Construction of a risk warning model for evacuation associated pulmonary edema in patients with mechanical ventilation for cardiogenic respiratory failure
10.3760/cma.j.cn211501-20240618-01570
- VernacularTitle: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
- Author:
Hongwang HAO
1
;
Lu XIANG
;
Zhinan WANG
;
Guangren HU
;
Fulian ZHANG
Author Information
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
- Publication Type:Journal Article
- Keywords:
Respiratory insufficiency;
Mechanical ventilation;
Evacuation related pulmonary edema;
Risk early warning model
- From:
Chinese Journal of Practical Nursing
2025;41(6):444-451
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To 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.Methods:A 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.Results:WIPE 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 absolute error was 0.020, the calibration curve fits the ideal curve, and the model calibration performance was good. Conclusions:WIPE in patients with cardiogenic respiratory failure induced by mechanical ventilation is affected by cardiac function status, mechanical ventilation parameters and other factors. The risk early warning model based on the above 9 independent influencing factors has good predictive efficacy, and can provide reference for clinical prevention of WIPE.
