A real world evaluation of the long-term efficacy of strategies to prevent chronic Pseudomonas aeruginosa pulmonary infection in children with cystic fibrosis
Bibliographic record
Abstract
BACKGROUND: Children with cystic fibrosis (CF) are susceptible to chronic Pseudomonas aeruginosa (PA) infection. Early eradication of PA has proven short-term efficacy. No studies have evaluated the long- term impact of early eradication for CF patients, particularly those diagnosed by newborn screening (NBS). Our objective was to quantify the long-term impact of early PA eradication on the risk of chronic PA infection in children (0-18 years old) with CF prior to and following the introduction of a province-wide NBS program. METHODS: This 20-year retrospective cohort study compared 94 patients eligible for treatment with inhaled tobramycin at first PA isolation ("recent cohort") with 27 historical controls ("historical cohort"). RESULTS: A smaller proportion of patients in the recent cohort developed chronic PA (24% versus 78%; P<0.001); the adjusted risk of chronic infection was 2.90 (95%CI 1.47, 5.76; P=0.002) in the historical vs recent cohort. However, NBS was not independently associated with the risk of chronic PA infection after its introduction. CONCLUSIONS: Early eradication of PA, irrespective of early diagnosis, is associated with reduced risk of chronic PA. However, concomitant improvements in medical care since the introduction of early eradication protocols may have contributed to these long-term observed benefits.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".