Natural history of the anterior visual pathway after surgical decompression in patients with pituitary tumors
Bibliographic record
Abstract
Introduction: Visual dysfunction is one of the primary indications for surgical management of pituitary tumors with the goal of terminating the progressive decline in vision. Unfortunately, it is difficult to predict how successful surgical decompression will be in these patients. The purpose of this study was to assess the structural changes seen in the anterior visual pathway after pituitary tumor resection. Methods: 13 patients (7F) underwent endoscopic tumor resection for pituitary macroadenoma. Each patient underwent a full ophthalmologic assessment including optical coherence tomography (OCT) preoperatively and postoperatively at 3-6months and 9-12months. Post-surgical changes in the retinal nerve fiber layer thickness (RNFLT) for each eye (N=26) were compared in cases with normal preoperative RNFLT (greater than 80 μm) versus those with abnormally thinned RNFLT (less than 80 μm). Results: For 9 cases with thinned RNFLT preoperatively (mean=70.1 μm±8.5), there was a significant decline in RNFLT at 3-6 months follow-up (mean change= −3.8 μm;p=0.002), which did not recover even at 9-12months after surgery (mean=67.6 μm±12.7). Contrastingly, eyes with normal RNFLT preoperatively (mean=89.7 μm±9.4) did not show significant postoperative thinning (mean change= −1.9 μm). Conclusion: Even after a complete surgical decompression, there are ongoing structural changes in the anterior visual pathway in patients with compressive neuropathy. There may be a point of no return where surgical decompression may not prevent further structural degeneration.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".