Analysis Of Risk Factors For Postoperative Pulmonary Infection In Patients With Cervical Spinal Cord Injury And Nomogram Prediction Model

Objective:Analyze the risk factors of postoperative pulmonary infection in patients with acute cervical spinal cord injury(CSCI),and construct a Nomogram prediction model for postoperative pulmonary infection in CSCI patients.Methods:Collect clinical data of 689 CSCI patients admitted to the First Affiliated Hospital of Nanchang University,Yichun People’s Hospital,and Pingxiang People’s Hospital from July 2011 to July 2021.The patient’s gender,age,ASIA classification,hypertension history,diabetes history,high dose hormone use,smoking history,cervical spinal cord injury site(C1-C4 for high injury,C5-C7 for low injury),time difference from injury to operation,number of operation segments,operation time,intraoperative blood loss,and postoperative drainage volume were recorded.All patients underwent cervical spine surgery.Using 574 cases from the first two centers as the training set and 115 cases from the latter center as the validation set,patients in the training set were divided into infection group and non infection group(control group)based on the occurrence of postoperative pulmonary infections.Then,risk factors for postoperative pulmonary infection in CSCI were selected through single factor and multiple factor regression analysis,and a Nomogram prediction model was established using R software.The validation set data was used for external validation of the model,and the predictive performance,accuracy,and clinical application value of the model were verified using ROC curves,calibration charts,and decision curves.Results:A total of 689 patients were included,including 558 males and 131 females,with an average age of 53.60 years.There were 184 cases of pulmonary infections,with an incidence rate of 26.70%.Among them,there were 574 cases in the training set,and 144 cases had pulmonary infections,with an incidence rate of 25.09%.In the validation set of 115 cases,40 patients had pulmonary infection,and the incidence rate was 34.78%.Univariate analysis showed that there were statistically significant differences between the infected and non infected groups in terms of age,ASIA grade,high dose hormone use,smoking history,location of cervical spinal cord injury,time difference from injury to surgery,number of surgical segments,surgical time,intraoperative bleeding,and postoperative drainage(P<0.05).Further binary logistic regression analysis showed that the risk factors for postoperative pulmonary infection were age,ASIA grade,high dose hormone use,high-level injury,smoking,multi-segment surgery,and prolonged surgical time.The ROC curve AUC of the model built in the training set is 0.905,and the ROC curve AUC of the validation set is 0.917.From the calibration chart,it can be seen that the calibration curves of the training set model and the validation set model are close to the standard curve.The decision curve shows that the model is within the range of 1%-100%,and the predicted net benefit of the model is relatively high,indicating that the model has good predictive efficiency and clinical application value.Conclusions:Age,ASIA grade,hormone use,site of cervical spinal cord injury,smoking history,number of surgical segments,and surgical time are associated with postoperative pulmonary infection in CSCI patients.The risk prediction model for postoperative pulmonary infection in CSCI patients established on this basis has good predictive efficiency and accuracy,and has high clinical application value.