Effects of inspiratory muscle training in cystic fibrosis: a systematic review
Bibliographic record
Abstract
OBJECTIVE: We performed a systematic review to determine the effect of inspiratory muscle training (IMT) on inspiratory muscle strength and endurance, exercise capacity, dyspnoea and quality of life for adolescents and adults living with cystic fibrosis. DATA SOURCES: MEDLINE, EMBASE and CINAHL electronic databases were searched up to January 2008. REVIEW METHODS: We performed a systematic review using the methodology outlined in the Cochrane Collaboration protocol. Articles were included if: (1) participants were adolescents or adults with cystic fibrosis (> 13 years of age); (2) an IMT group was compared to a sham IMT, no intervention or other intervention group; (3) the study used a randomized controlled trial or cross-over design; and (4) it was published in English. Data were abstracted and methodological quality was assessed independently by two reviewers. RESULTS: The search strategy yielded 36 articles, of which two met the inclusion criteria. Both studies used a targeted or threshold device for IMT. Meta-analyses were limited to forced expiratory volume in 1 second (FEV1) and forced vital capacity (FVC), which showed no difference in effect between the IMT group and the sham and/or control group. Individual study results were inconclusive for improvement in inspiratory muscle strength. One study demonstrated improvement in inspiratory muscle endurance. CONCLUSION: The benefit of IMT in adolescents and adults with cystic fibrosis for outcomes of inspiratory muscle function is supported by weak evidence. Its impact on exercise capacity, dyspnoea and quality of life is not clear. Future research should investigate the characteristics of the subgroup of people with cystic fibrosis that might benefit most from IMT.
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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 | 0.009 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.009 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 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".