Chronic chiasmal compression and persistent visual field defect without detectable changes in optical coherence tomography of the macular ganglion cell complex
Bibliographic record
Abstract
PURPOSE: Optical coherence tomography (OCT) of the retinal nerve fiber layer (RNFL) and macular ganglion cell complex (GCC) are important in the ophthalmological evaluation of patients with sellar masses. Changes in OCT of the RNFL and macular GCC often precede visual field changes in patients with chronic chiasmal compression. OCT of the macular GCC has been shown to have better correlation with visual function and allow for even earlier detection of compression of the anterior visual pathways. We present a case of a chronic visual field defect from a pituitary adenoma with largely normal OCT parameters and only subtle changes in OCT of the RNFL and no perceptible changes in OCT of the macular GCC. OBSERVATIONS: A 32-year-old man presented with a four-month history of decreased vision in his left eye and was found to have a monocular temporal visual field defect from a pituitary adenoma. OCT of the RNFL showed only a subtle change in that the nasal quadrant was mildly reduced and the optic nerve did not follow the ISNT rule. There was no asymmetry, deviation from normal parameters or differences in the nasal and temporal sextants on OCT of the macular GCC. This remained stable after testing two months later and a worsening visual field defect. He was found to have an elevated prolactinoma and after initiation of cabergoline, his visual field defect rapidly resolved within a few days. CONCLUSIONS AND IMPORTANCE: OCT RNFL and macular GCC may have parameters in the normal range in patients with chronic chiasmal compression, emphasizing the importance of both anatomical and psychophysical testing. OCT of the RNFL may show these changes earlier than OCT macular GCC and both should be performed for the pre-treatment evaluation of patients with sellar masses. Preserved RNFL and macular GCC thickness confer a good prognosis as demonstrated in this case with rapid resolution of visual changes after medical treatment.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".