Airway Clearance Techniques in Primary Ciliary Dyskinesia: A Systematic Review.
Bibliographic record
Abstract
OBJECTIVE: Primary ciliary dyskinesia (PCD) is a respiratory disorder that impairs mucociliary clearance, leading to decreased lung function. Conventional chest physiotherapy (CCP) is the traditional airway clearance technique (ACT) and is considered a standard treatment for PCD patients. This systematic review investigated whether device supported ACTs are better alternatives for improving lung function and/or quality of life in PCD, compared with CCP. METHODS: The OVID Medline, PubMed, CINAHL, and Cochrane databases were searched. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed, and the Grading of Recommendations, Assessment, Development, and Evaluation approach was used to aggregate the data. This systematic review has been registered on the International Prospective Register of Systematic Reviews website. RESULTS: Of the 389 citations that resulted from our literature search, 2 randomized crossover trials that included a total of 54 patients were analyzed. The certainty of the aggregated study evidence was very low. No difference was identified between device-supported ACTs and CCP in terms of forced vital capacity and forced expiratory volume in 1 second in PCD patients aged 6 to 20 years. CONCLUSION: Device-supported ACTs could be considered alternative treatment options to replace CCP. High quality research is required to confirm this result.
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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| 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) | 0.006 | 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".