Renhua Lu, Yan Fang, Qisheng Lin, Yifei Lu, Yijun Zhou, Xiaojun Zeng, Tingting Liu, Wangshu Wu, Kewei Xie, Haifen Zhang, Shan Mou, Haijiao Jin, Zhaohui Ni, Leyi Gu
This trial is expected to demonstrate that the mobile intelligent hemodialysis platform can achieve high session completion rates, adequate dialysis efficiency, and a safety profile comparable to conventional center-based dialysis. If validated, this platform has the potential to improve service accessibility, reduce indirect costs, enhance patient autonomy, and provide a resilient dialysis option in public health emergencies and disaster settings, representing a meaningful paradigm shift in dialysis care delivery.
INTRODUCTION: End-stage kidney disease (ESKD) is a growing global public health burden, with millions of patients dependent on maintenance hemodialysis (MHD). Conventional center-based MHD imposes significant constraints on patient flexibility, accessibility, and quality of life, while home hemodialysis faces substantial implementation barriers in China. Advances in digital health technologies - including artificial intelligence, internet of things (IoT), and real-time data analytics - offer opportunities to fundamentally transform dialysis care delivery. This study presents the protocol for the first clinical trial evaluating a mobile intelligent hemodialysis platform in mainland China.
METHODS: This is a prospective, single-center, exploratory clinical trial to be conducted at Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine. Twenty adult ESKD patients (aged 18-75 years) receiving regular MHD 3 times weekly for at least 3 months will be enrolled. Participants will undergo a single 4-h hemodialysis session on the mobile intelligent dialysis platform, a specialized medical vehicle integrating water purification, dialysis equipment, and an intelligent clinical decision support system across six functional zones. The primary endpoint is the successful session completion rate, defined as completion without platform-related technical failure or premature termination. Secondary endpoints include dialysis adequacy (urea reduction ratio ≥65%; Kt/V >1.2), hemodynamic stability, and pre- to post-dialysis changes in biochemical parameters. Safety assessments include continuous vital sign monitoring and adverse event grading according to Common Terminology Criteria for Adverse Events (CTC-AE) version 4.0. The study has been approved by the Ethics Committee of Ren Ji Hospital (approval number: LY2024-313-A) and registered in the Chinese Clinical Trial Registry (ChiCTR2500100356).
CONCLUSION: This trial is expected to demonstrate that the mobile intelligent hemodialysis platform can achieve high session completion rates, adequate dialysis efficiency, and a safety profile comparable to conventional center-based dialysis. If validated, this platform has the potential to improve service accessibility, reduce indirect costs, enhance patient autonomy, and provide a resilient dialysis option in public health emergencies and disaster settings, representing a meaningful paradigm shift in dialysis care delivery.