心源性呼吸衰竭机械通气患者发生撤机相关性肺水肿的风险预警模型构建  

Construction of a risk warning model for evacuation associated pulmonary edema in patients with mechanical ventilation for cardiogenic respiratory failure

作　　者：郝洪旺 项露 王智男 胡广仁 章富莲[1] Hao Hongwang;Xiang Lu;Wang Zhinan;Hu Guangren;Zhang Fulian(Department of Intensive Care Unit,Chengbei Campus of Hangzhou First People′s Hospital(Hangzhou Geriatric Hospital),Hangzhou 310000,China;Department of Burn and Plastic Surgery,Chengbei Branch of Hangzhou First People′s Hospital(Hangzhou Geriatric Hospital),Hangzhou 310000,China;Department of Operating Room,Mingji Hospital Affiliated to Nanjing Medical University,Nanjing 210019,China)

机构地区：[1]杭州市第一人民医院城北院区(杭州市老年病医院)重症病房,杭州310000 [2]杭州市第一人民医院城北院区(杭州市老年病医院)烧伤整形科,杭州310000 [3]南京医科大学附属明基医院手术室,南京210019

出　　处：《中国实用护理杂志》2025年第6期444-451,共8页Chinese Journal of Practical Nursing

摘　　要：目的探讨心源性呼吸衰竭机械通气患者发生撤机相关性肺水肿(WIPE)的影响因素,基于独立影响因素构建风险预警模型。方法采用横断面调查法,回顾性选取2021年4月至2023年12月在杭州市第一人民医院城北院区治疗并接受机械通气的心源性呼吸衰竭患者220例,根据患者有无发生WIPE分为WIPE组34例和无WIPE组186例,使用医院电子病历系统统计患者各项临床资料,通过单因素分析及多因素Logistic回归分析确定WIPE的影响因素,并基于回归分析法构建风险预警模型,使用R 4.2.1软件绘制对应的列线图,采用受试者工作特征曲线、校准曲线检验模型预测效能。结果WIPE组患者男18例,女16例,年龄(65.12±9.28)岁。无WIPE组患者男107例,女79例,年龄(60.25±8.40)岁。多因素Logistic回归分析结果显示,年龄(OR=1.072)、吸烟史(OR=3.412)、急性生理学和慢性健康状况评分Ⅱ(OR=1.184)、心功能分级(OR=4.043)、浅快呼吸指数(OR=1.100)、机械通气时间(OR=1.540)、合并高血压(OR=4.903)、合并左心室舒张功能障碍(OR=5.151)及合并慢性阻塞性肺疾病(OR=5.536)均是发生WIPE的独立影响因素(均P<0.05),基于以上9个独立影响因素构建的风险预警模型其曲线下面积为0.938,最佳截断值0.620对应的灵敏度、特异度分别为0.971、0.801,模型的区分能力良好。校准曲线结果显示,平均绝对误差为0.020,校准曲线贴合理想曲线,模型校准性能良好。结论心源性呼吸衰竭机械通气患者发生WIPE受心功能状态、机械通气参数等因素影响,基于以上9个独立影响因素构建的风险预警模型预测效能良好,可为临床上预防WIPE提供参考。ObjectiveTo explore the influencing factors of evacuation associated pulmonary edema(WIPE)in patients with mechanical ventilation of cardiogenic respiratory failure,and to build a risk warning model based on independent influencing factors.MethodsA total of 220 patients with cardiogenic respiratory failure who were treated and received mechanical ventilation in Chengbei Campus of Hangzhou First People′s Hospital from April 2021 to December 2023 were retrospectively selected by cross-sectional investigation method,and were divided into WIPE group(34 cases)and non WIPE group(186 cases)according to whether the patients had WIPE or not.Clinical data of the patients were analyzed using the hospital electronic medical record system.The influencing factors of WIPE were determined by univariate analysis and multivariate Logistic regression analysis,and the risk early warning model was constructed based on regression analysis.The corresponding nomogram was drawn by R language software,and the predictive efficiency of the model was tested by receiver operating characteristic curve and calibration curve.ResultsWIPE group included 18 males and 16 females,aged(65.12±9.28)years.Non WIPE group included 107 males and 79 females,aged(60.25±8.40)years.Multivariate Logistic regression analysis showed that age(OR=1.072),smoking history(OR=3.412),acute physiology and chronic health evaluationⅡ(OR=1.184),cardiac function classification(OR=4.043),shallow rapid breathing index(OR=1.100),mechanical ventilation time(OR=1.540),hypertension(OR=4.903),left ventricular diastolic dysfunction(OR=5.151)and chronic obstructive pulmonary disease(OR=5.536)were independent influencing factors(all P<0.05).The area under the curve of the risk early warning model constructed based on the above 9 independent influencing factors was 0.938,and the sensitivity and specificity corresponding to the optimal cutoff value of 0.620 were 0.971 and 0.801,respectively,indicating good differentiation ability.The calibration curve results show that the average

关 键 词：呼吸功能不全 机械通气 撤机相关性肺水肿 风险预警模型 

分 类 号：R54[医药卫生—心血管疾病]