护理管理杂志2024,Vol.24Issue(7) :614-618,624.DOI:10.3969/j.issn.1671-315x.2024.07.012

急危重症患者院内转运不良事件风险预测模型的构建

Construction of a risk prediction model for adverse events in intra-hospital transfer of critically ill patients

陶珍珍 王志伟 祁进芳 李振刚 董正惠 刘玉姣
护理管理杂志2024,Vol.24Issue(7) :614-618,624.DOI:10.3969/j.issn.1671-315x.2024.07.012

急危重症患者院内转运不良事件风险预测模型的构建

Construction of a risk prediction model for adverse events in intra-hospital transfer of critically ill patients

陶珍珍 1王志伟 1祁进芳 1李振刚 1董正惠 2刘玉姣3
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作者信息

  • 1. 830011,乌鲁木齐市,新疆医科大学护理学院
  • 2. 830092,乌鲁木齐市,新疆医科大学第六附属医院护理部
  • 3. 830000,乌鲁木齐市,新疆医科大学第四附属医院/新疆维吾尔自治区中医医院急诊科
  • 折叠

摘要

目的 探讨急危重症患者院内转运不良事件的危险因素,并构建风险预测模型.方法 采用目的抽样法,选取 2023 年1月至6月乌鲁木齐市某三级甲等医院急诊科收治的342例急危重症患者为研究对象,根据是否发生院内转运不良事件分为发生组和未发生组.采用Logistic回归模型分析相关影响因素,构建预测模型,绘制可视化列线图.使用ROC曲线下面积及校准曲线验证模型的预测效能.结果 建模组239例急危重症患者中有75例发生院内转运不良事件,发生率为31.38%.Logistic回归分析显示,收缩压、改良早期预警评分、供氧装置、监护仪、转运班次、转运总时长为急危重症患者院内转运不良事件发生的独立危险因素(P<0.05).结果 显示,建模组ROC曲线下面积为0.943,灵敏度为0.968,特异度为0.875;验证组ROC曲线下面积为0.922,灵敏度为0.903,特异度为0.875.Hosmer-Lemeshow检验显示?2=7.348,P=0.403,校正曲线显示该列线图模型的预测概率和实际概率具有较好的一致性.结论 急危重症患者院内转运不良事件发生率较高,收缩压、改良早期预警评分、供氧装置、监护仪、转运班次、转运总时长是其发生院内转运不良事件的影响因素,基于以上影响因素构建的风险预测模型具有良好风险识别能力,列线图模型具有较好的区分度和校准度.

Abstract

Objective To explore the risk factors for adverse events in intra-hospital transport of critically ill patients and construct a risk prediction model.Methods A total of 342 patients with acute and critical illnesses in the emergency department of a tertiary hospital in Urumqi City from January to June 2023 were selected for the study by purposive sampling,and they were divided into the occurrence group and the non-occurrence group according to whether they had an adverse event of intra-hospital transport.The Logistic regression model was used to analyze the related risk factors,construct the prediction model,and draw a visual nomogram.The predictive efficacy of the model was verified by using the area under the ROC curve and the calibration curve.Results Seventy-five out of 239 patients with acute and critical ill-nesses in the modeling group experienced intra-hospital transport adverse events,with an incidence rate of 31.38%.Logistic regression analy-sis showed that systolic blood pressure,Modified Early Warning Score(MEWS),oxygen supply device,monitor,transfer shift,and total trans-port duration were independent risk factors for adverse events in intra-hospital transport of critically ill patients(P<0.05).The results showed that the area under the ROC curve in the modeling group was 0.943,with a sensitivity of 0.968 and specificity of 0.875,and the area under the ROC curve in the validation group was 0.922,with a sensitivity of 0.903 and a specificity of 0.875.Hosmer-Lemeshow test showed?2=7.348,P=0.403,and the calibration curve showed good agreement between the predicted and actual probabilities of this nomogram model.Conclusion The incidence of adverse events of intra-hospital transport is higher in critical patients.Systolic blood pressure,MEWS score,oxygen supply device,monitor,transfer shift,and total transport duration are the influencing factors of adverse events in intra-hospital trans-port,and the risk prediction model constructed on the basis of the above influencing factors has good risk identification ability,and the nomo-gram model has a better degree of differentiation and calibration.

关键词

急危重症患者/安全转运/不良事件/预测模型/列线图

Key words

critically ill patients/safe transfer/adverse event/predictive model/nomogram

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出版年

2024
护理管理杂志
中国人民解放军北京军区总医院

护理管理杂志

CSTPCD
影响因子:2.38
ISSN:1671-315X
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