Establishment of a nomogram model for risk of pulmonary infection after craniocerebral injury and preliminary assessment of its effectiveness

Abstract

Objective To explore the risk factors of postoperative pulmonary infection in patients with craniocerebral injury and establish a nomogram model to predict the risk of postoperative pulmonary infection after craniocerebral injury. Methods The clinical data of 169 patients with craniocerebral injury, admitted to and underwent craniotomy in our hospital from January 2013 to December 2018, were retrospectively analyzed. The clinical data of patients with postoperative pulmonary infection and without postoperative pulmonary infection were compared. The risk factors of postoperative pulmonary infection were analyzed by multivariate Logistic regression. R language was used to establish a nomogram model to predict the risk of postoperative pulmonary infection after craniocerebral injury. Receiver operating characteristic (ROC) curve was used to explore the prediction efficiency of the nomogram model for pulmonary infection after craniocerebral injury. Results Among the 169 patients, 74 (43.8%) were complicated with pulmonary infection and 95 (56.2%) were not complicated with pulmonary infection. As compared with non-pulmonary infection group, pulmonary infection group had significantly higher percentages of patients with open craniocerebral injury and Glasgow coma scale (GCS) scores<7, significantly higher American Society of Anesthesiologists (ASA) grading, lower albumin level one week after surgery, statistically longer operation time, and significantly higher percentages of patients with conscious disorder, patients accepted intraoperative blood transfusion, patients used breathing machine, and patients stayed in bed for 4 weeks or more (P<0.05). Multivariate Logistic regression analysis showed that GCS scores (OR=0.243, 95%CI: 0.122-0.497, P=0.000), ASA grading (OR=3.349, 95%CI: 2.233-5.021, P=0.000), disturbance of consciousness (OR=3.185, 95%CI: 1.217-8.334, P=0.018), and use of ventilator (OR=3.376, 95%CI: 1.590-7.167, P=0.002) were independent risk factors for postoperative pulmonary infection in patients with craniocerebral injury. The scores of the nomogram model were 13.7, 100.0, 38.0 and 27.5 in GCS scores, ASA grading, disturbance of consciousness and use of ventilator, respectively. The consistency index of the nomogram model for predicting postoperative pulmonary infection in patients with craniocerebral injury was 0.835. ROC curve showed that the area under the curve predicted by nomogram model for postoperative pulmonary infection in patients with craniocranial injury was 0.840 (95%CI: 0.778-0.901). Conclusion Based on the risk factors for pulmonary infection after craniocerebral injury, a nomogram model for predicting the risk of pulmonary infection is established, which has a good differentiation degree and prediction effect, and can provide a reference for medical staff to identify high-risk patients at an early stage, so as to take more targeted intervention measures. Key words: Craniocerebral injury; Pulmonary infection; Nomogram; Risk factor