A Pilot Study to Compare Tobramycin 80 mg Injectable Preparation wth 300 mg Solution for Inhalation in Cystic Fibrosis Patients
Bibliographic record
Abstract
BACKGROUND: Inhaled tobramycin has been shown to improve lung function in cystic fibrosis (CF) patients chronically infected with Pseudomonas aeruginosa. However, to date no comparative data are available for different dose regimens used in clinical practice. OBJECTIVES: To compare the clinical efficacy of the two most commonly used treatment regimens of inhaled tobramycin in patients with CF. METHODS: In an open crossover study of CF patients, subjects were randomly allocated to receive either 80 mg tobramycin twice-daily continuous treatment or 300 mg tobramycin twice daily in cycles of 28 days on and 28 days off treatment. After three months, patients were switched to the alternative treatment regimen. RESULTS: A total of 32 patients with a mean (+/- SD) age of 18.5+/-8.6 years were included in the study. Compared with the treatment period using colistin, forced expiratory volume in 1 s decreased by -2.1+/-13.8% in the 80 mg tobramycin group and increased by +2.3+/-13.0% in the 300 mg group. Similar changes were observed in forced vital capacity (-2.5+/-12.9% in the 80 mg tobramycin group versus +2.5+/-9.6% in the 300 mg tobramycin group). Variability in responses was large but the differences were not statistically significant. Personal preference indicated that the majority of patients preferred the high-dose cycle compared with the lower dose continuous inhalation, but this was not linked to objective data on efficacy. CONCLUSIONS: The present trial fails to provide convincing evidence for superiority in efficacy of either of the two treatment regimens of inhaled tobramycin in CF patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".