Aztreonam lysine: a novel inhalational antibiotic for cystic fibrosis
Bibliographic record
Abstract
Michael D Parkinsabcabc & J Stuart Elborn*cdda Department of Medicine, University of Calgary and Alberta Health Services, Calgary, Alberta, Canadab Department of Microbiology and Infectious Disease, University of Calgary and Alberta Health Services, Calgary, Alberta, Canadac North Ireland Adult Cystic Fibrosis Centre, Level 8, Belfast City Hospital, Belfast Health and Social Trust, Belfast, BT9 7AB, UKd Center for Infection and Immunity, Queen’s University, Belfast, UK. † Author for correspondenceAcquisition of Pseudomonas aeruginosa, the most prevalent organism isolated from cystic fibrosis (CF) airways, is associated with an accelerated clinical deterioration and reduced survival. Strategies to chronically suppress P. aeruginosa infections in individuals with CF have evolved over the last four decades and now largely focus on regular administration of aerosolized antibiotics. Aztreonam lysine (AZLI; Cayston®, Gilead Pharmaceuticals [Foster City, CA, USA]), a novel formulation of the monobactam aztreonam suitable for aerosol delivery has recently been developed. AZLI is administered as 75 mg three-times daily for 28 days in ‘on/off’ cycles using the Altera™/eFlow® electronic nebulizer (PARI Innovative Manufacturers [Midlothian, VA, USA]). In individuals with CF chronically infected with P. aeruginosa, AZLI improved healthcare-associated quality-of-life scores, pulmonary function and weight, prolonged time to requirement of antibacterial therapy for symptoms of pulmonary exacerbation and reduced P. aeruginosa sputum burdens. These outcomes were durable over 18 months of cycled use. AZLI has been demonstrated to be safe and effective, and expands available chronic maintenance therapies in CF.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".