ISSN 2097-6046（网络）
ISSN 2096-7446（印刷）
CN 10-1655/R
主管：中国科学技术协会
主办：中华护理学会
中华急危重症护理杂志

中华急危重症护理杂志 >

2024 , Vol. 5 >Issue 6: 485 - 492

DOI: https://doi.org/10.3761/j.issn.2096-7446.2024.06.001

论著

ICU患者活动减少型谵妄风险动态列线图预测模型的构建与验证

  • 张欢 ,
  • 甘秀妮 ,
  • 周雯 ,
  • 高燕
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  • 400010 重庆市 重庆医科大学附属第二医院护理部
张欢：女,本科（硕士在读）,护士,E-mail：2365925389@qq.com

收稿日期: 2024-01-31

  网络出版日期: 2024-06-21

基金资助

重庆市自然科学基金面上项目（CSTB2022NSCQ-MSX0816）

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Development and validation of a dynamic nomogram prediction model for hypoactive delirium risk in ICU patients

  • ZHANG Huan ,
  • GAN Xiuni ,
  • ZHOU Wen ,
  • GAO Yan
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  • Department of Nursing,The Second Affiliated Hospital of Chongqing Medical University,Chongqing, 400010,China

Received date: 2024-01-31

  Online published: 2024-06-21

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摘要

目的 构建ICU患者活动减少型谵妄风险动态列线图预测模型,并验证其预测效果。方法 选取2022年10月—2023年11月重庆市某三级甲等医院ICU患者430例作为研究对象,采用ICU意识模糊评估表联合Richmond躁动-镇静评分进行谵妄评估和分型。通过单因素分析和多因素Logistic回归分析确定独立预测因子,构建动态列线图预测模型。采用受试者操作特征曲线下面积（area under the curve,AUC）和Hosmer-Lemeshow（H-L）拟合优度检验模型的区分度和校准度,并对模型进行内、外部验证。结果 纳入模型的预测因子为电解质紊乱（OR=2.350）、留置导管≥2根（OR=3.529）、使用利尿剂（OR=0.342）、格拉斯哥昏迷评分（OR=0.183）、C反应蛋白浓度（OR=1.006）、血尿素浓度（OR=1.063）。建模组AUC为0.941（95%CI：0.916~0.966）,灵敏度为87.9%,特异度为90.3%,H-L检验结果为P=0.415。验证组AUC为0.897（95%CI：0.837~0.956）,灵敏度为79.6%,特异度为86.5%,H-L检验结果为P=0.450。结论 该研究构建的动态列线图预测模型能有效预测ICU患者发生活动减少型谵妄的概率,为医护人员科学预测活动减少型谵妄的发生提供有效工具,且临床使用便捷。

关键词： 重症监护病房; 活动减少型谵妄; 危险因素; 列线图; 护理

本文引用格式

张欢 , 甘秀妮 , 周雯 , 高燕 . ICU患者活动减少型谵妄风险动态列线图预测模型的构建与验证[J]. 中华急危重症护理杂志, 2024 , 5(6) : 485 -492 . DOI: 10.3761/j.issn.2096-7446.2024.06.001

Abstract

Objective To develop a dynamic nomogram prediction model for hypoactive delirium risk in ICU patients and verify its predicted effect. Methods A total of 430 patients were selected from the ICU of a tertiary Grade A hospital in Chongqing from October 2022 to November 2023. The Confusion Assessment Methodfor Intensive Care Unit and Richmond Agitation-Sedation Scale were used for delirium assessment and classification. Independent predictors were determined through univariate analysis and multivariate logistic regression analysis,and a dynamic nomogram prediction model was developed. The area under the receiver operating characteristic curve and Hosmer-Lemeshow goodness of fit were used to test the discrimination and calibration of the model,and the internal and external verification of the model was conducted. Results The predictors were electrolyte disorders（OR=2.350）,indwelling catheters≥2（OR=3.529）,use of diuretics（OR=0.342）,Glasgow Coma Scale score（OR=0.183）,concentration of C-reactive protein（OR=1.006）,and urea concentration（OR=1.063）. In modeling group,the AUC was 0.941（95%CI：0.916~0.966）,the sensitivity was 87.9%,the specificity was 90.3%,and the Hosmer-Lemeshow test was P=0.415. In validation group,the AUC was 0.897（95%CI：0.837~0.956）,the sensitivity was 79.6%,the specificity was 86.5%,and the Hosmer-Lemeshow test result showed that P=0.450. Conclusion The dynamic nomogram prediction model constructed in this study can effectively predict the probability of hypoactive delirium in ICU patients,providing an effective tool for medical staff to scientifically predict the occurrence of hypoactive delirium,and is convenient for clinical use.

Key words： Intensive Care Units; Hypoactive Delirium; Risk Factors; Nomogram; Nursing Care

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