Risk Prediction and Management for Central Nervous System Infection After Resection for Gliomas-The 8-Year Experience from a Tertiary Medical Center

Objective: To identify risk factors for central nervous system infection (CNSI) following glioma resection and develop a predictive model. Methods: Retrospective analysis of 435 glioma resection cases was conducted to assess CNSI risk factors. A nomogram predictive model was constructed and validated internally and externally. CSF characteristics and antibiotic use in CNSI patients were summarized and the impact of CNSI on long-term prognosis was evaluated. Results: CNSI incidence was 14.9%. Independent risk factors included ventricular opening, postoperative systemic infection, maximum diameter ≥ 5 cm, and preoperative peripheral blood monocyte percentage ≥ 10%. The predictive model showed good performance (C statistic = 0.797, AUC = 0.731). CNSI patients had elevated CSF protein and leukocytes, with meropenem and vancomycin as primary antibiotics. CNSI had no significant impact on long-term prognosis. Conclusions: Key risk factors for CNSI were identified, and an effective predictive model was established, providing important references for clinical decision-making and CNSI management.