Update on the diagnosis and management of cystic fibrosis pulmonary exacerbations
Bibliographic record
Abstract
Pulmonary exacerbations in people with cystic fibrosis are associated with significant morbidity and reduced quality of life. Pulmonary exacerbation treatment guidelines, published by an expert panel assembled by the Cystic Fibrosis Foundation nearly 15 years ago, were primarily consensus-based as there were several gaps in the evidence base. In particular, limited evidence existed regarding optimal pulmonary exacerbation treatment strategies, including duration of antibiotic therapy, treatment location, antibiotic selection, and the role of systemic corticosteroids. Over the last decade, results from observational studies and large multi-center randomized controlled trials have begun to answer important questions related to pulmonary exacerbation treatment. This review focuses on the diagnosis, etiology, and changing epidemiology of pulmonary exacerbations, and also summarizes the most recent and up-to-date studies describing pulmonary exacerbation treatment. Finally, this review provides consideration for future pulmonary exacerbation research priorities, particularly in the current highly effective modulator therapy era.
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 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 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".