P.155 Endoscopic endonasal approaches for the resection of anterior skull base meningiomas
Bibliographic record
Abstract
Background: This study aims to review the clinical outcomes, extent of resection, complications, and prognostic factors in patients undergoing endonasal endoscopic resection (EEA) of anterior cranial base meningiomas. Methods: We conducted a retrospective review of 25 patients who underwent EEA resection of these lesions between 2001 and 2023. We assessed the extent of resection, complications, postoperative outcomes, and key technical aspects of the procedure. Results: 84% of patients were classified as ASA class III. Additionally, 64% of patients presented with visual disturbances. The mean blood loss was 472 ml. Intraoperative lumbar drains were used in 40% of cases, and dural sealants in 56%. A pedicled nasal flap was employed for reconstruction in 92% of cases. One vascular injury was documented, and 16% of patients developed a cerebrospinal fluid (CSF) leak in the postoperative period The degree of resection varied according to tumor location. Prognostic factors for achieving gross total resection, functional improvement, and key factors for reconstruction are discussed. The rate of CSF leaks decreased dramatically in the later years of the series Conclusions: Cranial base meningiomas can be successfully managed via a purely endoscopic endonasal approach, with acceptable morbidity and mortality rates.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".