Symptomatic correlates of six-minute walk performance in persons with multiple sclerosis.
Bibliographic record
Abstract
BACKGROUND: The six-minute walk (6MW) test has been identified as a valid, reliable, and reproducible measure of endurance walking performance that differentiates persons with multiple sclerosis (MS) and controls and correlates with disability and walking impairment. AIM: This study examined symptoms of fatigue, pain, and depression as correlates of 6MW performance and the possibility that such symptoms would account for the difference in 6MW distance between persons with MS and controls. DESIGN: Observational. SETTING: Research laboratory. POPULATION: Sixty-six persons, 33 with MS and 33 controls matched on age, sex, height, and weight. METHODS. Participants completed the fatigue severity scale (FSS), short-form of the McGill pain questionnaire (SF-MPQ), and depression items of the hospital anxiety and depression scale (HADS-D) and then performed the six-minute walk (6MW) in a rectangular corridor. RESULTS: There were statistically significant differences between groups in 6MW distance (p = 0.0001) and FSS (P=0.0001) and SF-MPQ (P=0.025), but not HADS-D (P>0.05), scores. 6MW distance was significantly correlated with FSS (P=-0.66), SF-MPQ (P=-0.38), and HADS-D (P=-0.33) scores in the overall sample, but 6MW distance was significantly correlated with only FSS scores in the separate samples of those with MS (P=-0.46) and controls (P=-0.46). Only group (β=0.32) and FSS scores (β=-0.53) explained variance in overall 6MW distance in a hierarchical, linear regression analysis. CONCLUSION: This study provides new insight into the symptomatic correlates of 6MW performance and identifies fatigue as a possible target of interventions designed to improve walking endurance in MS. CLINICAL REHABILITATION IMPACT: Clinicians and practitioners might consider targeting fatigue as a method of managing compromised endurance walking in persons with 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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".