Establishment Of A Nomogram Model For The Risk Of Multidrug-resistant Organism Pulmonary Infection In Patients With Traumatic Brain Injury After Surgery

Objective:This study aims to establish a risk prediction model for multidrug-resistant organism(MDRO)pulmonary infection in patients undergoing neurosurgical trauma surgery.Methods:A retrospective analysis of the clinical data of 287 TBI patients who were treated with neurosurgical trauma surgery in a certain neurosurgery department from September2020 to September 2022 was conducted.A modeling group was established and independent risk factors for MDRO pulmonary infection in TBI patients were screened using single-factor analysis and multi-factor Lasso logistic regression.Then,a nomogram prediction model for postoperative MDRO pulmonary infection in TBI patients was developed based on the independent risk factors.The clinical data of 73 TBI patients from March 2020 to September 2020 were used to construct a validation group,and the nomogram model was validated.Results:In the modeling group,123 of 287 patients had MDRO pulmonary infection,with an infection rate of 42.9%.164 cases of non-MDRO infection.Lasso logistic regression showed that preoperative GCS score ≤8 points(OR=3.43,95%CI:1.666～7.196),dilated pupil(OR=2.701,95%CI : 1.250～6.012),combined antimicrobial use days ≥ 7days(OR=3.874,95%CI:1.961～7.827),and the neurological intensive care Unit(NICU)hospitalization days ≥7 days(OR=4.851,95%CI:1.996～12.195)were independent risk factors for postoperative pulmonary infection in patients with TBI.The nomogram model was constructed based on the four independent risk factors that were identified.The results showed that the area under ROC curve(AUC)of the nomogram model in the modeling group and the verification group were 0.897 and 0.925,respectively,indicating that the prediction model had good prediction ability.Hosmer-Lemeshow test tested the model for goodness of fit,and the results showed that P = 0.4401,indicating that this Nomogram prediction model had a good calibration.The decision analysis curves for both the modeling group and the validation group show that the model has high clinical benefit.Conclusion:The Nomogram prediction model established based on lasso logistic regression analysis has good predictive value,which is conducive to early identification of TBI patients with postoperative secondary MDRO pulmonary infection risk.Doctors and nurses should strengthen monitoring of patients and adjust medication strategies as necessary to prevent the occurrence of MDRO lung infections.