“Seeing” in NARCOMS: a look at vision-related quality of life in the NARCOMS registry
Bibliographic record
Abstract
BACKGROUND: Research on vision-related quality of life (QOL) in multiple sclerosis (MS) is still limited. Tools such as the Visual Functioning Questionnaire-25 (VFQ-25) and the Vision Performance Scale (VPS) facilitate assessments of the severity of visual impairment and its impact on daily life. OBJECTIVE: The objective of this paper is to examine vision-related QOL, comorbid eye conditions, use of visual aids and utilization of eye-care providers in the North American Research Committee on Multiple Sclerosis (NARCOMS) population, and to explore these issues in those with a history of optic neuritis (ON) and diplopia. METHODS: In 2008, NARCOMS registrants reported on their use of visual aids, the VFQ-25, VPS, history of ON, diplopia, refractive error conditions (REC) and comorbid eye diseases (CED). We conducted regression analyses and correlations between select variables. RESULTS: The response rate for the survey was 60.4%. Of the 9107 responders, 66.7% reported visual disability measured by VPS. Of respondents, 43.1% had a history of ON and 38.6% reported prior diplopia. Frequencies of myopia (51.8%), hyperopia (26.6%), and uveitis (3.4%) exceeded those expected for the general population. Mean (SD) VFQ-25 composite score was 82.0 (14.2). A history of ON or diplopia accounted for 9.7% of the variance in the VFQ-25; 90.6% of respondents used glasses or contact lenses. Rates of utilizations of eye-care providers were lower than expected. CONCLUSION: Prior ON, diplopia, REC and CED adversely impact vision-related QOL in MS. Increased utilization of eye-care providers and use of visual aids could improve vision-related QOL in people with MS.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".