The Impact of Gender on Recovery from Acute Optic Neuritis: Does Sex Matter? (P01.137)
Bibliographic record
Abstract
Objective: Given that estrogen has been postulated to have a neuro-protective effect at the optic nerve head, we hypothesized that men would have lower retinal nerve fiber layer (RNFL) values relative to women after an acute optic neuriitis (ON) event. Background Optic neuritis is an inflammatory injury of the optic nerve, which represents a single lesion model of multiple sclerosis (MS). Most ON patients are young women, albeit the basis of the female predilection remains unclear. In this study, we aimed to use the ON model of MS to determine whether retinal nerve fiber layer (RNFL) values differed between men and women after an acute isolated ON event. Design/Methods: In this prospective cohort study, 39 men and 105 women with acute ON underwent repeat ophthalmic and optical coherence tomography (OCT) testing over a 6-month period. The main outcome measures were RNFL measurements in ON eyes for male and female patients 6-months after ON. Results: Men were older (mean age = 39 years) than women (35) (p = 0.05) in this study; and more men (62%) than women (41%) had a diagnosis of MS versus a clinically isolated syndrome (CIS) (p = 0.02) . Because age and MS diagnosis were two significant covariates, both variables were controlled for in subsequent multiple regression analyses. Acutely, there were no differences in RNFL values between genders, whereas after 6-months mean RNFL values were lower in men (74µm) than women (91µm) (p . Retinal nerve fiber layer measurements below 75µm, were associated with clinically and statistically significant reductions in visual recovery after ON. Conclusions: There are differences in recovery between men women after ON. Our findings raise intriguing questions about the potential impact of gender in MS; and the neuro-protective benefits of estrogen, which may be explored in future studies. Supported by: The Multiple Sclerosis Society of Canada. Disclosure: Dr. Costello has received personal compensation for activities with Biogen Idec and Novartis. Dr. Costello has received personal compensation for activities with Biogen Idec and Novartis. Dr. Pan has nothing to disclose. Dr. Burton has received personal compensation for activities with Biogen Idec and Novartis. Dr. Trufyn has nothing to disclose.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".