Longitudinal patterns of cortical thinning in multiple sclerosis
Bibliographic record
Abstract
In multiple sclerosis (MS), cortical atrophy is correlated with clinical and neuropsychological measures. We aimed to examine the differences in the temporospatial evolution of cortical thickness (CTh) between MS-subtypes and to study the association of CTh with T2-weighted white matter lesions (T2LV) and clinical progression. Two hundred and forty-three MS patients (180 relapsing-remitting [RRMS], 51 secondary-progressive [SPMS], and 12 primary-progressive [PPMS]) underwent annual clinical (incl. expanded disability status scale [EDSS]) and MRI-examinations over 6 years. T2LV and CTh were measured. CTh did not differ between MS-subgroups. Higher total T2LV was associated with extended bilateral CTh-reduction on average, but did not correlate with CTh-changes over time. In RRMS, CTh- and EDSS-changes over time were negatively correlated in large bilateral prefrontal, frontal, parietal, temporal, and occipital areas. In SPMS, CTh was not associated with the EDSS. In PPMS, CTh- and EDSS-changes over time were correlated in small clusters predominantly in left parietal areas. Increase of brain lesion load does not lead to an immediate CTh-reduction. Although CTh did not differ between MS-subtypes, a dissociation in the correlation between CTh- and EDSS-changes over time between RRMS and progressive-MS was shown, possibly underlining the contribution of subcortical pathology to clinical progression in progressive-MS.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".