Epidemiology of Clonal <i>Pseudomonas Aeruginosa</i> Infection in a Canadian Cystic Fibrosis Population
Bibliographic record
Abstract
RATIONALE: The extent of the genetic relatedness among Pseudomonas aeruginosa isolates and its impact on clinical outcomes in the cystic fibrosis (CF) population is poorly understood. OBJECTIVES: The objectives of this study were to determine the prevalence of clonal P. aeruginosa infection in Canada and to associate P. aeruginosa genotypes with clinical outcomes. METHODS: This was an observational study of adult and pediatric patients with CF across Canada. Isolates were typed using multilocus sequence typing. A clone was defined as sharing at least six of seven alleles. Genotyping results were associated with clinical outcomes, including forced expiratory volume in 1 second, body mass index, rate of pulmonary exacerbation, and death/transplant. RESULTS: A total of 1,537 P. aeruginosa isolates were genotyped to 403 unique sequence types (STs) in 402 individuals with CF. Although 39% of STs were shared, most were shared only among a small number of subjects, and the majority (79%) of the genetic diversity in P. aeruginosa isolates was observed between patients. There were no significant differences in clinical outcomes according to genotype. However, patients with a dynamic, changing ST infection pattern had both a steeper decline in forced expiratory volume in 1 second (-2.9% predicted change/yr, 95% confidence interval [CI] = -3.8 to -1.9 compared with 0.4, 95% CI = -0.3 to 1.0; P < 0.001) and body mass index (-1.0 percentile change/yr, 95% CI = -1.6 to -0.3 compared with -0.1, 95% CI = -0.7 to 0.5; P = 0.047) than those with a stable infection with the same ST. CONCLUSIONS: There was no widespread sharing of dominant clones in our CF population, and the majority of the genetic diversity in P. aeruginosa was observed between patients. Changing genotypes over time within an individual was associated with worse clinical outcomes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".