Summary of findings: aztreonam lysine for inhalation vs tobramycin: Need for antibiotics see pulmonary exacerbations
Summary of findings: aztreonam lysine for inhalation probably leads to lower pulmonary exacerbations: need for additional antibiotics compared with tobramycin (moderate certainty).
What each review found
Current versions only| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Summary of findings: aztreonam lysine for inhalation vs tobramycin Pulmonary exacerbations: need for additional antibiotics · children and adults with CF and P aeruginosa Summary of findings: aztreonam lysine for inhalation probably leads to lower pulmonary exacerbations: need for additional antibiotics compared with tobramycin (moderate certainty). Inhaled anti‐pseudomonal antibiotics for long‐term therapy in cystic fibrosis (2022) · Cochrane Headline outcomes only | RR 0.66 [0.51, 0.86] | 1 study · 268 participants | Moderate |
Summary of findings: aztreonam lysine for inhalation vs tobramycin Pulmonary exacerbations: need for additional antibiotics. · children and adults with CF and P aeruginosa Summary of findings: aztreonam lysine for inhalation probably leads to lower pulmonary exacerbations: need for additional antibiotics. compared with tobramycin (moderate certainty). Inhaled anti‐pseudomonal antibiotics for long‐term therapy in cystic fibrosis (2018) · Cochrane Headline outcomes onlyearlier version CD001021.PUB3, superseded | RR 0.66 [0.51, 0.86] | 1 study · 268 participants | Moderate |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Inhaled anti‐pseudomonal antibiotics for long‐term therapy in cystic fibrosis 2022 · Cochrane Headline outcomes only | Not reported | list not extracted yet | Not assessed |
Studies behind the findings
None of these reviews ties its included studies to this outcome in the data here. Cochrane reviews and reviews with headline outcomes only do not list their studies yet.
How reviews are matched to this question
Reviews word the same question differently. Four decision models (TypeSafe's Jev, Liquid AI's d1-ultra, SubQ Snap and Baseten's Elephant) judged each wording of the population, intervention, comparator and outcome against the others; two wordings count as the same when at least three of them agree and none clearly disagrees, and findings count as this question only when all four elements match. Timing, setting and subgroup never split a question: they are shown on each finding.