关键词: 肺通气障碍, 多发性肋骨骨折, 风险预测模型, 影响因素

Abstract: Objective To establish a risk prediction model for postoperative pulmonary ventilation disorder in patients with multiple rib fractures.Methods From March 2019 to March 2021,a total of 150 patients with multiple rib fractures admitted to our hospital were selected and divided into a control group(patients without ventilatory disorders,52 cases) and a study group(patients with ventilatory disorders,98 cases) according to whether or not pulmonary ventilation disorders occurred after the operation.The clinical data of patients,such as visit time,diabetes,sputum expectoration,the number of rib fractures,smoking history,underlying lung diseases,age,gender and other clinical data,were collected for univariate analysis,multi-factor Logistic regression analysis was performed according to the results of single factor analysis,and R software was used to construct a risk prediction model for postoperative ventilatory disorder in patients with multiple rib fractures,the ROC curve and H-L fit degree were used to test and evaluate the model.Results Univariate analysis,the results showed that the occurrence of postoperative pulmonary ventilation disorder in patients with multiple rib fractures was related with age,underlying lung diseases,sputum expectoration,visit time,diabetes,smoking history,operation time,number of fractures,and body mass index(P<0.05);the multivariate Logistic regression analysis model,and the results showed that the age older than 60 years old,combined with underlying lung diseases,poor sputum expectoration,smoking history,visit time more than 24 h,combined with diabetes,operation time ≥120min,number of fracture ≥6,and body mass index ≥24kg/m2 were independent risk factors for lung ventilation disorder after multiple rib fracture operation(P<0.05).On this basis,R software was used to construct a risk prediction model for postoperative lung ventilation disorders in patients with multiple rib fractures,the area under the ROC curve and the HL deviation were used to test the model,the area under the ROC curve was 0.908,and the sensitivity and specificity were 80.77,86.73 respectively.The result of H-L deviation degree was  χ2=3.758,P=0.512.Conclusion Age older than 60 years old,combined with underlying lung diseases,poor sputum expectoration,smoking history,visit time more than 24 h,combined with diabetes,operation time ≥120 min,number of fractures ≥6,and body mass index ≥24 kg/m2 are independent risk factors that affect lung ventilation disorder after multiple rib fractures operation,the risk prediction model established on this basis has high discrimination and accuracy,which can provide an effective basis for early clinical identification of the risk of pulmonary ventilation disorder after operation.

Key words: pulmonary ventilation disorder, multiple rib fractures, risk prediction model, influencing factors