Physical activity demonstrates protective associations with structural visual metrics in children with multiple sclerosis through time
Bibliographic record
Abstract
Background: Previous work has demonstrated that higher levels of physical activity (PA) are associated with better retinal fiber integrity in children with multiple sclerosis (MS). Objective: To determine whether high PA levels are associated with retinal fiber integrity through time in children with demyelinating disease. Methods: Children with MS or monophasic acquired demyelinating syndromes (mono-ADS) were included. PA level was assessed by questionnaire, and a spectral-domain optical coherence tomography (OCT) scanner determined retinal nerve and ganglion cell inner plexiform fiber layer thickness (RNFL and GCIPL, respectively). Linear mixed models were used to analyze longitudinal associations. Results: Children with MS ( n = 28, 20F, mean age 14.6 (standard deviation (SD) ±2.4)) and mono-ADS ( n = 24, 11F, mean age 9.5 (SD ±4.5)) took part. In children with MS, RNFL and GCIPL thickness was shown to decline by 1.0 mm ( p < 0.05) over time. More active children with MS had thicker GCIPL through time compared to those who were inactive (2.5 mm, p < 0.01). Furthermore, taking part in any strenuous PA was associated with greater RNFL and GCIPL thickness (1.5–2.1 mm, p < 0.05). These differences were not found in children with mono-ADS. Conclusion: Moderate to vigorous PA is associated with better retinal integrity over time in pediatric MS. Future interventions should evaluate whether changes to PA level coincide with changes to retinal integrity in children 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".