Intermittent inhaled tobramycin and systemic cytokines response in CF patients with Pseudomonas aeruginosa
Bibliographic record
Abstract
INTRODUCTION: CF pulmonary guidelines recommend alternate therapy (one month on, one month off) with inhaled tobramycin for chronic Pseudomonas aeruginosa colonization in cystic fibrosis (CF). Tobramycin-inhaled powder (TIP™) is increasingly replacing time-consuming nebulizer therapy. It is unclear whether laboratory parameters change during the month off period compared with the month on therapy. PURPOSE: Our aim was to assess whether spirometry, lung clearance index and circulating inflammatory markers differ between on/off treatment periods. MATERIALS AND METHODS: A prospective pilot study evaluating CF patients treated with TIP, on two consecutive months (on/off) therapy. The evaluations were performed at the end of a month off therapy (1-2 days before the initiation of TIP) and after 28 days of treatment with TIP (1-2 days after the end of the treatment cycle). RESULTS: Nineteen CF patients (10 males) with a mean age of 18.7±9.7 years and BMI (body mass index) of 19.62±3.53 kg/m2 were evaluated. After a month off treatment with TIP, spirometry parameters and lung clearance index remained unchanged. IL-6 increased significantly (p=0.022) off treatment. There was a non-significant change in the other inflammatory cytokines off therapy [hs-CRP, IL-8,TNF-α, α1-antitrypsin (α1AT) and neutrophilic elastase]. CONCLUSIONS: The results of lung function parameters support the relative stability of CF patients during the month off therapy; however, the difference in serum IL-6 raises the possibility of ongoing higher degrees of inflammation during the month off therapy with TIP. The small sample size and the multiple parameters evaluated preclude firm conclusions; therefore, larger multicenter studies are needed to assess the on/off treatment strategy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".