Early Clinical and MRI Predictors of Time to Second Attack and Disability in Children with Acute Demyelinating Syndromes: Findings from a Prospective National Cohort Study (S54.007)
Bibliographic record
Abstract
BACKGROUND: Early predictors of outcome in children with multiple sclerosis (MS) have implications for clinical care and for identifying eligible children for clinical trials. OBJECTIVE: To determine clinical and MRI predictors of disability and time to second attack at onset in children with MS. METHOD: Children younger than 16 years of age with an acute demyelinating syndrome (ADS) were enrolled at 23 sites into a national prospective study. Standardized clinical and MRI data were acquired at onset, 3, 6, and 12 months and annually after onset for 9 years. Children were diagnosed with MS according to McDonald criteria. Age at ADS onset, gender, date of second attack, Expanded Disability Status Scale (EDSS) score at most recent visit, and relapse count were extracted from the database. Baseline and serial MRI scans were evaluated using a standardized scoring tool. Clinical and MRI parameters that predict time to second attack and EDSS score were evaluated using Cox proportional hazards and linear regression models. RESULTS: Of 302 eligible children, 74 (26%) have been diagnosed with MS (mean observation: 3.9±2.2 years, range: 0.04-8.1 years; 26 (65%) female). Mean annualized relapse rate was 0.9±1.0 (mean total relapses: 2.0± 1.0). The presence of 蠅1 persisting T1-hypointense lesion and 蠅1 periventricular lesion at onset predicted time to second attack (HR 2.8, 95% confidence interval 1.1-7.1). EDSS score at most recent visit was not associated with relapse count in the first 1 or 2 years after onset, but was correlated with total relapses (r=0.34, p=0.001), and to an even greater degree for those children followed 蠅4 years (r=0.44, p=0.001). EDSS was associated with new T2 lesion count over the first year following ADS (r=0.38, p=0.04). CONCLUSION: Specific MRI parameters present at onset are associated with time to second attack and disability in children with MS. Study Supported by: Canadian Multiple Sclerosis Scientific Research Foundation
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".