Prognostic determination using optical coherence tomography compared with visual functions in optic neuritis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: The majority of optic neuritis patients often notice improvement and gain stability of their visual functions, however, evidences of ongoing retinal nerve fiber layer (RNFL) thinning have been reported. Purposes: To investigate the correlation between RNFL thickness measured with Optical coherence tomography (OCT) and visual function tests and to determine the utility of OCT in visual prognostic assessment of optic neuritis. Method: A prospective study was performed in 12 patients with acute isolated optic neuritis. Best corrected visual acuity (BCVA), Swedish interactive threshold algorithms (SITA) 30-2 strategy on Humphrey field analyzer, and fast RNFL thickness analysis were performed on both affected and fellow eyes at baseline, 1.5, three and six months. Results: Mean BCVA and average mean deviation (MD) of the affected eye were significantly different from the fellow eyes at baseline. Affected eyes had significant thinner of RNFL at baseline, 1.5, three, and six months. Significant correlations between (i) mean RNFL thickness and BCVA at 1.5 ( r = 0.707, p = .010), (ii) mean RNFL thickness and MD at 1.5 months ( r = 0.674, p = .016) and six months( r = 0.710, p = .032), (iii) mean RNFL thickness at 1.5 months and MD at six months ( r = 0.782, p = .013). Conclusion: A correlation between RNFL thickness and visual function tests indicates that OCT might have roles in detection and prediction of RNFL damage in Optic neuritis (ON) patients despite no evidence of MS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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