MRI brain volume loss, lesion burden, and clinical outcome in secondary progressive multiple sclerosis
Bibliographic record
Abstract
BACKGROUND: Magnetic resonance imaging (MRI) of brain volume measures are widely used outcomes in secondary progressive multiple sclerosis (SPMS), but it is unclear whether they are associated with physical and cognitive disability. OBJECTIVE: To investigate the association between MRI outcomes and physical and cognitive disability worsening in people with SPMS. METHODS: = 889). We investigated the association of change in whole brain and gray matter volume, contrast enhancing lesions, and T2 lesions with significant worsening on the Expanded Disability Status Scale (EDSS), Timed 25-Foot Walk (T25FW), Nine-Hole Peg Test (NHPT), and Symbol Digit Modalities Test (SDMT) with logistic regression models. RESULTS: We found no association between MRI measures and EDSS or SDMT worsening. T25FW worsening at 48 and 96 weeks, and NHPT worsening at 96 weeks were associated with cumulative new or newly enlarging T2 lesions at 96 weeks. NHPT worsening at 48 and 96 weeks was associated with normalized brain volume loss at 48 weeks, but not with other MRI outcomes. CONCLUSION: The association of standard MRI outcomes and disability was noticeably weak and inconsistent over 2 years of follow-up. These MRI outcomes may not be useful surrogates of disability measures in SPMS.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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".