P.161 Postoperative visual deterioration after endoscopic pituitary adenoma resection: predictors, management, and long-term sequelae
Bibliographic record
Abstract
Background: Postoperative visual deterioration following endoscopic endonasal surgery for pituitary adenoma is very rare yet significant morbidity. Visual deficit can arise from iatrogenic injury, compression or ischemic insults. The specific predictors of visual decline and their correlation with the effectiveness of various interventions remain poorly understood. Methods: We retrospectively reviewed data from790 patients who underwent endoscopic endonasal surgery for pituitary adenoma between 2014-2024. We included all the patients who had New Postoperative visual deterioration. Demographic, preoperative, intraoperative, postoperative data were collected and analyzed. Results: Nine patients (1.13%) experienced early postoperative visual deterioration. None of the patient has intraoperative report of direct injury to the optic apparatus, ischemic etiology was seen in five patients. Four patients underwent early reoperation to explore and decompress the optic apparatus. Vision was restored to baseline after reoperation in all 4 compressive cases. In the ischemic group (n=5), three patients improved with supplemental oxygen and hypervolemic-hypertensive therapy (p=0.03). Conclusions: Prognosis and outcome of Postoperative visual deterioration depends on the underlying cause and the effectiveness of intervention. Compressive etiology has a favorable prognosis when identified and managed with reoperation and decompression. Ischemic etiology potentially treatable with supplemental oxygen hypervolemic-hypertensive and high mean arterial pressure in more than half of 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 | 0.002 |
| 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 | 0.000 |
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".