Clinical and Demographic Predictors of Optic Neuritis Subtype
Why this work is in the frame
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Bibliographic record
Abstract
To determine which clinical features differentiate acute optic neuritis (ON) subtypes to support treatment decision-making in patients when the diagnostic work-up is incomplete or inconclusive. We performed a retrospective study at two academic centers. ON was classified as idiopathic/multiple sclerosis-associated (I/MS-ON; also known as “typical” ON) versus non-I/MS-ON (e.g. neuromyelitis optica; also known as “atypical” ON). Multiple linear regression models assessed the association between ON subtype and clinical features including: demographics, presence of optic disc edema, bilaterality (simultaneous ON involving both eyes), and baseline visual acuity (logMAR). Sensitivity analyses examined the impact of incomplete race/ethnicity data on subtype. Among 614 episodes (518 patients), most ON events (n = 440, 85%) were I/MS-ON. In univariate analyses, bilaterality (OR 6.67 [95%CI 3.7,11.11]), presence of optic disc edema (OR 2.22 [95%CI 1.32,3.70]), and age (OR 1.32 [95%CI 1.08,1.61] for each decade) were significantly associated with higher odds of having non-I/MS-ON compared to I/MS-ON. In multiple logistic regression modeling, each decade of life (OR 1.35 [95%CI 1.06,1.69]), bilaterality (OR 7.69 [95%CI 4.17,14.29]), and each point increase in baseline logMAR (OR 1.47 [95%CI 1.11,1.92]) were associated with increased odds of having non-I/MS-ON compared to I/MS-ON. In sensitivity analyses, age no longer significantly predicted ON subtype. When considering multiple clinical factors, bilateral simultaneous ON and worse baseline visual acuity were significantly associated with non-I/MS-ON. Older age may also be associated with non-I/MS-ON, but additional studies are needed. These observations may guide decision-making in patients with ON, in which diagnostic testing is incomplete or inconclusive.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it