"Selar coefficient" and risk factors associated with cerebrospinal fluid leakage in endoscopic endonasal surgery for neuroendocrine pituitary tumors - RANC, Revista Argentina de Neurocirugia; Monsalve, Martín Andrés; Ruella, Mauro Emiliano; Domecq Laplace, Lucila; Fraire, Jazmín Azul; Caffaratti, Guido; Cervio, Andrés (Revista Argentina de Neurocirugía, 2024)
Background: neuroendocrine pituitary tumors (PitNET) account for approximately 15% of primary intracranial neoplasms. The endoscopic endonasal approach (EEA) is currently the most common surgical technique to treat this pathology. One of the main complications of this procedure is the CSF leakage. Objectives: to describe the risk factors contributing to the development of CSF leakage in EEA for PitNET. Methods: a retrospective analysis was conducted on patients operated by the same surgeon between 2019 and 2023 with a diagnosis of PitNET using EEA. Clinical, radiological, surgical, and oncological variables associated with intraoperative CSF leakage (FiOP) and postoperative CSF leakage (FpOP) were analyzed. A novel tool is proposed to aid in diagnosing this complication: the “sellar coefficient.” Results: the incidence of FiOP was 41.3%. Univariate analysis identified several significant risk factors for this complication. In multivariate analysis, four factors showed independent association: pituitary apoplexy, suprasellar tumor extension above tuberculum sellae - dorsum sellae (TS-DS) plane, subtotal tumor resection, weak sellar barrier, and sellar coefficient. Regarding FpOP, its incidence was 3.3%. The grade of FiOP was the main determinant factor. Additionally, FpOP was associated with an increased risk of complications such as meningitis and vasospasm. Conclusion: CSF leaks in EEA for PitNET have an impact on surgical time, hospital stay and increase the risk of complications. This emphasizes the importance of comprehensive preoperative evaluation and precise surgical planning. The introduction of the "sellar coefficient”, a simple and reproducible radiological metric, could contribute to predicting the risk of CSF leakage.