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中华重症医学电子杂志 ›› 2025, Vol. 11 ›› Issue (03) : 238 -243. doi: 10.3877/cma.j.issn.2096-1537.2025.03.005

临床研究

实时重症预警平台对骨科创伤患者预后的影响
吴昌德1, 杨辉2, 刘灵娟1, 朱玉芬1, 黄力维1, 刘松桥1,3, 杨毅1,()   
  1. 1 210009 南京,江苏省重症医学重点实验室 东南大学附属中大医院重症医学科
    2 242000 安徽宣城,安徽省宣城市人民医院重症医学科
    3 222000 江苏连云港,连云港市第一人民医院 徐州医科大学附属连云港医院 南京医科大学康达学院第一附属医院 南京医科大学连云港临床医学院
  • 收稿日期:2024-11-15 出版日期:2025-08-28
  • 通信作者: 杨毅
  • 基金资助:
    江苏省重点研发计划项目(BE2022854); 安徽省临床医学研究转化专项(202304295107020070)

Impact of a real-time critical care early warning platform on clinical outcomes in orthopedic trauma patients

Changde Wu1, Hui Yang2, Lingjuan Liu1, Yufen Zhu1, Liwei Huang1, Songqiao Liu1,3, Yi Yang1,()   

  1. 1 Jiangsu Provincial Key Laboratory of Critical Care Medicine, Department of Critical Care Medicine, Zhongda Hospital, School of Medicine, Southeast University, Nanjing 210009, China
    2 Department of Intensive Care Unit, Xuancheng People's Hospital, Xuancheng 242000, China
    3 the First People's Hospital of Lianyungang, the Affiliated Lianyungang Hospital of Xuzhou Medical University, the First Affiliated Hospital of Kangda College of Nanjing Medical University, the Lianyungang Clinical College of Nanjing Medical University, Lianyungang 222000, China
  • Received:2024-11-15 Published:2025-08-28
  • Corresponding author: Yi Yang
引用本文:

吴昌德, 杨辉, 刘灵娟, 朱玉芬, 黄力维, 刘松桥, 杨毅. 实时重症预警平台对骨科创伤患者预后的影响[J/OL]. 中华重症医学电子杂志, 2025, 11(03): 238-243.

Changde Wu, Hui Yang, Lingjuan Liu, Yufen Zhu, Liwei Huang, Songqiao Liu, Yi Yang. Impact of a real-time critical care early warning platform on clinical outcomes in orthopedic trauma patients[J/OL]. Chinese Journal of Critical Care & Intensive Care Medicine(Electronic Edition), 2025, 11(03): 238-243.

目的

探讨实时重症预警平台在骨科创伤患者中的应用效果。

方法

选取东南大学附属中大医院从2020年1月至2023年12月就诊于骨科并转入ICU的患者作为研究对象。排除非创伤患者、ICU住院时间<24 h的患者。将接入预警平台的患者作为预警组(68例),未接入预警平台的患者作为非预警组(121例)。以住院时间为主要终点,通过多因素线性回归分析探讨重症预警平台与住院时间的相关性。

结果

研究共纳入189例患者,其中位年龄为72岁,女性占43.9%(83例),急诊入院占31.7%(60例),脊柱创伤占39.7%(75例)。基线特征显示,预警组中脊柱创伤患者比例(55.9%)显著高于非预警组(30.6%),差异有统计学意义(χ2=10.612,P=0.001)。预警组患者的住院时间、ICU住院时间较非预警组明显缩短,差异有统计学意义(P=0.006,P=0.017)。通过多因素线性回归分析发现,重症预警平台的应用与住院时间缩短相关(回归系数=-5.91,标准误=2.63,t=2.25,P=0.026)。

结论

实时重症预警平台可有效缩短骨科创伤患者的住院时间。

Objective

To evaluate the impact of a real-time critical care early warning platform on outcomes in patients with orthopedic trauma.

Methods

A study enrolling patients admitted to the Orthopedic Department who were subsequently transferred to the Intensive Care Unit (ICU) at Zhongda Hospital, Southeast University between January 2020 and December 2023, was conducted. Non-trauma patients and whose with an ICU length of stay (LOS) of less than 24 hours were excluded. Patients monitored by the early warning platform were assigned to the alert group (68 cases), while those receiving standard care formed the non-alert group (121 cases). The primary endpoint was hospital LOS. Multivariate linear regression was used to assess the independent association between the platform use and hospital LOS.

Results

Among the 189 included patients, the median age was 72 years, 43.9% (83 cases) were female, 31.7% (60 cases) were emergency admissions, and 39.7% (75 cases) had spinal trauma. Baseline characteristics showed that, the proportion of patients with spinal trauma in the warning group (55.9%) was significantly higher than that in the non-alert group (30.6%), with a significant difference (χ2=10.612, P=0.001). Patients in the alert group had a significantly shorter median hospital LOS (P=0.006) and ICU LOS (P=0.017) compared to the non-alert group. Multivariate linear regression analysis confirmed that the application of the critical care early warning platform was independently associated with a reduction in hospital LOS (β=-5.91 days, SE=2.63, t=2.25, P=0.026).

Conclusion

The implementation of a real-time critical care early warning platform is associated with a significant reduction in hospital and ICU LOS among orthopedic trauma patients.

图1 重症预警平台运行模式 注:CWP为重症预警平台;RRT group为快速反应小组
图2 患者入组流程图 注:非创伤原因入骨科转ICU的5例患者为我院2022年底至2023年1月骨科病房收治的新型冠状病毒感染患者
表1 预警组与非预警组患者的临床特征[例(%)]
表2 预警组与非预警组患者转入ICU时病情严重程度及临床结局
表3 重症预警平台对住院时间影响的多因素回归分析
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