Fatigue, sleep disorders, anaemia and pain in the multiple sclerosis prodrome
Bibliographic record
Abstract
BACKGROUND: There is increasing evidence of prodromal multiple sclerosis (MS). OBJECTIVE: The aim of this study was to determine whether fatigue, sleep disorders, anaemia or pain form part of the MS prodrome. METHODS: This population-based matched cohort study used linked administrative and clinical databases in British Columbia, Canada. The odds of fatigue, sleep disorders, anaemia and pain in the 5 years preceding the MS cases' first demyelinating claim or MS symptom onset were compared with general population controls. The frequencies of physician visits for these conditions were also compared. Modifying effects of age and sex were evaluated. RESULTS: MS cases/controls were assessed before the first demyelinating event (6863/31,865) or MS symptom onset (966/4534). Fatigue (adj.OR: 3.37; 95% CI: 2.76-4.10), sleep disorders (adj.OR: 2.61; 95% CI: 2.34-2.91), anaemia (adj.OR: 1.53; 95% CI: 1.32-1.78) and pain (adj.OR: 2.15; 95% CI: 2.03-2.27) during the 5 years preceding the first demyelinating event were more frequent among cases, and physician visits increased for cases relative to controls. The association between MS and anaemia was greater for men; that between MS and pain increased with age. Pre-MS symptom onset, sleep disorders (adj.OR: 1.72; 95% CI: 1.12-2.56) and pain (adj.OR: 1.53; 95% CI: 1.32-1.76) were more prevalent among cases. CONCLUSION: Fatigue, sleep disorders, anaemia and pain were elevated before the recognition of MS. The relative anaemia burden was higher in men and pain more evident among older adults.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".