Construction of a nomogram-based risk prediction model for postoperative pulmonary venti-lation dysfunction in patients with multiple rib fractures based on Lasso and Logistic regres-sion
Du Yiying
Yuan Lei
Tian Peng
He Chengxiang
Kong Yijie
Zhang Mei
Abstract：Objective To develop a Nomogram-based risk prediction model for postoperative pulmonary ventilation dysfunction in patients with multiple rib fractures(MRF)based on Least Absolute Shrinkage and Selec-tion Operator(Lasso)and Logistic regression.Methods A retrospective analysis was conducted on 210 hospital-ized patients with MRF at our department from Jun.2020 to Jun.2023.Injury mechanisms included road traffic ac-cidents(n=44),crush injuries(n=61),assaults(n=53),and falls(n=52).According to the Chinese Expert Con-sensus on Adult Pulmonary Function Diagnostics,patients with an FEV1/FVC ratio＜70%were classified into the pulmonary ventilation dysfunction group(n=134),and those with an FEV1/FVC ratio≥70%were assigned to the control group(n=76).Univariate analysis,Lasso regression,and multivariate Logistic regression were employed to i-dentify risk factors for pulmonary ventilation dysfunction in MRF patients.A nomogram was developed using R soft-ware.Internal validation was performed via the bootstrap method.Model discrimination was assessed using the con-cordance index(C-index),and calibration was evaluated with a calibration curve.Results Among the 210 pa-tients,134 developed pulmonary ventilation dysfunction,with the incidence being 63.8%(95%CI:57.3%-70.3%).There were no statistically significant differences between the two groups in terms of gender,hyperten-sion,diabetes,history of stroke,atrial fibrillation,preoperative anemia,intraoperative blood loss,or postoperative drainage volume(P＞0.05).However,the dysfunction group showed a much higher proportions of patients in terms of age≥70 years,BMI≥25 kg/m2,number of fractured ribs≥6,pre-hospital time≥1 d,combined chronic pulmona-ry disease or coronary artery disease,with history of smoking or alcohol use,conventional surgeries,operation time≥2 h,strong sputum expectoration ability,ASA grade of Ⅲ-Ⅳ,as well as much preoperative PaO2 level and much low-er PaCO2 level,all revealing significant difference when compared to the control group(all P＜0.05).Lasso regres-sion with the lambda set at 0.018 identified the following as significant predictors of postoperative pulmonary ventila-tion dysfunction:age≥70 years(OR=1.671,95%CI:0.834-3.345),BMI≥25 kg/m2(OR=3.671,95%CI:1.855-7.292),number of fractured ribs≥6(OR=7.241,95%CI:2.927-17.782),pre-hospital time≥1 d(OR=2.894,95%CI:1.120-7.479),and traditional surgery(OR=0.401,95%CI:0.197-0.818),with the specificity and sensitivity of 75.3%and 76.8%,Brie score of 0.161,and the C-index after internal validation of the model of 0.825,respectively.Calibration plots showed that the ideal probability curves and the actual probability curves over-lapped with each other to a high degree.Conclusion In this study,the risk factors of age≥70 years,BMI≥25 kg/m2,number of fractured ribs≥6,pre-hospital time≥1 d,and traditional surgery were identified through Las-so and Logistic regression.A nomogram-based risk prediction model has been developed for postoperative pulmonary ventilation dysfunction in MRF patients,which demonstrates high predictive performance and can effectively assess the risk of postoperative pulmonary ventilation dysfunction.
Keywords：Rib fracturesNormogramPulmonary ventilation dysfunction
Publication Date：2025-05-15
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：7( 370-375,393 )