Maculopathies Referred to Neuro-Ophthalmology Clinic as Optic Neuropathies: A Case Series
Bibliographic record
Abstract
BACKGROUND: The clinical features of maculopathies and optic neuropathies often overlap: Both present with decreased visual acuity and variable loss of color vision; thus, maculopathy can be misdiagnosed as optic neuropathy, leading to patient harm. We aimed to determine what findings and/or tests were most helpful in differentiating between optic neuropathy and maculopathy. METHODS: A retrospective chart review of consecutive patients over 4.5 years who were referred to neuro-ophthalmology clinics with the diagnosis of optic neuropathy but whose final diagnosis was maculopathy. Patient demographics, mode of presentation, clinical profile, complete ophthalmological examination, results of all ancillary testing, and final diagnosis were recorded. RESULTS: A total of 47 patients (27 women) were included. The median age was 55 years (range, 18-85). Most referrals were by ophthalmologists (72.3%) and optometrists (12.8%). The diagnosis of maculopathy was made in 51.1% of patients at the time of first neuro-ophthalmic consultation. Only 6.4% patients (3) had relative afferent pupillary defect. Benign disc anomalies (tilted, myopic, small, or anomalous discs) were present in 34.0%, and 21.3% had pathologic disc changes unrelated or secondary to maculopathy. Macular ocular coherence tomography (OCT) was abnormal in 84.4% (with outer retinal pathology in 42.2% and inner retina pathology in 17.8%). Retinal nerve fiber layer (RNFL) thickness was normal in 82.6% of patients. CONCLUSIONS: Macular OCT is a high-yield test in differentiating between optic neuropathy and maculopathy and should be obtained in patients with suspected optic neuropathies who have normal RNFL thickness. Macular dystrophies, particularly cone dystrophies, unspecified retinal disorders, and macular degeneration were the most common mimics of optic neuropathy. The diagnosis was often present on OCT of the macula. The presence of coexistent benign and pathological disc anomalies may lead to maculopathy being misdiagnosed as optic neuropathy.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".