Effect of pulmonary exacerbations on long-term lung function decline in cystic fibrosis
Bibliographic record
Abstract
It is unknown what proportion of long-term lung function decline in cystic fibrosis (CF) is explained by pulmonary exacerbations. The aim of this study was to determine how exacerbations requiring hospitalisation contribute to the course of CF lung disease. This was a retrospective cohort study. The primary outcome was the rate of decline of forced expiratory volume in 1 s (FEV(1)) % predicted. Out of 851 subjects, 415 (48.8%) subjects had ≥ 1 exacerbation. After adjustment for confounders, the annual rate of FEV(1) decline in those without an exacerbation was 1.2% per yr (95% CI 1.0-1.5), compared with 2.5% per yr (95% CI 2.1-2.8) in those with an exacerbation. The proportion of overall FEV(1) decline associated with ≥ 1 exacerbation was 52% (95% CI 35.0-68.9). For a given number of exacerbations, the annual rate of FEV(1) decline was greatest in subjects with ≤ 6 months between exacerbations. Half of FEV(1) decline seen in CF patients was associated with pulmonary exacerbations. Time between exacerbations, specifically ≤ 6 months between exacerbations, plays an important contribution to overall lung function decline. These findings support using time to next exacerbation as a clinical end-point for CF trials.
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".