Díaz-Bello Sergio, Muñuzuri-Camacho Marco Antonio, Rodríguez-Hernández Luis, Castro-Martinez Elvira, Villanueva-Castro Eliezer, Coutinho-Thomas Domingo, Villalobos-Díaz Rodolfo, López-Valencia German, Moncada-Habib Tomas, Rodríguez-Hernández Ivan Abdiel, Cacho-Díaz Bernardo, Gutierrez-Aceves Guillermo Axayacalt, Moreno-Jiménez Sergio, Gonzalez-Aguilar Alberto
Neurosurgery, Instituto Nacional de Neurología y Neurocirugía Manuel Velasco Suárez, Mexico City, MEX.
Neurology, Instituto Nacional de Neurología y Neurocirugía Manuel Velasco Suárez, Mexico City, MEX.
Cureus. 2025 May 19;17(5):e84424. doi: 10.7759/cureus.84424. eCollection 2025 May.
To identify risk factors for postoperative seizures in patients with brain tumors without preoperative seizures and develop a predictive scoring system to guide antiepileptic drug (AED) prophylaxis.
A retrospective analysis was conducted on patients with intra-axial brain tumors and no history of preoperative seizures or AED use. Logistic regression identified significant predictors of postoperative seizures, and a scoring system was created using receiver operating characteristic (ROC) analysis. Data were drawn from a neuro-oncology database that had been active since 1970.
A total of 446 patients were included from 16,918 records, with a mean age of 45.1 years (67.8% male, 345 with gliomas). Over 20% experienced postoperative seizures. Logistic regression identified five significant predictors, including tumor location, patient age, extent of resection, and neoplastic edema. A scoring system was developed to improve seizure risk assessment and seizure control. The BRAINNN Score (Brain tumor-associated Risk Assessment Index developed at the National Institute of Neurology and Neurosurgery, INNN) is a newly designed predictive tool to estimate the risk of postoperative seizures in brain tumor patients without a prior history of seizures.
This study proposes a personalized approach to AED prophylaxis using a novel, objective scoring system based on clinically relevant factors. This framework has the potential to optimize perioperative care and improve outcomes for patients with brain tumors.
确定术前无癫痫发作的脑肿瘤患者术后癫痫发作的危险因素,并开发一种预测评分系统以指导抗癫痫药物(AED)预防。
对轴内脑肿瘤且无术前癫痫发作史或未使用过AED的患者进行回顾性分析。逻辑回归确定术后癫痫发作的显著预测因素,并使用受试者工作特征(ROC)分析创建评分系统。数据来自自1970年以来一直活跃的神经肿瘤学数据库。
从16918条记录中纳入了446例患者,平均年龄45.1岁(男性占67.8%,345例为胶质瘤患者)。超过20%的患者经历了术后癫痫发作。逻辑回归确定了五个显著预测因素,包括肿瘤位置、患者年龄、切除范围和肿瘤性水肿。开发了一种评分系统以改善癫痫发作风险评估和控制。BRAINNN评分(国立神经病学和神经外科研究所开发的脑肿瘤相关风险评估指数)是一种新设计的预测工具,用于估计无癫痫发作史的脑肿瘤患者术后癫痫发作的风险。
本研究提出了一种基于临床相关因素的新型客观评分系统的个性化AED预防方法。该框架有可能优化围手术期护理并改善脑肿瘤患者的预后。