P.147 Endoscopic transorbital approach to the skull base: a single centre 8 year experience
Bibliographic record
Abstract
Background: Minimally invasive endoscopic techniques via the transorbital approach (ETOA) is emerging as an alternative approach for addressing skull base tumours. This study aims to showcase our institution’s 8 year experience in using ETOA, detailing the surgical technique employed and presenting comprehensive patient outcomes. Methods: A retrospective analysis was conducted on data from 32 patients who underwent ETOA within the past eight years. Demographic data was obtained as well as information on surgical approaches, intra-operative findings, recurrence and complications. Results: 33 ETOA procedures were performed on 29 patients, with an average age of 45, 14 of whom were women. The superior orbital corridor was utilized in 100% of cases, and in 79.17%, ETOA was complemented by a transnasal approach. Spheno-orbital meningioma accounted for the most common surgical indication (36.36%, n=12, followed by lateral frontal sinus mucocele (18.75%, n=6). The median length of stay was one day.Transient V1 numbness was the primary complication (33%, n=8), and 18.75% (n=6) necessitated another surgery. Notably, no mortality was associated with this procedure. Conclusions: Our institution’s experience underscores the notable safety and effectiveness of ETOA, The main complications being transient V1 numbness, proptosis, transient diplopia. Revision surgery was only required in 6 out of 33 cases.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".