ISSN 2097-6046（网络）
ISSN 2096-7446（印刷）
CN 10-1655/R
主管：中国科学技术协会
主办：中华护理学会
中华急危重症护理杂志

中华急危重症护理杂志 >

2026 , Vol. 7 >Issue 1: 111 - 115

DOI: https://doi.org/10.3761/j.issn.2096-7446.2026.01.018

综述

急危重症患者生成型健康数据智能监测与风险预警的研究进展

  • 周奕 ,
  • 张小红 ,
  • 段应龙 ,
  • 张文秀 ,
  • 沈志莹 ,
  • 董小倩 ,
  • 谢建飞
展开
  • 1.中南大学湘雅三医院护理部 长沙市 410013
    2.中南大学湘雅三医院妇科 长沙市 410013
    3.中南大学湘雅三医院重症医学科 长沙市 410013
    4.中南大学湘雅三医院骨科 长沙市 410013
    5.中南大学湘雅三医院血液内科 长沙市 410013
    6.中南大学湘雅护理学院 长沙市 410013
周奕：女，硕士，护师，E-mail：yi.zhou@csu.edu.cn
*谢建飞，E-mail：xiejianfei@csu.edu.cn

收稿日期: 2025-03-16

  网络出版日期: 2026-01-06

基金资助

湖南省自然科学基金-杰出青年基金项目(2022JJ10098)

收起

Research progress on intelligent monitoring and risk warning of patient-generated health data in critically ill patients

  • ZHOU Yi ,
  • ZHANG Xiaohong ,
  • DUAN Yinglong ,
  • ZHANG Wenxiu ,
  • SHEN Zhiying ,
  • DONG Xiao-qian ,
  • XIE Jianfei
Expand
  • 1. Nursing Department， the Third Xiangya Hospital，Central South University， Changsha 410013， China
    2. Department of Gynecology， the Third Xiangya Hospital，Central South University， Changsha 410013， China
    3. Department of Emergency and Critical Care Medicine， the Third Xiangya Hospital，Central South University， Changsha 410013， China
    4. Department of Orthopaedics， the Third Xiangya Hospital，Central South University， Changsha 410013， China
    5. Department of Hematology， the Third Xiangya Hospital，Central South University， Changsha 410013， China
    6. Xiangya School of Nursing， Central South University， Changsha 410013， China

Received date: 2025-03-16

  Online published: 2026-01-06

Supported by

Hunan Natural Science Foundation-Distinguished Young Scholars(2022JJ10098)

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摘要

患者生成型健康数据（patient-generated health data，PGHD）在急危重症早期识别与风险预警中扮演核心角色，但传统监测技术存在采集指标单一、精度不稳定等局限性，难以应对急危重症患者复杂、动态、多维度的监测需求。护理新材料凭借高灵敏度、可穿戴性与智能响应特性，为PGHD的连续获取与实时分析提供新途径。该文综述了护理新材料在围手术期急症监测、慢性疾病急性加重识别及肿瘤急症预警中的应用进展，重点分析其在监测精度、灵敏度及与数字技术协同的机制，评估其在临床适应性、多源数据价值转化、患者数据主权保障等方面的现实挑战，探讨护理新材料由被动响应向智能预警转型的新思路，为急危重症护理监测的精准化、智能化研究提供参考。

关键词： 新材料; 监测; 危重病护理; 患者生成型健康数据; 综述文献专题

本文引用格式

周奕 , 张小红 , 段应龙 , 张文秀 , 沈志莹 , 董小倩 , 谢建飞 . 急危重症患者生成型健康数据智能监测与风险预警的研究进展[J]. 中华急危重症护理杂志, 2026 , 7(1) : 111 -115 . DOI: 10.3761/j.issn.2096-7446.2026.01.018

Abstract

Patient-generated health data（PGHD） play a central role in the early detection and risk warning of critically ill patients. Traditional monitoring technologies，however，are limited by narrow indicator scope and unstable measurement accuracy，making them insufficient to meet the complex，dynamic，and multidimensional needs of critical care monitoring. Nursing-related innovative materials，owing to their high sensitivity，wearability，and smart responsiveness，offer a novel approach for continuous data acquisition and real-time analysis of PGHD. This review summarizes recent advances in the application of such materials for perioperative critical monitoring，acute exacerbation detection in chronic disease，and early warning in oncologic emergencies. We focus on their contributions to monitoring precision and sensitivity，and the mechanisms by which they synergize with digital technologies. We also assess real-world challenges regarding clinical adaptability，translation of multisource data into actionable value，and protection of patients’ data sovereignty. Finally，we explore a new paradigm for transforming nursing-related innovative materials from passive response toward intelligent early warning，providing a reference for future research on the precision and intelligence of critical care nursing monitoring.

Key words： Nursing-related Innovative Materials; Monitoring; Critical Care Nursing; Patient-Generated Health Data; Review Literature as Topic

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