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急诊科危重症患者院内转运不良事件的风险预测模型构建

Construction of A Risk Prediction Model for Adverse Events During Intra-hospital Transport of Critically Ill Patients in the Emergency Department
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摘要 目的分析急诊科危重症患者院内转运不良事件风险因素,构建风险预测模型。方法采用方便抽样法选取2021年10月至2023年2月某院急诊科进行院内转运的870例危重症患者的临床资料,采用单因素和多因素Logistic回归分析建立风险预测模型,以受试者工作特征(receiver operating characteristic,ROC)曲线下面积(area under curve,AUC)评价模型预测效果。结果英国国家早期预警评分(national early warning score,NEWS)、血氧饱和度、急诊B超、血管活性药物、机械通气是急诊科危重症患者发生病情不良事件的独立风险因素;血氧饱和度、携氧装置、Ⅲ类管路、护工参与转运是技术不良事件的独立风险因素(均P<0.05)。AUC分别为0.813,0.756。结论构建的急诊科危重症患者院内转运不良事件风险预测模型具有一定的参考价值。 Objective To analyze the risk factors associated with adverse events during intra-hospital transport of critically ill patients in the Emergency Department(ED)and to develop a risk prediction model.Methods Clinical data from 870 critically ill patients undergoing intra-hospital transport in the ED of a hospital from October 2021 to February 2023 were selected.Univariate and multivariate logistic regression analyses were employed to establish the risk prediction model.The prediction effect of the model was evaluated by the receiver operating characteristic(ROC)area under curve(AUC).Results Multivariate logistic regression revealed that national early warning score(NEWS),blood oxygen saturation(SPO_(2)),emergency B-ultrasound usage,vasoactive drug usage,and mechanical ventilation were independent risk factors for adverse events associated with disease.SPO_(2),transportation with oxygen devices,transportation with a third type of pipe,and the involvement of nursing assistants were independent risk factors for adverse events associated with technology(all P<0.05).The AUC were 0.813 and 0.756.Conclusions The constructed risk prediction model is of certain reference value.
作者 姚小云 李玉肖 陈亚玲 傅保国 丁娟 郑艳 YAO Xiaoyun;LI Yuxiao;CHEN Yaling;FU Baoguo;DING Juan;ZHENG Yan(Department of Emergency,Jingzhou Central Hospital,Jingzhou 434020,Hubei Province,China;Department of Nursing,Jingzhou Central Hospital)
出处 《军事护理》 CSCD 北大核心 2024年第2期51-55,共5页 MILITARY NURSING
基金 湖北省2021年度科技计划项目(2021CFB601)。
关键词 急诊科 危重症患者 院内转运 不良事件 预测模型 emergency department critically ill patients intra-hospital transport adverse event prediction model
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