张玉宝, 王汇, 程岚. COPD机械通气病人谵妄发生风险的列线图预测模型构建与评估[J]. 蚌埠医学院学报, 2021, 46(11): 1611-1615. DOI: 10.13898/j.cnki.issn.1000-2200.2021.11.029
    引用本文: 张玉宝, 王汇, 程岚. COPD机械通气病人谵妄发生风险的列线图预测模型构建与评估[J]. 蚌埠医学院学报, 2021, 46(11): 1611-1615. DOI: 10.13898/j.cnki.issn.1000-2200.2021.11.029
    ZHANG Yu-bao, WANG Hui, CHENG Lan. Establishment and evaluation of a nomogram predictive model for the risk of delirium occurrence in COPD patients with mechanical ventilation[J]. Journal of Bengbu Medical College, 2021, 46(11): 1611-1615. DOI: 10.13898/j.cnki.issn.1000-2200.2021.11.029
    Citation: ZHANG Yu-bao, WANG Hui, CHENG Lan. Establishment and evaluation of a nomogram predictive model for the risk of delirium occurrence in COPD patients with mechanical ventilation[J]. Journal of Bengbu Medical College, 2021, 46(11): 1611-1615. DOI: 10.13898/j.cnki.issn.1000-2200.2021.11.029

    COPD机械通气病人谵妄发生风险的列线图预测模型构建与评估

    Establishment and evaluation of a nomogram predictive model for the risk of delirium occurrence in COPD patients with mechanical ventilation

    • 摘要:
      目的分析影响慢性阻塞性肺疾病(COPD)机械通气病人谵妄发生的危险因素,建立列线图预测模型并进行评估。
      方法回顾性分析2018年1月至2019年8月收治的COPD机械通气病人382例临床资料,按照病人是否发生谵妄分为谵妄组与非谵妄组,采用单因素与多因素logistic回归模型筛选影响COPD机械通气病人发生谵妄的危险因素,将各危险因素纳入R软件建立列线图预测模型,采用ROC曲线下面积评估模型的区分度并进行拟合优度检验。
      结果COPD机械通气病人谵妄发生率为29.58%(113/382);多因素logistic回归分析显示,APACHEⅡ评分(OR=1.075,95% CI:1.008~1.146)、使用镇静药(OR=2.013,95% CI:1.185~3.420)、使用身体约束(OR=2.673,95% CI:2.673~5.362)、机械通气时间(OR=1.134,95% CI:1.064~1.207)、住ICU时间(OR=1.154,95% CI:1.075~1.239)均为影响COPD机械通气病人谵妄发生的独立危险因素(P < 0.05~P < 0.01);基于影响谵妄发生的相关危险因素建立列线图预测模型并进行评估,ROC曲线下面积为0.859(95% CI:0.813~0.904);列线图校准曲线斜率接近1;模型拟合较好(χ2=4.73,P>0.05)。
      结论基于影响COPD机械通气病人谵妄发生的危险因素建立的列线图预测模型具有良好区分度与一致性,可为预防COPD机械通气病人谵妄的发生提供一定指导价值。

       

      Abstract:
      ObjectiveTo analyze the risk factors that affect the occurrence of delirium in mechanically ventilated patients with chronic obstructive pulmonary disease (COPD), establish a nomogram prediction model and evaluate it.
      MethodsA retrospective analysis of the clinical data of 382 COPD mechanically ventilated patients from January 2018 to August 2019 was performed.The patients were divided into delirium group and non-delirium group according to the occurrence of delirium.The risk factors of delirium in COPD patients with mechanical ventilation were screened by single factor and multivariate logistic regression models.The risk factors were incorporated into R software to establish a nomogram prediction model, and the area under the ROC curve was used to evaluate the discrimination of the model and test the goodness of fit.
      ResultsThe incidence of delirium in COPD mechanically ventilated patients was 29.58%(113/382).Multivariate logistic regression showed that APACHEⅡ score(OR=1.075, 95% CI: 1.008-1.146), use of sedatives(OR=2.013, 95% CI: 1.185-3.420), use of physical restraint(OR=2.673, 95% CI: 2.673-5.362), mechanical ventilation time(OR=1.134, 95% CI: 1.064-1.207), ICU stay(OR=1.154, 95% CI: 1.075-1.239) were the independent risk factors that affect the occurrence of delirium in COPD patients with mechanical ventilation(P < 0.05 to P < 0.01).A nomogram prediction model was established and evaluated based on the relevant risk factors affecting the occurrence of delirium.The area under the ROC curve was 0.859(95% CI: 0.813-0.904);the slope of the nomogram calibration curve was close to 1;the model fitted well(χ2=4.73, P>0.05).
      ConclusionsThe nomogram prediction model based on the risk factors of delirium in COPD patients with mechanical ventilation has good discrimination and consistency, which can provide some guidance for the prevention of delirium in COPD patients with mechanical ventilation.

       

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