[1]杨晓文,童孜蓉,吴娟,等.神经外科重症机械通气患者脱机失败预测模型的构建[J].军事护理,2023,40(06):9-12.[doi:10.3969/j.issn.2097-1826.2023.06.003]
　YANG Xiaowen,TONG Zirong,WU Juan,et al.Development of Prediction Model of Weaning Failure in Neurosurgical Patients with Severe Mechanical Ventilation[J].Nursing Journal Of Chinese People's Laberation Army,2023,40(06):9-12.[doi:10.3969/j.issn.2097-1826.2023.06.003]
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神经外科重症机械通气患者脱机失败预测模型的构建
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《军事护理》[ISSN:2097-1826/CN:31-3186/R]

卷:
40
期数:
2023年06期
页码:
9-12
栏目:
急危重症护理专栏
出版日期:
2023-06-15

文章信息/Info

Title:
Development of Prediction Model of Weaning Failure in Neurosurgical Patients with Severe Mechanical Ventilation
文章编号:
2097-1826(2023)06-0009-04
作者:
杨晓文; 童孜蓉; 吴娟; 王昱
(江苏省人民医院 神经外科重症监护室,江苏 南京 210000)
Author(s):
YANG Xiaowen; TONG Zirong;  WU Juan; WANG Yu
(Intensive Care Unit of Neurosurgery,Jiangsu Provincial People's Hospital,Nanjing 210000,Jiangsu Province,China)
关键词:
神经外科;  机械通气;  脱机失败;  预测模型
Keywords:
department of neurosurgery;  mechanical ventilation;  weaning failure;  prediction model
分类号:
R473
DOI:
10.3969/j.issn.2097-1826.2023.06.003
文献标志码:
A
摘要:
目的 构建神经外科重症机械通气患者脱机失败的预测模型,以期为神经外科重症机械通气患者脱机失败的防治提供理论依据。方法 2021年1月至2022年10月,采用便利抽样法选取某院收治的神经外科重症机械通气患者310例为研究对象。采用Logistic回归分析筛选机械通气患者脱机失败的危险因素,构建神经外科重症机械通气患者脱机失败的预测模型,并分析预测模型的预测效能。结果 310例患者中,60例患者脱机失败,占19.35%。是否脱机失败的患者在年龄、吸烟指数、机械通气时间等资料上的差异均有统计学意义(均P<0.05)。Logistic回归分析显示,年龄、格拉斯哥昏迷量表评分、吸烟指数、机械通气时间、多器官功能障碍综合征及呼吸系统基础疾病等是神经外科重症机械通气患者脱机失败的危险因素(均P<0.05)。预测模型的受试者工作特征曲线下面积为0.722(95%CI:0.647～0.798)。结论 构建的预测模型能对神经外科重症机械通气患者脱机失败进行准确预测,有助于临床及时制订神经外科重症机械通气患者脱机失败的相关对策。
Abstract:
Objective To develop a prediction model of weaning failure in neurosurgical patients with severe mechanical ventilation,and to provide theoretical basis for prevention and treatment of the weaning failure.Methods From January 2021 to October 2022,310 patients with severe mechanical ventilation in department of neurosurgery admitted to a hospital were selected by convenience sampling method as the study objects.The risk factors of weaning failure in patients with severe mechanical ventilation in department of neurosurgery were screened by logistic regression analysis,and the prediction model of weaning failure in patients with severe mechanical ventilation in department of neurosurgery was constructed,and the prediction efficiency of the model was analyzed.Results Among 310 patients,60 patients failed in weaning process, accounting for 19.35%.There were statistically significant differences in age,smoking index and mechanical ventilation time among patients who failed in weaning process(all P<0.05).Logistic regression analysis showed that age,Glasgow Coma Scale(GCS)score,smoking index,mechanical ventilation duration, multiple organ dysfunction syndrome(MODS),and underlying respiratory diseases were risk factors for weaning failure in patients with severe mechanical ventilation in department of neurosurgery(all P<0.05).The area under the receiver operating characteristic curve of the prediction model was 0.722(95%CI:0.647-0.798).Conclusions The established prediction model can accurately predict the weaning failure,which is helpful for clinical formulation of relevant countermeasures for the weaning failure of patients with severe mechanical ventilation in department of neurosurgery.

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备注/Memo

备注/Memo:
【 收稿日期 】2022-10-31【 修回日期 】2023-04-27
【 基金项目 】江苏省科教能力提升工程(ZDXK202225)
【 作者简介 】杨晓文,本科,主管护师,电话:025-68303063
【 通信作者 】童孜蓉,电话:025-68306162
更新日期/Last Update: 2023-06-15