刘微, 刘建超, 庄倩, 冯聪, 叶小飞, 刘丽华, 李林. 伤员伤情危重程度简易评分的构建与验证[J]. 解放军医学院学报, 2023, 44(11): 1206-1211. DOI: 10.12435/j.issn.2095-5227.2023.040
引用本文: 刘微, 刘建超, 庄倩, 冯聪, 叶小飞, 刘丽华, 李林. 伤员伤情危重程度简易评分的构建与验证[J]. 解放军医学院学报, 2023, 44(11): 1206-1211. DOI: 10.12435/j.issn.2095-5227.2023.040
LIU Wei, LIU Jianchao, ZHUANG Qian, FENG Cong, YE Xiaofei, LIU Lihua, LI Lin. Construction and verification of a simple scoring system for severity of injuries[J]. ACADEMIC JOURNAL OF CHINESE PLA MEDICAL SCHOOL, 2023, 44(11): 1206-1211. DOI: 10.12435/j.issn.2095-5227.2023.040
Citation: LIU Wei, LIU Jianchao, ZHUANG Qian, FENG Cong, YE Xiaofei, LIU Lihua, LI Lin. Construction and verification of a simple scoring system for severity of injuries[J]. ACADEMIC JOURNAL OF CHINESE PLA MEDICAL SCHOOL, 2023, 44(11): 1206-1211. DOI: 10.12435/j.issn.2095-5227.2023.040

伤员伤情危重程度简易评分的构建与验证

Construction and verification of a simple scoring system for severity of injuries

  • 摘要:
    背景 对伤员伤情危重程度的准确判断和精确分类是实施科学救治的前提和基础。
    目的 构建可供院前急救使用的伤员伤情危重程度监测指标和测量方法。
    方法 收集解放军总医院8个医学中心2014 - 2018年创伤伤员44642例,纳入年龄、入院病情、体温、脉搏、呼吸、收缩压、共病数量、伤部、伤类、伤因10个指标;采用多元Logistic回归分析构建伤情危重评分模型,用Liu方法、Youden指数法、离(0,1)最近法确定创伤危重分级界值。
    结果 构建的伤情危重分值,为该伤员各变量风险分值之和,取值范围为-15 ~ 98分,模型验证区分度和校准度均较好;将伤情分为轻度和重度,<32分为轻度,≥32分为重度。
    结论 构建的伤情危重评分可用于院前环境对伤员的伤情危重评估和伤员结局预测,并作为救治资源调配的依据。

     

    Abstract:
    Background Accurate assessment and classification for the severity of injuries is a prerequisite and foundation for implementing timely and scientific treatment.
    Objective To provide some monitoring indicators and measurement methods for the severity of injuries for uses in battlefield and on-site first aid.
    Methods A total of 44 642 cases with trauma injuries were collected from 8 medical centers affiliated to Chinese PLA General Hospital from 2014 to 2018, and multiple logistic regression analysis was used to construct an injury severity scoring model, including 10 indicators: age, admission condition, temperature, pulse, breathing, systolic blood pressure, number of comorbidities, injury sites, injury types, and injury causes. The Liu method, Youden index method, and nearest (0, 1) method were used to determine the cut-off scores of trauma severity.
    Results The severity score of injury was the sum of the risk scores of each variable, ranging from -15 to 98 points, and the verification of discrimination and calibration degree of the model was good. The cut-off score for grading injuries into mild and severe was 32, with <32 classified as mild and ≥32 as severe.
    Conclusion The injury severity score can be used for assessment of the severity and prediction of casualty outcomes in battlefield and on-site environments, which can be used as a reference for resource allocation.

     

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