Early Relapses, Onset of Progression, and Late Outcome in Multiple Sclerosis
Bibliographic record
Abstract
OBJECTIVES: To investigate the relationship among attacks in the first 2 years (early relapses), secondary progression (SP), and late disability in multiple sclerosis (MS). DESIGN: Cohort study with follow-up of 28 years. SETTING: Referral MS center. PATIENTS: Patients (N=730) with relapsing-remitting MS diagnosed according to Poser criteria, from the database of the London Multiple Sclerosis Clinic, London, Ontario, Canada. MAIN OUTCOME MEASURE: Long-term evolution of patients with high (≥ 3 attacks) and early (within the first 2 years of the disease) frequency of relapses. In the total SP population and in patients grouped by numbers of early relapses, we assessed the predictive effect of latency to progression (time to SP) on times to attain cane requirement (Disability Status Scale score of 6 [DSS 6]) and bedridden status (DSS 8). RESULTS: Among the group with frequent early relapses (n=158), outcomes were variable. Although 103 (65.2%) experienced rapid conversion to SP MS (median duration, 5 years) and rapidly attained DSS 6 and DSS 8 scores (7 and 17 years, respectively), the remainder (n=55) did not enter the SP phase, despite adverse early relapse features. Among the total SP population, longer latency to progression was associated with lower probability of attaining DSS 6 (odds ratio, 0.76 [95% CI, 0.69-0.84] and 0.44 [95% CI, 0.37-0.52] for 5- and 15-year latency, respectively) and longer times to severe disability. The same association between time to onset of SP and late outcomes was observed even in patients matched by number of early attacks. However, duration of the relapsing-remitting phase did not influence the times from SP onset to DSS levels. CONCLUSIONS: Our results indicate dissociation between early inflammatory attacks and onset of the SP phase and further question the validity of relapse frequency as a surrogate marker for late disability. Among the group with frequent early relapses, we observed a large variability of outcomes, ranging from one extreme to the opposite.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | low |
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".