Acquisition and eradication of P. aeruginosa in young children with cystic fibrosis
Bibliographic record
Abstract
When do infants and young children with cystic fibrosis acquire infection with Pseudomonas aeruginosa? Can this be eradicated when first detected? Children <6 yrs of age participated in an annual bronchoalveolar lavage (BAL)-based microbiological surveillance programme in Perth, Australia. When P. aeruginosa was detected, an eradication programme using combination treatment with i.v., oral and nebulised antibiotics was undertaken. Repeat BAL was performed 3 months following treatment, to assess eradication success. P. aeruginosa was detected in 33 (28.4%) children; median (range) age at detection was 30.5 (3.3-71.4) months. P. aeruginosa was mucoid at detection in six (18.2%) out of 33 patients and associated with respiratory symptoms in 16 (48.5%) out of 33 children. In total, 26 children underwent eradication therapy, with P. aeruginosa eradicated in 20 (77%) out of 26 following one eradication cycle and in three (total 88%) additional children following a second cycle. Eradication was associated with a significant decrease in neutrophil elastase and interleukin-1beta in BAL fluid 12 months post eradication. Eradication of Pseudomonas aeruginosa infection is achievable in young children with cystic fibrosis for up to 5 yrs using combination i.v., oral and nebulised antibiotic therapy and is associated with reduced pulmonary inflammation 12 months post eradication.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".