Ultrasound diaphragm activity in patients with cystic fibrosis: relationship to disease severity and peripheral muscle strength
Bibliographic record
Abstract
Rationale: Cystic fibrosis (CF) is associated with changes in respiratory and peripheral skeletal muscles, but their relationship is not fully understood. Ultrasonography (US) can provide an evaluation of diaphragm activity, but data in CF patients is lacking. This study aimed to compare US-derived diaphragm function to usual markers of disease severity and to peripheral muscle strength in this population. Methods: Stable CF patients were prospectively recruited. US Diaphragm activity was evaluated using TF%max, defined as [thickening fraction during tidal breathing / thickening fraction during maximal inspiration]. Exacerbation rate, dyspnea level (mMRC scale), lung function testing, C-reactive protein (CRP), transthyretin (TT), handgrip strength (HS) and body composition were measured and compared to TF%max. Results: 22 patients were included (16 males, mean FEV1 56±29%. Mean TF%max was 28±20%, was inversely related to FEV1 (rho=0.73, p<0.01) and was significantly related to dyspnea level (b=0.60; p=0.003), 1-year exacerbation rate (b=0.45, p=0.03) and was significantly lower in patients with mMRC<2 compared to those with higher score (22±18 vs 40±17%, p=0.03). TF%max was correlated to CRP level (b=0.57, p<0.01) but not to TT, fat-free mass or HS (all p=NS). Conclusion: In patients with CF, TF%max is related to clinical severity and could provide a novel tool to assess disease burden. No association was found with markers of peripheral muscle status and strength, suggesting that the respiratory and peripheral involvement in CF probably have different determinants. Additional studies are required to further explore this relationship.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".