Effects of 8 months of exercise therapy in warm water for fibromyalgia on physical function, fitness and disease impact in affected women
Bibliographic record
Abstract
Introduction: The fibromyalgia syndrome is a chronic disorder characterised by generalised pain, muscle stiffness, reduced physical condition and fatigue that limit their daily life activities. Little knowledge is available on the feasibility and effects of long-lasting physical training in warm water on major physical abilities related with everyday life in patients with FM. The aim of the present study was to evaluate the feasibility and effects of 8 months of supervised exercise therapy in warm water on physical function, fitness and disease impact in women with fibromyalgia. Methods: Thirty women with fibromyalgia [mean ± SD] age 50.8 ± 8.7 (years); body mass index 27.7 ± 4.1 (kg/m2); duration of symptoms 19.8 ± 7.4 (years); number of tender points 17.0 ± 1.0; number of specific drugs 1.4 ± 0.8 (antidepressives, muscular relaxants and analgesics); were randomly assigned into 2 groups: an experimental group, performing 3 weekly sessions for 60 minutes of exercise therapy in warm water (n=15); and a control group, continuing their usual care and habitual leisure-time activities (n=15). Physical function and fitness were evaluated using the following tests: 10-m maximal walking speed, 10-step stair-climbing, blind one-leg stance, hand-grip dynamometry and Canadian Aerobic Fitness. The disease impact was evaluated using the Fibromyalgia Impact Questionnaire (FIQ). The data was examined by applying statistical tests for the analyses of variances. Results: Patients in both groups were in a similar condition at baseline. After 8 months of exercise therapy, the experimental group showed improvements in several aspects of physical function and fitness, such as balance (30%; p=0.031), maximal walking speed (6%; p=0.006), stair-climbing capacity with no extra weight (14%; p=0.003) and 10 kg-weighted (25%; p = 0.002) and maximal oxygen uptake (8%; p=0.015). These patients also showed ameliorations of the disease impact in terms of pain (9%; p = 0.040), stiffness (53%; p=0.015), anxiety (41%; p=0.037), depression (28%; p=0.030) and self-perceived physical function (20%; p=0.047), with an overall reduction in the total FIQ score (18%; p=0.017). Conclusion: 8 months of aquatic exercise therapy for fibromyalgia was feasible and led to relevant improvements in physical function and fitness, reducing the disease impact in FM women.
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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 | 0.000 | 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) | 0.002 | 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".