Nomogram for Predicting the Risk of Post-Craniotomy Intracranial Infection in Patients With Brain Tumors

This study aims to develop a nomogram to predict the risk of post-craniotomy intracranial infection (PCII) in patients with brain tumors.

Data from patients with brain tumors hospitalized between January 2021 and December 2023, encompassing personal attributes and clinical assessments, were compiled from the First Affiliated Hospital of Jinan University. Multifactorial analysis was employed to identify potential PCII risk factors. A nomogram model was crafted based on these risk factors. The model's predictive efficacy was evaluated using the concordance index (C-index), area under the receiver operating characteristic curve (AUC), and calibration curve. Additionally, PCII risk was forecasted at -3, -7, and -14 days post-surgery.

Among 968 patients with brain tumors, 120 developed PCII post-surgery, resulting in a 12.40% incidence rate. Via multivariate Cox proportional hazards regression analysis and Akaike information criterion, nine PCII risk factors were identified, including BMI, surgical duration, preoperative albumin levels, hypertension, diabetes, indwelling drainage tube usage, subtentorial location, cerebrospinal fluid leakage, and intraoperative blood loss ≥ 400 mL. A nomogram model incorporating these predictors yielded a C-index of 0.876. The AUC values for PCII at -3, -7, and -14 days were 0.787, 0.842, and 0.873, respectively. Notably, the calibration curve illustrated close alignment between predicted and actual infection rates in patients with brain tumors at -3, -7, and -14 days.

We developed a nomogram model to predict the occurrence of PCII in patients with brain tumors, facilitating the assessment of PCII risk in this patient population.