Early Detection of Right Ventricular Dysfunction and Emerging Pulmonary Hypertension in Systemic Sclerosis

肺动脉高压(PAH)是一种发病率很高的疾病，通常会使患者并发 自身免疫性疾病系统性硬化症(SSC)，是导致这一人群死亡的主要原因。正确的 心室(RV)对后负荷进行性增加的适应是SSC预后的主要决定因素 尽管指南推荐的早期检测算法旨在识别PAH和治疗 PAH的治疗进展，SSC患者往往诊断较晚，死亡率居高不下 很高。虽然有几种策略可用，但现有的筛查算法预测准确率较低。 因此，尚未得到满足的需要是更好地描述SSc的高危表型，并改进亚群的识别 当治疗干预可能影响预后时，在病程早期发生PAH的风险最大。这 研究旨在通过提供非侵入性和客观的预后定量成像标志物来填补这一空白 以及使用复杂的生物统计和机器学习(ML)技术的基于轨迹的亚型分析， 能够及早识别处于不利长期后果风险中的亚人群。利用小说 超声心动图技术，我们最近发现了右室收缩能力和收缩储备的早期变化 在SSC发展为显性多环芳烃之前。根据这些发现，在目标1中，我们将具体 确定在标准筛查中加入房室收缩的回声衍生参数是否可以 确定不同的临床表型和PAH发展的高风险轨迹，同时表征 这些轨迹的性质和相互作用跨越每个变量。我们的方法将结合ML 用贝叶斯多元线性混合建模改进同类的表征和表型 亚组以及轨迹如何呈现不良事件的独特风险。目标2侧重于生物 房室水平同时直接测量房室收缩的回声技术的验证 储备和RV-动脉偶联以确定RVLSS是否是RV收缩性能的无创性替代物 和房室收缩储备。我们的协同和互补目标将用于派生和验证 AIM 3中稳健的早期检测策略，改进了现有的筛查方法，使早期 SSC中多环芳烃的预测。我们在研究这些关键问题方面处于独特的地位，因为我们可以访问其中一个 在世界上规模最大、表型精良的SSC队列中，我们在 SSC中RV功能的无创和有创评估，以及我们在复杂多方面的专业知识 完成这一项目所需的方法。RV适应不良的早期识别和特征 对于新出现的肺血管疾病将在SSc的临床治疗中产生革命性的作用，a 心肺疾病发病率和死亡率极高的人群。如果成功，我们的 研究结果也可能适用于其他有PAH发展风险的队列，以允许更早的 检测和早期干预。

Pulmonary arterial hypertension (PAH) is a highly morbid disease that commonly complicates patients with the autoimmune disease systemic sclerosis (SSc) and is a leading cause of death in this population. Right ventricular (RV) adaptation to progressive increases in afterload is the main determinant of outcome in SSc and despite guideline-recommended early detection algorithms designed to identify PAH and therapeutic advances in the treatment of PAH, SSc patients are often diagnosed late, and mortality remains exceedingly high. Although several strategies are available, existing screening algorithms have low predictive accuracy. Thus, an unmet need to better delineate high-risk phenotypes in SSc and improve identification of subgroups at greatest risk of PAH earlier in the disease course when therapeutic interventions may affect prognosis. This research aims to fill this gap by providing noninvasive and objective prognostic quantitative imaging markers and trajectory-based subtype analysis using sophisticated biostatistical and machine-learning (ML) techniques, enabling early identification of subpopulations at risk for adverse, long-term outcomes. Utilizing novel echocardiographic techniques, we recently identified early changes in RV contractility and contractile reserve in SSc prior to the development of overt PAH. Drawing from these findings, in Aim 1, we will specifically determine whether the addition of echo-derived parameters of RV contractility to standard screening can identify distinct clinical phenotypes and high-risk trajectories in the development of PAH, while characterizing the nature and interaction of these trajectories across each of the variables. Our methodology will combine ML with Bayesian multivariate linear mixed modeling to improve characterization and phenotyping of similar subgroups and how trajectories present unique risk for adverse events. Aim 2 focuses on the biologic validation of echo-derived techniques with simultaneous direct chamber-level measures of RV contractile reserve and RV-arterial coupling to determine whether RVLSS is a noninvasive surrogate for RV contractility and RV contractile reserve. Our synergistic and complementary aims will be used to derive and validate a robust early detection strategy in Aim 3, improving upon existing screening methods, enabling the early prediction of PAH in SSc. We are uniquely positioned to study these critical questions given our access to one of the largest and finely phenotyped SSc cohorts in the world, our strong track record of excellence in the noninvasive and invasive assessment of RV function in SSc, and our expertise in the complex multifaceted methodology necessary to complete this project. Early identification and characterization of RV maladaptation to emerging pulmonary vascular disease would be transformative in the clinical management of SSc, a population with exceedingly high morbidity and mortality from cardiopulmonary disease. If successful, our findings may also be applicable to other cohorts who are at-risk for the development of PAH to allow for earlier detection and earlier intervention.