Perceived quality of life, fatigue and the metabolic cost of walking in generalized hypermobility spectrum disorder and hypermobile Ehlers-Danlos syndrome
Bibliographic record
Abstract
Introduction Individuals with hypermobile Ehlers-Danlos Syndrome (hEDS) and Hypermobility Spectrum Disorders (HSD) often experience chronic pain, leg fatigue and/or pain, which may contribute to a higher metabolic cost of walking. How these subjective measures may manifest in an elevated metabolic cost of transport and perceived pain at varying walking speeds remains to be evaluated. Methods We recruited 11 HSD/hEDS participants (33 ± 14 yrs, 170 ± 6. cm, weight 71 ± 11 kg) and 11 age- and sex-matched controls. Self-reported subjective outcome measures of health-related quality of life, fatigue severity, and foot function were evaluated prior to treadmill walking using the 36-Item Short Form Health Survey (SF-36) and the Fatigue Severity Scale (FSS). Participants also rated their self-perceived leg pain/fatigue following 3 x 6 min of treadmill walking at 80%, 100% and 120% of preferred walking speed (PWS). Cost of transport (CoT) was calculated from indirect calorimetry. Results CoT was significantly higher in HSD/hEDS compared to CON at all speeds ( p = 0.034). CoT was significantly higher at 80% PWS compared to both 100% and 120% PWS in HSD/hEDS. HSD/hEDS reported significantly poorer health outcomes across all SF-36 domains ( p < 0.05), significantly poorer foot function ( p < 0.001) and significantly higher fatigue severity ( p < 0.001) prior to walking. Despite similar PWS (1.1 ± 0.3 m⸱s -1 ), Leg pain/fatigue immediately following walking was significantly higher in HSD/hEDS compared to CON (group main effect p < 0.001) and increased with speed in HSD/hEDS (p = 0.011). The physical function domain was significantly related post-walking leg pain/fatigue, and perceived energy prior to walking (all r > 0.69, p < 0.001). Discussion These results have important implications for exercise prescription in individuals with HSD/hEDS whose CoT is higher during walking, which may exacerbate already elevated symptoms of pain and fatigue.
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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 | 0.001 |
| 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 | 0.000 |
| 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".