Hypertonic saline improves the LCI in paediatric patients with CF with normal lung function
Bibliographic record
Abstract
BACKGROUND AND AIMS Sensitive outcome measures to assess the efficacy of therapeutic interventions in patients with cystic fibrosis (CF) with mild lung disease are currently lacking. Our objective was to study the ability of the lung clearance index (LCI), a measure of ventilation inhomogeneity, to detect a treatment response to hypertonic saline inhalation in paediatric patients with CF with normal spirometry. METHODS In a crossover trial, 20 patients with CF received 4 weeks of hypertonic saline (HS) and isotonic saline (IS) in a randomised sequence separated by a 4 week washout period. The primary end point was the change in the LCI due to HS versus IS. RESULTS Baseline characteristics including the LCI were not significantly different between both study periods. Four weeks of twice-daily HS inhalation significantly improved the LCI compared with IS (1.16, 95% CI 0.26 to 2.05; p=0.016), whereas other outcome measures such as spirometry and quality of life failed to reach statistical significance. Randomisation order had no significant impact on the treatment effect. CONCLUSIONS The LCI, but not spirometry was able to detect a treatment effect from HS inhalation in patients with CF with mild disease and may be a suitable tool to assess early intervention strategies in this patient population. Clinical trial number NCT00635141.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".