身体功能测试和CPET）和结构（心脏CT和T1 MRI）评估， 基线和1年时重复功能测试。将在3年时前瞻性评估CV结局。 AIM 1（A）将确定与其他临床使用的测试（心脏CT， T1 MRI，身体功能测试），用于预测3年时的CV结局;以及（B）确定 在预测3年时的心血管结局方面，VO 2 Peak优于单基线VO 2 Peak（上级）。 AIM 2将开发一种新的风险分层模型，并评估纳入功能指数是否可以 与传统风险评分相比，CKD患者未来心血管结局的预测性更好。

PROJECT SUMMARY/ABSTRACT There are currently no cardiovascular (CV) risk prediction tools for patients with Chronic Kidney Disease (CKD) in clinical practice today. In fact, the optimal approach to CV risk stratification in patients with CKD is uncertain, highly contested and confounded by a paucity of published data. Furthermore, traditional risk prediction models fail in their predictive accuracy for CV events in patients with CKD, underestimating risk by up to 50%. This is exceedingly problematic, given that CVD is the leading cause of death in CKD. This has forced clinicians to consider alternative approaches such as the assessment of coronary artery calcification (CAC) score (by cardiac CT) or myocardial fibrosis (by native T1 MRI) as risk stratification tools, however there remains considerable clinical equipoise regarding their prognostic utility in CKD. Moreover, emerging evidence suggests that evaluation of CV structure at rest rather than ascertainment of function under the stress of exercise, may be insufficiently sensitive to accurately reflect the risk of premature CV death in CKD. Although exercise has been shown to be among the most potent predictors of future CV evens, it is rarely assessed in patients with CKD. Recent work by our group suggests that global indices of CV functional capacity (as assessed by oxygen uptake (VO2) at peak exercise) using cardiopulmonary exercise testing (CPET) may offer a potential solution for accurately prognosticating CV risk in CKD. If CPET could be used to accurately predict future CV events and risk stratify CKD patients, this could have practice changing implications. Potential applications include the identification of patients for earlier or more intensive medical or dialytic therapies, in the selection and prioritization of patients for timely kidney transplantation, in pre-operative risk assessment for major surgery and to help guide the selection of patients for coronary angiography. The overall aim of the proposed study is therefore to define the optimal diagnostic test and CV functional index for CV risk discrimination and prognostication. The central hypothesis of this proposal is that measurement of VO2Peak by CPET will be superior to other diagnostic tests for predicting future CV events in patients with advanced CKD. The present study is a proof-of-concept single-center prospective study that will recruit a total of n=140 racially and ethnically diverse advanced CKD stage 5D (hemodialysis) patients. All patients will undergo functional (physical function testing and CPET) and structural (cardiac CT and T1 MRI) assessments at baseline and repeat functional testing at 1-year. CV outcomes will be assessed prospectively at 3-years. AIM 1 (A) will determine the predictive value of VO2Peak compared to other clinically used tests (cardiac CT, T1 MRI, physical function testing) for predicting CV outcomes at 3-years; and (B) determine if changes in VO2Peak is superior to single baseline VO2Peak for predicting cardiovascular outcomes at 3-years. AIM 2 will develop a new risk stratification model and assess whether the inclusion of functional indices can better prognosticate future cardiovascular outcomes in CKD compared to traditional risk scores.