Construction of a risk nomogram prediction model for intracranial infection after craniotomy

OBJECTIVE To analyze the risk factors for intracranial infection in patients after craniotomy, establish a nomogram model for predicting risk and validate it.

METHODS A retrospective analysis was conducted on 1 185 patients who underwent craniotomy in the Department of Neurosurgery at Quanzhou First Hospital from Jan. 2022 to Dec. 2024. These patients were divided into an infection group (n=106) and a non-infection group (n=1 079) based on the occurrence of intracranial infection during hospitalization. Logistic regression analysis was used to screen for risk factors of postoperative intracranial infection, and a nomogram prediction model was constructed.

RESULTS Logistic regression analysis showed that prolonged operation time, preoperative diabetes, lumbar cisterna drainage catheter placement, ventricular drainage >7 days, artificial dura mater application and intraoperative blood loss ≥300 ml were risk factors for postoperative intracranial infection (P < 0.05). Based on these six indicators, a nomogram prediction model was established. The nomogram model demonstrated good predictive performance upon validation: both the concordance index (C-index) and the area under the receiver operating characteristic curve (AUC) were 0.804, indicating excellent discrimination. The Hosmer-Lemeshow test (χ²=3.218, P=0.781) and the calibration curve mean absolute error(MAE)=0.009 both indicated precise calibration performance. The validation by the decision curve analysis (DCA) suggested that when the prediction probability threshold of the nomogram model was set between 0.050 and 0.800, the clinical net benefit reached its maximum, indicating optimal clinical application value.

CONCLUSIONS The risk nomogram prediction model for intracranial infection after craniotomy constructed in this study demonstrates good predictive performance and clinical applicability. The relevant predictive indicators are scientific and easily obtainable, providing an effective reference for the diagnosis of intracranial infection after craniotomy.