Whole-Body Vibration Training During a Low Frequency Outpatient Exercise Training Program in Chronic Obstructive Pulmonary Disease Patients: A Randomized, Controlled Trial
Bibliographic record
Abstract
BACKGROUND: The aim of the study was to investigate whether whole-body vibration training (WBVT) can be applied beneficially within an outpatient low frequency exercise program. METHODS: In a prospective, controlled, randomized study, WBVT effectiveness and safety were investigated in COPD stage II-IV patients undergoing a 3-month training program. Participants took part in a 90-min circuit training once a week. On top patients were randomized to either perform squats with WBVT, or without (conventional training group (CTG)). Before and after the intervention, a sit-to-stand test (STST), a 6-min walk test (6-MWT), the COPD assessment test (CAT), and the chronic respiratory disease questionnaire (CRQ) were evaluated. RESULTS: Twenty-eight out of 55 patients completed the study (n = 12 WBTV, n = 16 CTG). The STST time remained nearly constant for the CTG (Δ -0.8 ± 3.1 s) and the WBVT (Δ 1.4 ± 3.2 s; P = 0.227), respectively. Similarly, for both WBVT and CTG, the 6-min walk distance remained unchanged (Δ 7 ± 55 m vs. 9 ± 45 m, P = 0.961). In three out of four categories, the CRQ scores showed a significant improvement within WBVT, and in one category when comparing across groups. The CAT score dropped by -0.8 ± 2.9 points within CTG and by 2.4 ± 2.7 points within WBVT (P = 0.105). There were no adverse events related to WBVT. CONCLUSION: The implementation of WBVT in the context of an outpatient low frequency exercise program did not significantly improve the patients' exercise capacity. An improvement in CAT and partially in CRQ was shown within WBVT. However, regarding the high dropout rate (49%), these results must be interpreted with caution.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".