老年高血压脑出血患者并发呼吸机相关肺炎的影响因素及预测模型构建  

Influencing factors for ventilator-associated pneumonia in elderly patients with hypertensive cerebral hemorrhage and construction of its prediction model

作　　者：徐安 高永霞 邵晗祺 齐超 Xu An;Gao Yongxia;Shao Hanqi;Qi Chao(Intensive Care Unit,First Affiliated Hospital of Nanjing Medical University,Jiangsu Provincial Hospital,Nanjing 210029,China;Emergency Intensive Care Unit,First Affiliated Hospital of Nanjing Medical University,Jiangsu Provincial Hospital,Nanjing 210029,China)

机构地区：[1]南京医科大学第一附属医院·江苏省人民医院重症监护室,南京210029 [2]南京医科大学第一附属医院·江苏省人民医院急诊重症监护室,南京210029

出　　处：《中华老年多器官疾病杂志》2025年第3期177-181,共5页Chinese Journal of Multiple Organ Diseases in the Elderly

基　　金：国家重点研发计划(2020YFC2009500);江苏省重点研发计划(BE2021012-4)。

摘　　要：目的探究老年高血压脑出血患者并发呼吸机相关肺炎(VAP)的影响因素,并构建预测模型。方法回顾性分析2020年2月至2023年6月南京医科大学第一附属医院收治的140例老年高血压脑出血患者相关资料,根据患者是否出现VAP分为VAP组(n=41)和非VAP组(n=99);收集患者各项资料,分析患者VAP发生影响因素,并构建预测模型。采用SPSS 26.0软件进行数据分析。根据数据类型,组间比较分别采用t检验及χ^(2)检验。采用多元logistic回归分析患者并发VAP的影响因素,并以此构建预测模型,采用受试者工作特征(ROC)曲线分析预测模型预测价值。结果140例患者VAP发生率为29.29%(41/140)。两组患者吸烟史、慢性阻塞性肺疾病、意识状态、通气体位、气管连接方式、机械通气时间、抗菌药物应用比较,差异有统计学意义(P<0.05)。多元logistic回归分析结果显示吸烟史、慢性阻塞性肺疾病、通气体位、机械通气时间、抗菌药物应用为VAP发生的影响因素(P<0.05);依据多元logistic回归分析显示,预测模型为Log P=-1.649+0.486×吸烟史+0.359×慢性阻塞性肺疾病+0.675×通气体位+0.426×机械通气时间+0.776×抗菌药物应用,Hosmer-Lemeshow表明χ^(2)=5.263,P=0.336;ROC曲线下面积为0.868(95%CI 0.826~0.926),灵敏度与特异度分别为81.32%与79.85%。结论高血压脑出血患者并发VAP容易受吸烟史、慢性阻塞性肺疾病、通气体位、吸烟史、机械通气时间等影响,以此构建风险预测模型预测效能优异。Objective To explore the influencing factors of ventilator-associated pneumonia(VAP)in elderly patients with hypertensive cerebral hemorrhage,and then construct a prediction model.Methods The relevant data of 140 elderly patients with hypertensive cerebral hemorrhage admitted to our hospital from February 2020 to June 2023 were collected and retrospectively analyzed.According to the occurrence of VAP or not,they were divided into a VAP group(n=41)and a non-VAP group(n=99).The factors affecting the occurrence of VAP were analyzed,and the prediction model was built.SPSS statistics 20.0 was used for data analysis.Depending on data type,t test or χ^(2) test was used for comparison between groups,and multiple logistic regression was employed to identify the influencing factors for VAP concurrence.And then a prediction model was constructed based on the obtained factors,and its predictive value was assessed with receiver operating characteristic(ROC)curve analysis.Results The incidence of VAP in the 140 patients was 29.29%(41/140).There were significant differences between two groups in terms of smoking history,chronic obstructive pulmonary disease(COPD),state of consciousness,position during ventilation,connection by orotracheal intubation(OTI)or tracheostomy tube,duration of mechanical ventilation,and antibiotic use(P<0.05).Multiple logistic regression analysis showed that smoking history,COPD,position during ventilation,duration of mechanical ventilation and antimicrobial use were the influencing factors for the occurrence of VAP(P<0.05).The constructed prediction model was Log P=-1.649+0.486×smoking history+0.359×COPD+0.675×position during ventilation+0.426×duration of mechanical ventilation+0.776×antibacterial use.Hosmer-Lemeshow test indicated that χ^(2)=5.263,P=0.336;ROC curve analysis displayed that the area under the curve was 0.868(95%CI 0.826-0.926),with a sensitivity of 81.32% and a specificity of 79.85%.Conclusion Smoking history,COPD,position during ventilation,smoking history and duration of mecha

关 键 词：老年人 高血压脑出血 呼吸机相关肺炎 影响因素 预测模型 

分 类 号：R743.2[医药卫生—神经病学与精神病学] R592[医药卫生—临床医学]