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Risk factors analysis and a nomogram model establishment for late postoperative seizures in patients with meningioma

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BACKGROUND Postoperative seizures (Sz) following surgical resection of intracranial meningiomas negatively impacts the quality of life of patients. However, there is still unclear with respect to the risk factors of… Click to show full abstract

BACKGROUND Postoperative seizures (Sz) following surgical resection of intracranial meningiomas negatively impacts the quality of life of patients. However, there is still unclear with respect to the risk factors of and long-term freedom to Sz in patients with meningiomas. This study aimed to identify independent predictors and develop a nomogram model of late postoperative Sz to optimize postoperative surveillance. METHODS We retrospectively analyzed 318 meningioma patients who underwent surgical resection at the Subei People's Hospital of Jiangsu province from January 2014 to December 2018. Then, clinical data were collected for further analysis and nomogram construction. RESULTS In our cohort, 62 patients (19.50%) experienced preoperative Sz, 12 patients (3.77%) experienced early postoperative Sz, and 56 patients (17.61%) experienced late preoperative Sz. Multivariate logistic regression analysis revealed that preoperative Sz, convexity location, tumor maximal size ≥3.5 cm, medical/surgical complications and tumor recurrence/progression were independent predictors of late postoperative Sz. A nomogram was developed by employing these five significant predictive factors. Statistical analysis showed that this model had a good discrimination performance. Among 32 patients who had more than one year follow up period form first late postoperative Sz, 17 (53.13%) patients experienced good Sz control. The probability of Sz freedom in the 2-year follow-up was roughly 75.2% among patients with preoperative Sz, and 84.8% among patients without preoperative Sz. CONCLUSIONS This nomogram model will be useful to assist clinicians to assess late postoperative Sz occurrence, identify high-risk patients early and schedule AEDs treatment, but further external validations are needed.

Keywords: postoperative seizures; analysis nomogram; nomogram model; risk factors; late postoperative

Journal Title: Journal of Clinical Neuroscience
Year Published: 2020

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