Oscillating positive expiratory pressure (oPEP) therapy in chronic obstructive pulmonary disease and bronchiectasis
Bibliographic record
Abstract
RATIONALE: Airway clearance methods such as oscillating positive expiratory pressure (oPEP) are proposed to provide benefit in patients with chronic obstructive pulmonary disease (COPD) and bronchiectasis by mobilizing secretions and enhancing mucous movement. METHODS: A six-week cross-over study was completed in 29 subjects (n=15 COPD, n=14 bronchiectasis) who provided written informed consent and were randomized to oPEP therapy (Aerobika®, Trudell Medical International) four-times daily. Pulmonary function tests, the Six Minute Walk distance (6MWD), St George's Respiratory Questionnaire (SGRQ) and the Patient Evaluation Questionnaire (PEQ) were used to evaluate therapy effects. RESULTS: There were no adverse events related to oPEP use. There were statistically significant improvements in 6MWD (p=0.01), SGRQ total score (p=0.01), and the PEQ Cough Frequency (p=0.006), dyspnea (p=0.03) and ease in bringing up sputum (p<0.0001). CONCLUSIONS: In subjects with COPD and bronchiectasis, three weeks of oPEP therapy (Aerobika®) was well-tolerated and there was improved dyspnea, quality of life, exercise capacity and ease in bringing up sputum. Table 1. Efficacy Results Parameter (+/-SD) Pre-oPEP (n=29) Post-oPEP (n=29) Sig Diff* FEV1% 64 (23) 64 (23) 0.40 FVC% 79 (22) 82 (21) 0.06 FEV1/FVC 61 (16) 60 (16) 0.06 6MWD m 409 (83) 424 (82) 0.01 SGRQ Total Score 44 (14) 39 (14) 0.01 PEQ Cough frequency 3.2 (1.1) 2.6 (0.9) 0.006 PEQ Dyspnea 2.4 (0.8) 2.0 (0.8) 0.03 PEQ Ease bringing up sputum 4.0 (0.4) 2.8 (1.1) <0.0001 PEQ Global 4.0 (0.3) 2.8 (1.2) <0.0001 SD=Standard Deviation *Significance of difference between pre and post oPEP measurement using paired two tailed t-test (p<0.05)
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".