• 智慧感染重症平台在综合救治重症发热伴血小板减少综合征患者中的临床研究
  • 陈广.智慧感染重症平台在综合救治重症发热伴血小板减少综合征患者中的临床研究[J].内科急危重症杂志,2025,31(2):119-125
    DOI:10.11768/nkjwzzzz20250205
    中文关键词:  重症发热伴血小板减少综合征  设备物联  智慧感染重症信息系统  智慧感染重症平台  病死率
    英文关键词:
    基金项目:国家十四五重点研发项目(2021YFC2600200)
    作者单位E-mail
    陈广 华中科技大学同济医学院附属同济医院 qning@vip.sina.com;liaojiazhi@tjh.tjmu.eud.cn 
    摘要点击次数: 274
    全文下载次数: 394
    中文摘要:
          摘要 目的:智慧感染重症平台的建设及比较其应用前后综合救治重症发热伴血小板减少综合征(SFTS)患者病死率的差异。方法:针对多类床旁设备建立智慧重症设备物联平台,通过集成设备物联平台、电子病历系统等建立智慧感染重症信息系统,进而整合为智慧感染重症平台。回顾性研究共纳入110例同济医院感染科ICU重型/危重型SFTS患者,分为非平台组和平台组,探讨其对患者病死率的影响。结果:本研究率先构建了智慧感染重症平台,实现多设备信息互通及集成展示,通过对多源异构数据的采集与分析,自动评估疾病进展、临床预后和死亡风险,及时预警以完善个体化诊疗方案。应用智慧感染重症平台后,危重型SFTS患者病死率显著下降接近30%。结论:智慧感染重症平台通过全面监测、远程监护与协作、智能化预警,协助制定个体化诊疗方案,显著降低了危重症SFTS的病死率。
    英文摘要:
          Abstract Objective: To build an intelligent platform for severe infection and to compare the mortality rates of patients with severe fever with thrombocytopenia syndrome (SFTS) before and after the implementation of this platform. Methods: An intelligent Internet of Things (IoT) platform for critical care equipment has been established by connecting multiple types of bedside devices. Furthermore, a smart infection critical care information system has been developed by merging the equipment IoT platform with the electronic medical record system, eventually integrating into an intelligent platform for severe infection. A total of 110 severe and critically ill patients with SFTS in the Intensive Care Unit (ICU) of the Department of Infectious Diseases of Tongji Hospital were included in this retrospective study, and were divided into non-platform group and platform group to explore the effect of intelligent platform on the mortality rate of patients. Results: In this study, we have developed the first intelligent platform for severe infection, which efficiently facilitates the information exchange and connects multiple equipment, creating a full-device, full-process, and holographic database. This platform can automatically assess disease progression, clinical prognosis, and mortality risk, and provide timely warnings to enhance personalized diagnostics and treatment strategies. The case fatality rate of critically ill patients with severe SFTS decreased significantly by nearly 30%. Conclusion: The intelligent platform for severe infection integrates comprehensive and remote monitoring, and automatic early warning systems.This platform can assist clinicians in formulating personalized diagnostics and treatment strategies, and effectively reduce the mortality rate of critically ill patients with SFTS.