Ventilatory support or respiratory muscle training as adjuncts to exercise in obese CPAP-treated patients with obstructive sleep apnoea: a randomised controlled trial
Bibliographic record
Abstract
Background Obstructive sleep apnoea (OSA) and obesity are interdependent chronic diseases sharing reduced exercise tolerance and high cardiovascular risk. Intervention A 3-month intervention with innovative training modalities would further improve functional capacity and cardiovascular health than usual cycle exercise training in already continuous positive airway pressure (CPAP)-treated obese patients with OSA. Methods Fifty three patients (35 2) were randomly allocated to exercise training on a cycle ergometer, either alone (ERGO) or with respiratory muscle training (ERGO+RMT) or non-invasive ventilation (ERGO+NIV). Changes in 6 min walking distance (primary outcome), aerobic capacity (VO2peak), cardiovascular parameters, body composition and sleep quality were evaluated. Measurements and main results All training modalities increased 6 min walking distance without differences between groups (P=0.97). ERGO+NIV and ERGO+RMT led to significantly higher improvement in VO2peak compared with ERGO (3.1 (95% CI 1.6 to 4.6) vs 2.3 (0.8 to 3.7) vs 0.5(−1.0 to 1.9) mL/min/kg, respectively, P=0.04) and ERGO+NIV significantly reduced self-measured blood pressure compared with ERGO+RMT and ERGO (systolic: −9.5 (95% CI −14.1 to −4.9) vs −13 (−5.8 to 3.1) vs −0.7 (−5.1 to 3.8) mm Hg, respectively, P=0.01). Waist and neck circumferences were reduced after ERGO+NIV compared with ERGO+RMT and ERGO (P=0.01). Conclusions Combining RMT or NIV with cycling exercise training failed to provide further improvement in functional capacity as compared with cycling exercise training alone. However, the combination of NIV and exercise training demonstrated superiority for improving cardiometabolic risk factors in obese CPAP-treated patients with OAS. TRIAL REGISTRATION NUMBER Results, NCT01155271 .
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".