Effects of Autogenic Drainage on Sputum Recovery and Pulmonary Function in People with Cystic Fibrosis: A Systematic Review
Bibliographic record
Abstract
PURPOSE: To determine the effects of short- and long-term use of autogenic drainage (AD) on pulmonary function and sputum recovery in people with cystic fibrosis (CF). METHODS: The authors conducted a systematic review of randomized and quasi-randomized clinical trials in which participants were people with CF who use AD as their sole airway clearance technique. RESULTS: Searches in 4 databases and secondary sources using 5 key terms yielded 735 articles, of which 58 contained the terms autogenic drainage and cystic fibrosis. Ultimately, 4 studies, 2 of which were long term, were included. All measured forced expiratory volume in 1 second (FEV1) and found no change. The long-term studies were underpowered to detect change in FEV1; however, the short-term studies found a clinically significant sputum yield (≥4 g). CONCLUSION: AD has been shown to produce clinically significant sputum yields in a limited number of investigations. The effect of AD on the function of the pulmonary system remains uncertain, and questions have emerged regarding the appropriateness of FEV1 as a valid measure of airway clearance from peripheral lung regions. Further consideration should be given to the use of FEV1 as a primary measure of the effect of AD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".