Body mass index as a predictor of MS activity and progression among participants in BENEFIT
Bibliographic record
Abstract
Background: There is a lack of studies on the association between obesity and conversion from a clinically isolated syndrome (CIS) to multiple sclerosis (MS). Objective: The aim of this study was to determine whether obesity predicts disease activity and prognosis in patients with CIS. Methods: Body mass index (BMI) at baseline was available for 464 patients with CIS in BENEFIT. Obesity was defined as BMI ⩾ 30 kg/m 2 and normal weight as 18.5 ⩽ BMI < 25. Patients were followed up for 5 years clinically and by magnetic resonance imaging. Hazard of conversion to clinically definite (CDMS) or to 2001 McDonald criteria (MDMS) MS, annual rate of relapse, sustained progression on Expanded Disability Status Scale (EDSS), change in brain and lesion volume, and development of new brain lesions were evaluated. Results: Obese individuals were 39% more likely to convert to MDMS (95% CI: 1.02–1.91, p = 0.04) and had a 59% (95% CI: 1.01–2.31, p = 0.03) higher rate of relapse than individuals with normal weight. No associations were observed between obesity and conversion to CDMS, sustained progression on EDSS or magnetic resonance imaging (MRI) outcomes, except for a larger reduction of brain volume in obese smokers as compared to normal weight smokers (−0.82%; 95% CI: −1.51 to −0.12, p = 0.02). Conclusion: Obesity was associated with faster conversion to MS (MDMS) and a higher relapse rate.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".