Elucidating the Dynamic Nature of Bacterial Infections in Cystic Fibrosis (CF) Lower Airways: A Cohort Study
Bibliographic record
Abstract
Background. CF has long been characterized as a disease of chronic infections. Indeed, prevalence of classical CF pathogens such as Pseudomonas aeruginosa (PA), Staphylococcus aureus (SA) and Haemophilus influenzae (HI) is recorded by international registries. Yet these represent only a small portion of organisms capable of infecting the CF airways. Herein we sought to characterize the incidence of new airway infections and examine associated risk factors. Methods. CF patients attending the Calgary Adult CF clinic from 2002 to 2012 with ≥1 sputum culture within a calendar year were included. Baseline demographics and annual microbiology (starting 12 months preceding study entry) were recorded. Patient demographics including baseline and chronic infections were assessed for associations with incident infections. Known demographic and microbiologic factors were studied for their association with incident infection. Incidence rates and ratios (IRR) were calculated using STATA 13.1 (College Station, TX). Results. A total of 189 patients (41% male, median age 21.4 years [IQR 18.3–29.4]) were analyzed. A total of 137 patients (72.5%) experienced 354 incident infections over 1159.9 patient-years, at a rate of 30.52 new infections/100 person-years. Thirty distinct genera were identified, with the most incident infections being caused by HI (22.0%), SA (14.7%), the Enterobacteriaceae (14.7%), PA (11.9%), Stenotrophomonas maltophilia (7.7%) and Streptococcus pyogenes (3.1%). Patients without chronic PA infection at baseline had a significantly increased rate of incident infection acquisition compared to those with chronic PA (IRR 1.32 [95% CI, 1.04–1.66]; p = 0.02). Conversely, those with SA at baseline had a greater rate of incident infections than those without (IRR 1.52 [95% CI, 1.20–1.93]; p < 0.001). Male sex, deltaF508 homozygosity, and pancreatic insufficiency were not associated with infection acquisition risk (p > 0.05). Conclusion. While CF is known for chronic infections, incident infections abound. Data herein demonstrate lower airways are highly dynamic with a multitude of infecting organisms. Of note, PA seemed to competitively inhibit incident infections. Perhaps the declining prevalence of PA infected CF patients is expanding the spectrum of CF pathogens. Disclosures. All authors: No reported disclosures
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".