Disability progression in aggressive multiple sclerosis
Bibliographic record
Abstract
OBJECTIVE: To examine disease progression in 'aggressive' multiple sclerosis (MS), British Columbia, Canada (1980-2009). METHODS: Aggressive (or 'malignant') MS was defined as Expanded Disability Status Scale (EDSS) ⩾6 within 5 years from onset. The first EDSS ⩾6 was termed 'baseline'. Within 2, 3 and 5 years post-baseline, patients were categorized as follows: 'worsened' or 'improved', relative to baseline EDSS (the remainder exhibited no change or had no new scores). The associations between patient characteristics (sex, relapsing onset/primary progressive, onset age, onset symptoms, disease duration, cumulative prior relapses and baseline EDSS) and worsening in disability were examined longitudinally using logistic regression. RESULTS: Of the 225/4341 (5.2%) aggressive/malignant MS patients, 134 (59.6%) were female, 167 (74.2%) were relapsing onset, 94 (41.8%) had received disease-modifying drugs at some point and the mean follow-up was 8.7 years. The proportion of patients who 'worsened' increased from 40.4% to 57.8%, while those who 'improved' varied little (range, 8.9%-10.2%). The odds of worsening increased with disease duration (adjusted odds ratio (AOR) = 1.36; 95% confidence interval (CI) = 1.22-1.52) and the presence of primary progressive (vs relapsing-onset) MS (AOR = 1.85; 95% CI = 1.01-3.38). CONCLUSION: Apart from disease duration and a primary progressive course, no clinically useful associations of subsequent disease worsening in patients with aggressive/malignant MS were identified.
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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 | 0.002 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".