基于多模态神经影像联合肌电信号的尿毒症瘙痒早期预测研究

尿毒症瘙痒（uremic pruritus，UP）是令终末期肾病（end-stage renal disease，ESRD）患者最感到不适的伴随症状之一，目前尚无有效的治疗手段。根据UP的流行病学报告，41.7%的ESRD患者在透析过程中伴随瘙痒症状。此外，已证实痒的根本原因是外周传导和中枢神经回路异常，这为诊断和治疗瘙痒提供新的理论依据。本项目以即将进行透析治疗的ESRD患者为研究载体，设计纵向观察实验，借助磁共振神经影像技术，结合面部肌电，探索透析治疗中出现UP的ESRD患者外周神经传导和中枢神经系统的发展变化。结合机器学习算法，预测透析治疗过程中ESRD患者是否出现瘙痒这一负性事件，并获取敏感、鲁棒的瘙痒风险预测标记。本项目的顺利实施可为ESRD患者透析治疗过程中瘙痒风险提供更为准确的参考依据，可能为临床治疗UP提供新的治疗靶点。

Uremic pruritus (UP) is one of a frequent and compromising symptom in patients with end-stage renal disease, lacking an effective treatment modalities currently. Based on the comprehensive epidemiologic data, in which 41.7% of dialysis patients with ESRD reported moderate to extreme pruritus. In addition, studies have confirmed that the cause of pruritus was concerned with abnormal peripheral conduction and central nervous circuits, which provides a new theoretical basis for the diagnosis and treatment of pruritus. The current project focuses on tracking the high-risk population of UP in ESRD patients in a longitude study. Firstly, by combining neuroimaging and facial electromyogrphy, we aim to explore the trajectory of peripheral conduction and central nervous system changes in ESRD patients with UP during dialysis. Subsequently, we aim to identify sensitive and robust markers for predicting high-risk ESRD patients developing UP during dialysis. This project can provide more evidence to ealy identify patients who are prone to develope UP in ESRD patients during dialysis, and may facilitate the potential therapeutic target for this disease.