Postoperative intracranial infection (ICI) is a serious complication that occurs after craniotomy, typically caused by the invasion of microorganisms such as bacteria into the sterile cranial cavity. Aneurysm clipping is one of the primary treatment methods for intracranial aneurysms, and ICI can significantly impact patient prognosis. Our investigation aims to systematically identify the determinants of postoperative ICI after aneurysm clipping and develop a robust predictive model for clinical risk assessment. To eliminate potential confounding factors introduced by aneurysm rupture and subarachnoid hemorrhage, our study focuses exclusively on patients with unruptured intracranial anterior circulation aneurysms.

We conducted a retrospective analysis of clinical data from 428 patients with anterior circulation aneurysms. Based on the occurrence of postoperative ICI, patients were stratified into non-infected group and infected group. Univariate and multivariate statistical analyses were performed to evaluate the following variables: gender, age, body mass index (BMI), hypertension, diabetes mellitus, aneurysm location, number of aneurysm clips applied, operative duration, intraoperative blood loss, cerebrospinal fluid (CSF) leakage, and postoperative intracranial hemorrhage or cerebral infarction in the surgical region. Subsequently, a predictive nomogram was constructed based on the multivariate regression results to generate a robust predictive model.

Among 428 patients with anterior circulation aneurysms, 38 developed postoperative ICI. Univariate analysis revealed that BMI, diabetes mellitus, operative duration, intraoperative blood loss, CSF leakage, and postoperative cerebral hemorrhage or infarction were significant factors influencing ICI. In contrast, variables such as gender, age, hypertension, and the number of aneurysm clips applied demonstrated no statistically significant association. Subsequent logistic regression analysis identified elevated BMI, diabetes mellitus, prolonged operative duration, substantial intraoperative blood loss, and postoperative CSF leakage as independent risk factors for ICI in UIA patients. A receiver operating characteristic (ROC) curve was constructed based on the predicted probabilities of ICI, yielding an area under the curve (AUC) of 0.8756, indicating strong predictive accuracy.

Postoperative ICI in patients with anterior circulation aneurysms is influenced by multiple factors, including BMI, diabetes mellitus, operative duration, intraoperative blood loss, and CSF leakage. A predictive model constructed based on the relative impact of these factors may assist clinicians in anticipating potential infection events during the perioperative period.