Heterogeneity of aerobic fitness changes with exercise training in progressive multiple sclerosis: Secondary, exploratory analysis of data from the CogEx trial
Bibliographic record
Abstract
BACKGROUND: There is heterogeneity of aerobic fitness (VO2peak) changes with a standardized exercise training stimulus in the general population (i.e. some participants demonstrate improvements, others no change, and some a reduction in VO2peak). OBJECTIVES: This secondary, exploratory analysis of data examined the heterogeneity of VO2peak responses and possible correlates among persons with progressive multiple sclerosis (PMS) from the CogEx trial. METHODS: CogEx was a multi-site, multi-arm, randomized, double-blinded, and sham-controlled trial undertaken by 11 sites in six different countries. Participants were randomized into one of four conditions with different combinations of exercise training and cognitive rehabilitation including respective sham conditions. The analysis focuses primarily on VO2peak change for the pooled exercise training intervention conditions compared with the pooled sham exercise control conditions. RESULTS: Waterfall plots for change in VO2peak suggested greater heterogeneity with exercise training than sham, and the proportions of difference in VO2peak change (i.e. improvement/worsening) were significantly different between exercise training and sham conditions(p < 0.05). The multivariable analysis indicated that lower baseline VO2peak (p < 0.001) was the only statistically significant correlate of increases in VO2peak with exercise training. CONCLUSION: Our results highlight the heterogeneity of change in VO2peak with exercise training that is correlated with initial aerobic capacity in PMS, and such results may inform hypothesis testing in future clinical trials of exercise training.
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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 | 0.066 | 0.103 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.012 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".