Correlates of Processing Speed Change With Combined Cognitive Rehabilitation and Exercise in Progressive MS: Secondary Analysis of the CogEx Trial
Bibliographic record
Abstract
BackgroundCognitive rehabilitation and exercise training are promising approaches for improving cognition in persons with progressive multiple sclerosis (MS). Identifying heterogeneity of change and factors that influence the effects of cognitive rehabilitation and/or exercise training on cognitive outcomes at the individual level have direct relevance for developing tailored and optimized rehabilitation interventions for improving cognition in progressive MS.ObjectiveThis study involved a secondary data analysis from the CogEx trial in progressive MS. This study first described heterogeneity of change in cognitive processing speed (CPS) across the intervention conditions and then identified possible adherence/compliance, baseline performance, and demographic/clinical variables as correlates of rehabilitation-related CPS changes.MethodsA total of 311 persons with progressive MS who were pre-screened for impaired CPS completed 12 weeks of combined cognitive rehabilitation (or sham) and exercise training (or sham). CPS was measured before and after the 12-week period. As potential correlates of CPS changes, we measured adherence/compliance (ie, treatment exposure), performance outcomes at baseline, as well as demographic and clinical characteristics at baseline.ResultsThere was heterogeneity of change in CPS across the 4 intervention conditions. We further identified baseline learning and memory impairment and premorbid intelligence quotient (IQ), but not adherence/compliance, other baseline performance outcomes, or demographic/clinical characteristics as significant correlates of CPS changes across the 4 intervention conditions.ConclusionsThe overall pattern of results suggests that future trials in this area might account for impaired learning and memory and/or premorbid IQ as potential covariates, or more carefully consider the role of reserve within rehabilitation interventions in progressive MS.
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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 | 0.011 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".