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作 者:黄文龙 谢小华[2] 熊海燕 谭薇[2] Huang Wenlong;Xie Xiaohua;Xiong Haiyan;Tan Wei(Department of Nursing,the People's Hospital of Longhua,Shenzhen 518000,China;Department of Nursing,the Second People's Hospital of Shenzhen,Shenzhen 518000,China)
机构地区:[1]深圳市龙华区人民医院护理部,深圳518000 [2]深圳市第二人民医院护理部,深圳518000
出 处:《中华现代护理杂志》2019年第5期577-580,共4页Chinese Journal of Modern Nursing
基 金:深圳市科技创新委员会资助项目(CXZZ20140418182638768);广东省科技计划项目(2014A020212574).
摘 要:目的探讨改良早期预警评分(MEWS)对急诊分级分诊为Ⅰ~Ⅲ级患者入住ICU 的预测价值,为急诊医务人员合理分流患者提供客观评估工具。方法采用便利抽样法,选取2017 年5 月 17 日—9 月27 日在某三级甲等综合医院急诊科就诊的患者463 例为研究对象,采集患者入急诊科时的相关数据进行MEWS 评分。结局指标为患者是否转入ICU,按照MEWS 分值分为MEWS ≥ 4 分组和MEWS< 4 分组,比较两组转入ICU率,分别计算MEWS、MEWS结合分级预测患者转入ICU的 ROC 曲线下面积、灵敏度、特异度、最佳截断值。结果 MEWS ≥ 4 分和MEWS < 4 分转入ICU 率分别为43.4%、13.5%,差异有统计学意义(χ2=52.3028,P<0.001)。MEWS预测患者转入ICU的AUC为0.759,最佳截断值为3.5分,灵敏度68.91%,特异度68.90%,MEWS结合分级预测患者转入ICU的AUC为0.861。结论 MEWS对分级为Ⅰ~Ⅲ级患者转入ICU具有中等的预测价值,增加分级预测能力提高,该评分工具简单、实用,可以为患者合理分流提供参考。Objective To explore the power of modified early warning score( MEWS) in predicting Class I-Ⅲ patients to be transferred into the intensive care unit( ICU) and to provide an objective assessment tool for medical workers to properly triage patients. Methods Totally 463 patients admitted into the Department of Emergency of a Class Ⅲ Grade A hospital from May 17 to September 27, 2017 by convenient sampling. MEWS was obtained by collecting the patients' data at admission. The outcome indicator was whether the patients were transferred into ICU. The patients were divided into the MEWS ≥ 4 group and the MEWS < 4 group based on MEWS. The rate of transfer into ICU was compared between the patients. The area under the receiver operating characteristic curves( AUC-ROC), sensitivity, specificity and the best cutoff point of MEWS and MEWS combined with stratification in predicting whether the patients would be transferred into ICU were calculated. Results The rate of transfer into ICU in the MEWS≥4 group and the MEWS<4 group was 43.4% and 13.5%, respectively(χ^2=52.3028, P < 0.001). The AUC-ROC of MEWS in predicting whether the patients would be transferred into ICU was 0.759, whose best cutoff point, sensitivity and specificity was 3.5, 68.91% and 68.90%. The AUC-ROC of MEWS combined with stratification in predicting whether the patients would be transferred into ICU was 0.861. Conclusions The predictive power of MEWS in predicting whether class I-Ⅲ patients would be transferred into ICU is medium, but its predictive power is enhanced when stratification is combined with MEWS. The scoring tool is simple and practical, which provides a reference for properly triaging patients.
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