Development and Validation of a Predictive Model for Postoperative Intracranial Infections in Neurosurgery with Risk Factor Analysis

Currently, the diagnosis of postneurosurgical intracranial infection is mainly dependent on cerebrospinal fluid (CSF) bacterial culture, which has the disadvantages of being time-consuming, having a low detection rate, and being easily affected by other factors. These disadvantages bring some difficulties to early diagnosis. Therefore, it is very important to construct a nomogram model to predict the risk of infection and provide a basis for early diagnosis and treatment.