Question · asked by 1 review
Autogenic drainage vs Flutter®: QoL
- Population
- adults and children with CF
- Intervention
- Autogenic drainage
- Comparison
- Flutter®
- Outcome
- QoL
What each review found
Current versions only| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Autogenic drainage vs Flutter® QoL (SF‐36 and CRQ) · adults and children with CF Autogenic drainage for airway clearance in cystic fibrosis (2021) · Cochrane Headline outcomes only | no estimate extracted | 1 study · 30 participants | Low |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Autogenic drainage for airway clearance in cystic fibrosis 2021 · Cochrane Headline outcomes only | Not reported | Not extracted | Not assessed |
Related questions
The same intervention and outcome, asked in another population or against another comparator.
- Autogenic drainage vs conventional physiotherapy · adults and children with CF · 1 review
- Autogenic drainage vs spontaneous cough · adults and children with CF · 1 review
- Autogenic drainage vs active cycle of breathing technique · adults and children with CF · 1 review
- Autogenic drainage vs intrapulmonary percussive ventilation (200 bpm) · adults with CF · 1 review
- Autogenic drainage vs PEP · adults and children with CF · 1 review
- Autogenic drainage vs high frequency chest wall oscillation · adults with CF · 1 review
- Autogenic drainage vs Cornet® · adults with CF · 1 review
- Autogenic drainage vs intrapulmonary percussive ventilation (400 bpm) · adults with CF · 1 review
- Autogenic drainage vs Flutter® · adults and children with cystic fibrosis · 0 reviews
- Autogenic drainage vs Cornet® · adults with cystic fibrosis · 0 reviews
- Autogenic drainage vs PEP · adults and children with cystic fibrosis · 0 reviews
- Autogenic drainage vs high frequency chest wall oscillation · adults with cystic fibrosis · 0 reviews
How reviews are matched to this question
Reviews word the same question differently. Four decision models (TypeSafe's Jev, Liquid AI's d1-ultra, SubQ Snap and Baseten's Elephant) judged each wording of the population, intervention, comparator and outcome against the others; two wordings count as the same when at least three of them agree and none clearly disagrees, and findings count as this question only when all four elements match. Timing, setting and subgroup never split a question: they are shown on each finding.