Natural history of secondary-progressive multiple sclerosis
Bibliographic record
Abstract
OBJECTIVE: To examine prognosis and risk factors for progression to and from secondary-progressive multiple sclerosis (SPMS). METHODS: Patients with definite relapsing-remitting MS (RRMS), onset before July 1988, attending a British-Columbian MS clinic before July 1998, and at least one Expanded Disability Status Scale (EDSS) scores were selected from the population-based database. Time to SPMS (from onset and birth) and the subsequent time to EDSS 8 were examined, as were potential risk factors. RESULTS: In all, 2484/2837 (87.6%) were relapsing-remitting (RR) at onset, with 1445/2484 (58.2%) reaching SPMS, taking a median 18.9 years (95% CI: 18.2-19.7). Those younger at onset took longer to reach SPMS (P < 0.0005), but did so at a younger age (P < 0.0005). Males reached SPMS more rapidly from onset and at a younger age (P < 0.0005), but were around the same age as females at EDSS 8 (P = 0.975). Characteristics at SPMS onset associated with a longer time from SPMS to EDSS 8 and an older age at EDSS 8 were: longer disease duration (P < 0.02), older age (P < 0.01) and lower EDSS (P < 0.0005). Onset symptoms had little influence on time to SPMS or subsequent progression. CONCLUSIONS: The RR phase lasted on average almost two decades, being shorter for males and those older at onset of MS. However, neither were necessarily unfavorable predictors as those older at onset were typically older at SPMS and eventually males and females reached EDSS 8 at around the same age. A longer RR phase was a favorable predictor of disease progression in SPMS. Furthermore, reaching SPMS at an older age or lower EDSS did not necessarily confer a worse outcome.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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".