Disability outcomes of early cerebellar and brainstem symptoms in multiple sclerosis
Bibliographic record
Abstract
Background: Cerebellar and brainstem symptoms are common in early stages of multiple sclerosis (MS) yet their prognostic values remain unclear. Objective: The aim of this study was to investigate long-term disability outcomes in patients with early cerebellar and brainstem symptoms. Methods: This study used data from MSBase registry. Patients with early cerebellar/brainstem presentations were identified as those with cerebellar/brainstem relapse(s) or functional system score ⩾ 2 in the initial 2 years. Early pyramidal presentation was chosen as a comparator. Andersen-Gill models were used to compare cumulative hazards of (1) disability progression events and (2) relapses between patients with and without early cerebellar/brainstem symptoms. Mixed effect models were used to estimate the associations between early cerebellar/brainstem presentations and expanded disability status scale (EDSS) scores. Results: The study cohort consisted of 10,513 eligible patients, including 2723 and 3915 patients with early cerebellar and brainstem symptoms, respectively. Early cerebellar presentation was associated with greater hazard of progression events (HR = 1.37, p < 0.001) and EDSS (β = 0.16, p < 0.001). Patients with early brainstem symptoms had lower hazard of progression events (HR = 0.89, p = 0.01) and EDSS (β = −0.06, p < 0.001). Neither presentation was associated with changes in relapse risk. Conclusion: Early cerebellar presentation is associated with unfavourable outcomes, while early brainstem presentation is associated with favourable prognosis. These presentations may be used as MS prognostic markers and guide therapeutic approach.
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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 | 0.004 |
| 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 | 0.000 | 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".