Effect of exercise modalities on walking capacity in patients with intermittent claudication: A Network Meta-Analysis
Bibliographic record
Abstract
Despite extensive research on the effect of supervised exercise therapy (SET) on walking performance in patients with symptomatic peripheral arterial disease (PAD), it remains unclear which training modality provides the greatest improvement in walking capacity. Thus, a random-effect network meta-analysis was performed to compare the effect of different types of SET on walking capacity in individuals with symptomatic PAD. The following databases were searched from January 1966 to April 2021: SPORTDiscus, CINAHL, MEDLINE, AMED, Academic Search Complete, and Scopus. Trials must include at least one type of supervised exercise therapy for patients with symptomatic PAD, with a minimum of 5 exercise sessions, and an objective measure of walking capacity. Eighteen studies were included for a total sample of 1135 participants. Intervention duration ranged from 6 to 24 weeks and included aerobic exercise (treadmill walking, cycling, Nordic walking), resistance training (lower and/or upper body), a combination of both, and underwater exercises. Results showed that combined training improved walking capacity to a comparable extent to aerobic walking (+122.0 [24.2-219.8] m vs. +106.8 [34.2-179.4] m), but with a larger effect size (1.20 [0.50-1.90] vs 0.67 [0.22-1.11]). Similar results were observed for the distance performed during the 6-minute walking test, with combined training being the most promising modality (+57.3 [16.2; 98.5] m), followed by underwater training (+56.5 [22.4-90.5] m) and aerobic walking (+39.0 [12.8-65.1] m). While combined exercise seems to be the most promising training modality, aerobic walking, and underwater training also improved walking capacity for patients with symptomatic PAD.
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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 | 0.012 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.037 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".