Inhaled Antibiotics for Lower Airway Infections
Bibliographic record
Abstract
Inhaled antibiotics have been used to treat chronic airway infections since the 1940s. The earliest experience with inhaled antibiotics involved aerosolizing antibiotics designed for parenteral administration. These formulations caused significant bronchial irritation due to added preservatives and nonphysiologic chemical composition. A major therapeutic advance took place in 1997, when tobramycin designed for inhalation was approved by the U.S. Food and Drug Administration (FDA) for use in patients with cystic fibrosis (CF) with chronic Pseudomonas aeruginosa infection. Attracted by the clinical benefits observed in CF and the availability of dry powder antibiotic formulations, there has been a growing interest in the use of inhaled antibiotics in other lower respiratory tract infections, such as non-CF bronchiectasis, ventilator-associated pneumonia, chronic obstructive pulmonary disease, mycobacterial disease, and in the post-lung transplant setting over the past decade. Antibiotics currently marketed for inhalation include nebulized and dry powder forms of tobramycin and colistin and nebulized aztreonam. Although both the U.S. Food and Drug Administration and European Medicines Agency have approved their use in CF, they have not been approved in other disease areas due to lack of supportive clinical trial evidence. Injectable formulations of gentamicin, tobramycin, amikacin, ceftazidime, and amphotericin are currently nebulized "off-label" to manage non-CF bronchiectasis, drug-resistant nontuberculous mycobacterial infections, ventilator-associated pneumonia, and post-transplant airway infections. Future inhaled antibiotic trials must focus on disease areas outside of CF with sample sizes large enough to evaluate clinically important endpoints such as exacerbations. Extrapolating from CF, the impact of eradicating organisms such as P. aeruginosa in non-CF bronchiectasis should also be evaluated.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.024 | 0.015 |
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".