Prognostic indicators in pediatric clinically isolated syndrome
Bibliographic record
Abstract
OBJECTIVE: To assess prognostic factors for a second clinical attack and a first disability-worsening event in pediatric clinically isolated syndrome (pCIS) suggestive of multiple sclerosis (MS) patients. METHODS: A cohort of 770 pCIS patients was followed up for at least 10 years. Cox proportional hazard models and Recursive Partitioning and Amalgamation (RECPAM) tree-regression were used to analyze data. RESULTS: In pCIS, female sex and a multifocal onset were risk factors for a second clinical attack (hazard ratio [HR], 95% confidence interval [CI] = 1.28, 1.06-1.55; 1.42, 1.10-1.84, respectively), whereas disease-modifying drug (DMD) exposure reduced this risk (HR, 95% CI = 0.75, 0.60-0.95). After pediatric onset MS (POMS) diagnosis, age at onset younger than 15 years and DMD exposure decreased the risk of a first Expanded Disability Status Scale (EDSS)-worsening event (HR, 95% CI = 0.59, 0.42-0.83; 0.75, 0.71-0.80, respectively), whereas the occurrence of relapse increased this risk (HR, 95% CI = 5.08, 3.46-7.46). An exploratory RECPAM analysis highlighted a significantly higher incidence of a first EDSS-worsening event in patients with multifocal or isolated spinal cord or optic neuritis involvement at onset in comparison to those with an isolated supratentorial or brainstem syndrome. A Cox regression model including RECPAM classes confirmed DMD exposure as the most protective factor against EDSS-worsening events and relapses as the most important risk factor for attaining EDSS worsening. INTERPRETATION: This work represents a step forward in identifying predictors of unfavorable course in pCIS and POMS and supports a protective effect of early DMD treatment in preventing MS development and disability accumulation in this population. Ann Neurol 2017;81:729-739.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".