检验医学与临床2025，Vol.22Issue(4)：475-479,484,6.DOI:10.3969/j.issn.1672-9455.2025.04.009
脑卒中相关性肺炎患者多药耐药菌感染影响因素分析及预测模型构建
Influencing factors and predictive model construction of multidrug-resistant bacteria infection in patients with stroke-associated pneumonia
摘要
Abstract
Objective To observe multidrug-resistant bacterial infections in patients with stroke-associated pneumonia(SAP),analyze their influencing factors and construct a prediction model.Methods A total of 202 patients with SAP treated at the hospital from January 2021 to January 2023 were selected as the study sub-jects.All patients underwent pathogen testing and drug susceptibility testing.Based on the presence of multi-drug-resistant bacterial infections,the patients were divided into the infection group and the non-infection group.Clinical data between the two groups were compared to analyze the influencing factors of multidrug-re-sistant bacterial infections in SAP patients.Predictive model was constructed.Receiver operating characteristic(ROC)curve was plotted to assess the predictive value of the model for multidrug-resistant bacterial infec-tions in SAP patients.Results Among the 202 patients with SAP,multidrug-resistant bacterial infections were observed in 113 cases(55.94%).The National Institutes of Health Stroke Scale(NIHSS)score in the infection group was higher than that in the non-infection group,and the proportions of patients with comorbid diabetes,coma,invasive procedures and prophylactic antibiotic use were significantly higher in the infection group than those in the non-infection group(P<0.05).Logistic regression analysis indicated that a higher NIHSS score(OR=1.586,95%CI:1.393-1.806,P<0.001),comorbid diabetes(OR=3.259,95%CI:1.505-7.058;P=0.003),coma(OR=2.823,95%CI:1.416-5.629,P=0.003),invasive procedures(OR=2.373,95%CI:1.299-4.336,P=0.005),and prophylactic antibiotic use(OR=2.941,95%CI:1.582-5.468,P=0.001)were identified as risk factors for multidrug-resistant bacterial infections in SAP patients.The regression equation Logit(P)=-2.034+0.461XNIHSS score+1.181Xdiabetes+1.038Xcoma+0.864Xinvasive procedures+1.079Xprophylactic use of antimicrobials was derived from the Logistic regression model.The calculated predictive probabilities were used as test variables to plot the ROC curve.The area under the curve of this model for predicting multidrug-resistant bacterial infections in SAP patients was 0.985,with sensitivity and specificity of 0.956 and 0.888 respectively.Conclusion Multidrug-resistant bacterial infections in SAP pa-tients associate with multiple factors.Clinical practices should incorporate these factors to predict such infec-tions at an early stage and implement appropriate interventions to improve patient outcomes.关键词
脑卒中相关性肺炎/多药耐药菌/影响因素/预测模型/药物敏感试验Key words
stroke-associated pneumonia/multidrug-resistant bacteria/influencing factor/predictive modeling/drug susceptibility testing分类
医药卫生引用本文复制引用
高新梅,邢雷,王清涛,母海蕾,朱东林..脑卒中相关性肺炎患者多药耐药菌感染影响因素分析及预测模型构建[J].检验医学与临床,2025,22(4):475-479,484,6.基金项目
河北省秦皇岛市重点研发科技支撑项目(202101157). （202101157）
