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 ›› 2023, Vol. 4 ›› Issue (12): 1068-1074.doi: 10.3761/j.issn.2096-7446.2023.12.002

• 论著 • 上一篇    下一篇

机械通气患者亚谵妄综合征风险预测模型的构建及验证研究

辜甜田, 陈俊希, 杨洋, 肖旭, 李交, 张咏梅   

  1. 563000 遵义市 遵义医科大学附属医院重症医学科二病区(辜甜田,陈俊希,杨洋,肖旭,李交); 遵义医科大学护理学院(张咏梅)
  • 收稿日期:2023-06-16 出版日期:2023-12-10 发布日期:2023-12-21
  • 通讯作者: 张咏梅,E-mail:hulizym@yeah.net
  • 作者简介:辜甜田:女,硕士,主管护师,E-mail:582184262@qq.com
  • 基金资助:
    贵州省遵义市科技局计划[遵市科合HZ字(2021)154号]

Construction and validation of a nomogram risk prediction model for subsyndromal delirium in mechanically ventilated patients

GU Tiantian, CHEN Junxi, YANG Yang, XIAO Xu, LI Jiao, ZHANG Yongmei   

  1. Department of Critical Care Medicine,Zunyi Medical University Hospital,Zunyi, 563000,China
  • Received:2023-06-16 Online:2023-12-10 Published:2023-12-21

摘要: 目的 分析机械通气患者亚谵妄综合征发生的危险因素,构建风险预测模型,以预测亚谵妄的发生。方法 采用便利抽样法,选取2021年7月—2022年6月贵州省某三级甲等医院ICU收治的机械通气患者434例,使用ICU患者意识模糊评估表将其分为亚谵妄综合征组(n=136)和非亚谵妄综合征组(n=298),通过单因素分析和多因素Logistic回归分析探索亚谵妄综合征发生的独立危险因素,建立风险预测模型并构建列线图,并对该模型进行内、外部验证。结果 多因素Logistic回归分析显示,年龄(OR=1.029)、急性生理与慢性健康状况评分(OR=1.267)、身体约束(OR=1.029)、重症监护疼痛评分(OR=2.487)、理查兹—坎贝尔睡眠量表评分(OR=1.150)、Richmond躁动—镇静评分(OR=1.500)是亚谵妄综合征发生的独立危险因素。根据上述6项危险因素构建的ICU机械通气患者亚谵妄综合征风险预测模型ROC曲线下面积为0.956,灵敏度为86.2%,特异度为94.1%。结论 该研究构建的风险预测模型能有效预测机械通气患者亚谵妄综合征的发生,为临床医护人员科学预测亚谵妄综合征的发生提供参考。

关键词: 机械通气, 亚谵妄综合征, 列线图, 预测模型, 危重病护理

Abstract: Objective To analyze the risk factors for the occurrence of subsyndromal delirium in mechanically ventilated patients and construct a nomogram risk prediction model to predict the occurrence of subsyndromal delirium. Methods Convenience sampling was used to select 434 mechanically ventilated patients admitted to the ICU of a tertiary hospital in Guizhou Province from July 2021 to June 2022,who were categorized into the subdelirium syndrome group(n=136)and the non-subdelirium syndrome group(n=298)using the ICU Patient Ambi-guity of Consciousness Assessment Scale. We explored the independent risk factors for the occurrence of subde-lirium syndrome through univariate and multifactorial logistic regression analyses,established a risk prediction model,developed a nomogram,and validated the model both internally and externally. Results Multifactorial logistic regression analysis revealed that age(OR=1.029),acute physiological and chronic health status score(OR=1.267),whether restrained(OR=1.029),intensive care pain score(OR=2.487),Richards-Campbell sleep scale score(OR=1.150),Richmond agitation-sedation score(OR=1.500)were independent risk factors for the development of subdelirium. The consistency index of the nomogram model for the occurrence of subdelirium in mechanically ventilated patients in the ICU was 0.956,with a sensitivity of 86.2% and a specificity of 94.1%. Conclusion The risk prediction model construc-ted in this study can effectively predict the occurrence of subdelirium syndrome in mechanically ventilated patients,which provides a reference for clinical medical personnel to scientifically predict the occurrence of subdelirium.

Key words: Mechanically Ventilated, Subsyndromal Delirium, Nomogram, Prediction Model, Critical Care Nursing