Identifying Healthy and High-Risk Weight Loss Phenotypes to Optimize Obesity Management in End Stage Kidney Disease

识别健康和高风险的减肥表型以优化终末期肾病的肥胖管理

基本信息

批准号：
10405626
负责人：
Meera Nair Harhay
金额：
$ 27万
依托单位：
DREXEL UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-06-01 至 2025-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10405626
关键词：
Benefits and Risks Biological Markers Blood Pressure Body Composition Body Weight Body Weight decreased Body mass index Caring Cessation of life Characteristics Chronic Chronic Disease Clinical Confidence Intervals Consensus Data Data Set Dialysis patients Dialysis procedure Dietitian End stage renal failure Enrollment Ensure Foundations Goals Guidelines Health Health Status Hemodialysis Hospitalization Individual Inflammation Inflammatory Intake Interview Joints Kidney Kidney Diseases Kidney Transplantation Kilogram Knowledge Link Longitudinal Studies Machine Learning Malnutrition Measures Medical Modeling Muscle function Muscular Atrophy Nephrology Non obese Nutritional Obesity Outcome Patient-Centered Care Patients Persons Phenotype Physicians Physiological Population Process Prospective cohort study Provider Quality of life Reporting Research Research Proposals Risk Risk Factors Science Services Structure Techniques Transplant Recipients United States Vulnerable Populations Weight adverse outcome clinical care clinical predictors cohort data registry experience hazard health related quality of life healthy weight hemodynamics high risk improved improved mobility inflammatory marker machine learning algorithm meter morphogens mortality mortality risk muscle form muscle strength novel nutrition obese patients obese person obesity management patient oriented patient population predictive modeling predictive tools prevent prospective reduced muscle strength sarcopenia sleep quality stakeholder perspectives tool weight loss intervention

项目摘要

Project Summary/Abstract In 2016, 47,000 individuals who initiated dialysis in the United States (~42% of all incident dialysis patients that year) had obesity, with a body mass index (BMI) of ≥ 30 kilograms per meters squared. Across the BMI spectrum, individuals with kidney disease commonly lose weight after initiating dialysis treatment. However, whereas body weight typically stabilizes after the first several months of dialysis among patients without obesity, those with obesity often continue to lose weight. Both people with and without obesity who are on dialysis may lose weight due to muscle wasting and malnutrition, and recent studies have identified weight loss as a risk factor for death among people on dialysis, independent of BMI. Yet, some of the weight loss observed among obese dialysis patients may also reflect deliberate attempts to improve health, mobility, or access to kidney transplantation. Currently, there are no guidelines to help clinicians to differentiate between healthy and high-risk weight loss among people with obesity on dialysis. Further, typical obesity management paradigms are not easily transferrable to obese people with end-stage kidney disease, given factors such as chronic malnutrition, inflammation, and sarcopenia in this population that may modify the risks and benefits of different weight loss strategies. Therefore, the overarching goal of this five-year research proposal is to define healthy and high-risk weight loss phenotypes among people with obesity who are on dialysis, and to provide clinically feasible tools to improve obesity management in the setting of end-stage kidney disease. We will accomplish this goal by conducting three distinct but interrelated studies. In the first study, we will qualitatively determine patient-prioritized endpoints of weight loss, in addition to patient, physician and other stakeholder perspectives on the key factors that differentiate healthy from high-risk weight loss on dialysis. In the second study, we will leverage a national dataset of 23,000 obese dialysis patients and apply constructs of high and low physiologic reserve to derive healthy and high-risk weight loss phenotypes. We will then develop a weight- loss risk calculator tool that predicts the risks of hospitalization and death that are associated with each weight loss phenotype, using dynamic predictive joint models and machine learning techniques. In the third study, we will enroll 250 obese dialysis patients in a prospective, longitudinal study across five regions in the United States to evaluate the association between nutritional, inflammatory, and hemodynamic biomarkers and measures of health trajectory that are not typically captured in registry data, such as sarcopenia, dynapenia, body composition, and patient-prioritized endpoints such as quality of life. In accomplishing its aims, this research will provide urgently needed knowledge and tools that will improve the medical management of tens of thousands of people with end-stage kidney disease and obesity, ensuring that clinicians will be better able to incorporate patient-prioritized outcomes into assessments of weight loss interventions, and recognize and mitigate the effects of high-risk weight loss.

项目摘要/摘要 2016年，在美国发起透析的47,000个人（占所有事件透析的42％那年的患者患有肥胖症，每米平方的体重指数（BMI）为≥30公斤。穿过 BMI频谱，患有肾脏疾病的个体通常在开始透析治疗后体重减轻。但是，而体重通常在患者的前几个月后稳定没有肥胖症的人，肥胖者经常继续减肥。有和没有肥胖症的人都是在透析上可能由于肌肉浪费和营养不良而减肥，最近的研究已经确定了体重损失是透析人群中死亡的危险因素，独立于BMI。但是，一些减肥在肥胖的透析患者中观察到的也可能反映出有意改善健康，流动性或进入肾脏移植。目前，没有指导方针可以帮助临床医生区分透析患有肥胖症患者的健康和高风险的体重减轻。此外，典型的肥胖管理给定因素，例如该人群中的慢性营养不良，感染和肌肉减少症可能会改变不同的减肥策略。因此，这项五年研究建议的总体目标是定义患有透析的肥胖者的健康和高风险减肥表型，并提供临床上可行的工具，可以在末期肾脏疾病的情况下改善肥胖症管理。我们将通过进行三项不同但相互关联的研究来实现这一目标。在第一项研究中，我们将定性除了患者，身体和其他利益相关者之外，确定体重减轻的终点关于将健康与透析高风险体重减轻区分开的关键因素的观点。在第二个研究，我们将利用23,000名肥胖透析患者的国家数据集，并应用高和高的结构低生理储备可得出健康和高风险的减肥表型。然后，我们将发展一个权重 - 损失风险计算器工具，可预测与每种体重相关的住院和死亡的风险损失表型，使用动态预测性关节模型和机器学习技术。在第三项研究中，我们将在联合的五个地区进行一项前瞻性的纵向研究，招募250名肥胖透析患者评估营养，炎症和血液动力学生物标志物与通常未在注册表数据中捕获的健康轨迹的度量，例如肌肉减少症，Dynapenia，身体成分和患者优先的终点，例如生活质量。在实现目标时，研究将提供急需的知识和工具，以改善数十个的医疗管理成千上万的患有末期肾脏疾病和肥胖症的人中，确保临床医生将能够更好地将患者优先的结果纳入减肥干预措施的评估，并识别和减轻高风险减肥的影响。