P.156 Outcomes of Cranial Nerve Deficits in Patients with Pituitary Apoplexy: The Ottawa Hospital Experience
Bibliographic record
Abstract
Background: One of the rare but urgent presentations of a pituitary tumor is pituitary apoplexy. In this case series, we describe our experience regarding the cranial nerve recovery in patients with pituitary apoplexy following endoscopic endonasal transsphenoidal surgery (EETS). Methods: Retrospective cohort study with patient characteristics, tumor type, endocrine data, operation data collected. Postoperative data were extracted for the follow-up period available for each patient. Results: 15 pituitary apoplexy cases were identified. The cranial nerve deficits presented at admission were: visual deficit (33% patients); unilateral third nerve palsy (47% patients), unilateral sixth nerve palsy (27% patients). Postoperatively, 60% of patients with preoperative visual deficit had normal visual fields and the other 40% showed improvement. From those with oculomotor nerve dysfunction preoperatively, 43% have returned to normal nerve function and 57% presented improvement. 75% cases of abducens nerve palsy resolved postoperatively, while 25% showed improvement. Conclusions: Based on this series, surgical treatment should be offered to patients presenting with cranial nerve deficit in the setting of pituitary apoplexy. In this series, all cranial nerve deficits either returned to normal or improved following surgery. Though a small series, the presented results are superior to those reported in the literature for conservative management.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".