The Role of Optical Coherence Tomography in Differentiating Optic Disc Drusen from Optic Disc Edema
Bibliographic record
Abstract
An elevated optic nerve head can be an ominous sign, sometimes signifying an underlying basis for raised intracranial pressure. Alternatively, patients may harbor a different mechanism for this optic nerve head appearance, including optic disc drusen (ODD), which does not confer any life-threatening implications. It is important to refine the approach to distinguishing ODD from papilledema because this is a relatively common, and important, conundrum encountered in clinical practice. Optical coherence tomography (OCT) is a noninvasive, readily accessible, and cost-effective ocular imaging technique that can improve the diagnostic accuracy for detecting ODD; or, instead, increase the index of suspicion for papilledema, thus prompting additional investigations needed to identify (or exclude) potential causes of raised intracranial pressure. In this review, we will discuss the value of OCT in the diagnostic approach to cases of mild optic disc elevation, with acknowledgment of the potential pearls and pitfalls of this imaging technology. In particular, we will emphasize the helpful role OCT can play in differentiating cases of ODD from mild papilledema in the context of idiopathic intracranial hypertension (IIH).
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".