Home Microbiological Sampling in a Pediatric Cystic Fibrosis Population: Pandemic Implementation and Ongoing Use
Bibliographic record
Abstract
BACKGROUND: During the coronavirus disease 2019 (COVID19) pandemic, restrictions on in-person care threatened to disrupt in-clinic airway sampling for microbiological surveillance, a vital aspect of cystic fibrosis (CF) care. In response, institutions developed home airway sampling strategies to allow continued guidelines-based microbiological surveillance. The validity of this sampling technique and its ongoing use has not been reviewed. Our aim is to characterize the frequency of home versus in-clinic airway sampling at our institution before, during, and after COVID19 and to compare the positivity rates of significant CF pathogens in both sampling methods. METHODS: This single center, retrospective cohort study included children with CF with at least one airway culture between January 1st, 2019, and May 16th, 2023. Culture data were extracted from an electronic microbiological database and individual culture locations (home or clinic) were confirmed manually from patient charts. RESULTS: Two thousand six hundred and thirty eight cultures were included from 170 patients (52.4% male, mean age 6.2 years). Of these, 2080 were collected by healthcare providers at BCCH and 558 were collected at home by parents or caregivers. Overall, the positivity rate of all pathogens was higher in home collected samples (rate ratio: 1.46, 95%CI: 1.32-1.61, p < 0.001) than in-clinic collected samples. However, on a species-by-species analysis, only the positivity rate of other gram-negative bacilli had significantly higher positivity in home-collected samples (rate ratio: 1.69, 95%CI: 1.16-2.46, p = 0.01). CONCLUSION: The similar positivity rates of clinically significant CF pathogens suggest that home sampling is comparable to clinic sampling, though future prospective studies are needed to confirm this hypothesis.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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".