Newer antibacterial agents and their potential role in cystic fibrosis pulmonary exacerbation management
Bibliographic record
Abstract
Pulmonary exacerbations in cystic fibrosis (CF) are frequent events and account for a substantial proportion of the burden of morbidity and mortality in this disease. Antibacterial therapies to treat pulmonary exacerbations are instituted empirically and are individualized based on both patient factors (severity of exacerbation, frequency of exacerbation, recent courses of anti-infectives) and pathogen factors (previously isolated pathogens and in vitro predicted susceptibilities). However, the epidemiology of pathogens infecting CF airways is changing, with increased incidence of methicillin-resistant Staphylococcus aureus (MRSA), drug-resistant Pseudomonas aeruginosa and other Gram-negative non-fermenters such as Stenotrophomonas maltophilia and Achromobacter xylosoxidans. Accordingly, a great need for new and novel agents for the management of acute exacerbations in CF exists. While several antibiotics have recently been approved or are close to approval for clinical use, frequently their emphasis has been for Gram-positive, and specifically MRSA-related, disease. Despite this, these agents may have a role in CF-related exacerbations. This article reviews the spectrum of activity, pharmacokinetics and clinical and theoretical evidence for the use of newer agents including tigecycline, doripenem and ceftobiprole in the management of CF pulmonary exacerbations. Appropriate use of these agents in CF will require detailed CF-specific pharmacokinetic and pharmacodynamic data.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".