A randomised clinical trial of nebulised tobramycin or colistin in cystic fibrosis
Bibliographic record
Abstract
Chronic infection with Pseudomonas aeruginosa is associated with progressive deterioration in lung function in cystic fibrosis (CF) patients. The purpose of this trial was to assess the efficacy and safety of tobramycin nebuliser solution (TNS) and nebulised colistin in CF patients chronically infected with P. aeruginosa. One-hundred and fifteen patients, aged > or = 6 yrs, were randomised to receive either TNS or colistin, twice daily for 4 weeks. The primary end point was an evaluation of the relative change in lung function from baseline, as measured by forced expiratory volume in one second % predicted. Secondary end points included changes in sputum P. aeruginosa density, tobramycin/colistin minimum inhibitory concentrations and safety assessments. TNS produced a mean 6.7% improvement in lung function (p=0.006), whilst there was no significant improvement in the colistin-treated patients (mean change 0.37%). Both nebulised antibiotic regimens produced a significant decrease in the sputum P. aeruginosa density, and there was no development of highly resistant strains over the course of the study. The safety profile for both nebulised antibiotics was good. Tobramycin nebuliser solution significantly improved lung function of patients with cystic fibrosis chronically infected with Pseudomonas aeruginosa, but colistin did not, in this study of 1-month's duration. Both treatments reduced the bacterial load.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".