P.091 Surgical outcomes for patients undergoing repeat endoscopic endonasal trans-sphenoidal surgery for recurrent pituitary adenomas
Bibliographic record
Abstract
Background: Endoscopic endonasal trans-sphenoidal surgery (EETS) is a commonly used approach for the surgical treatment of primary pituitary adenomas. The role of this approach in patients with recurrent disease remains unclear. Here we review a high-volume institutional experience with repeat EETS for recurrent pituitary adenomas and compare outcomes against primary surgeries. Methods: A retrospective chart review of patients who underwent EETS at Toronto Western Hospital from 2008-2016 for pituitary adenomas was completed. Baseline patient characteristics and surgical outcomes were recorded for each surgery. Primary and repeat operations were compared for analysis using Fisher’s exact test and t-test where appropriate. Results: 347 primary and 48 repeat surgery patients were identified. The median follow-up was 3.6 years (range 0-10.6 years). Rates of GTR, optic decompression, endocrinopathy cure, and visual improvement in repeat EETS were 44%, 21%, 22%, and 21%, respectively. While these rates are lower when compared to primary surgeries (75% p<0.001, 58% p<0.001, 75% p=0.01, 37% and p=0.04), they demonstrate that desirable outcomes are still achievable after EETS for recurrent disease. Conclusions: These results from a quaternary-care centre suggest that repeat EETS is a viable option that is safe and effective at improving the visual and endocrine status in select patients with recurrent pituitary disease.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".