Diagnostic Yield of Investigations in Symmetric Optic Neuropathy
Bibliographic record
Abstract
BACKGROUND: Symmetric optic neuropathy (SON) is commonly seen in neuro-ophthalmic practice and is often discovered incidentally. Although multiple investigations might be performed to discover the underlying cause, they are not always indicated. The aim of this study was to report a clinically reasonable and cost-effective approach to investigating patients with SON. METHODS: SON was defined as bilateral optic neuropathy with normal and/or symmetrically decreased central visual acuity, absence of relative afferent pupillary defect, presence of symmetric optic disc pallor, symmetric thinning of peripapillary retinal nerve fiber layer on optical coherence tomography, and absence of other identifiable causes of optic neuropathy. Records of all patients diagnosed with SON seen at a tertiary university-affiliated neuro-ophthalmology practice from 2016 to 2022 were reviewed to identify the yield of various investigations. Clinical data from the initial and last follow-up visit were obtained. Subgroup analysis was performed to ascertain whether diagnostic yield is higher in patients with severe visual loss (central acuity worse than 20/40) compared with those with mild visual loss (acuity 20/40 or better). RESULTS: One hundred thirty-six patients met inclusion criteria. Testing for OPA1 and OPA2 mutations had the highest diagnostic yield (16.0%), followed by mitochondrial genome sequencing (13.6%), serum vitamin B12 (6.1%), and serum folate (1.6%). MRI brain was performed in 54.4% of patients and had a diagnostic yield of only 5%. Both patients who had abnormal MRI had symptoms of demyelination at presentation. Patients were followed for a mean of 15.0 (SD 21.3) months. The most frequently identified etiologies of SON were Leber hereditary optic neuropathy (8.1%), alcohol/tobacco amblyopia (7.4%), vitamin B12 deficiency (5.9%), and dominant optic atrophy (2.9%). Patients with severe visual impairment were more likely to have a final diagnosis compared with those with milder visual impairment (63.9% vs 12.0%, P < 0.001). CONCLUSIONS: The diagnostic yield of investigating SON in patients with preserved visual function, normal diet, and absence of other neurological symptoms is very low. It is reasonable to observe patients with SON with mild visual impairment, reserving costly investigations for those with the visual acuity worse than 20/40 or progressive course.
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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 | 0.003 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".