Longitudinal changes in the cystic fibrosis airway microbiota with time and treatment
Bibliographic record
Abstract
BACKGROUND: Whether there is any benefit in integrating culture-independent molecular analysis of the lower airway microbiota of people with cystic fibrosis into clinical care is unclear. This study determined the longitudinal trajectory of the microbiota and if there were microbiota characteristics that corresponded with response to treatment or predicted a future pulmonary exacerbation. METHODS: At least one sputum sample was collected from 149 participants enrolled in this prospective longitudinal multi-centre study and total bacterial density and microbiota community measurements were determined and compared with clinical parameters. RESULTS: In 114 participants with paired samples when clinically stable, ∼8 months apart, the microbiota remained conserved between timepoints, regardless of whether participants received acute intravenous antibiotic treatment or not. In 62 participants, who presented with an acute exacerbation, a decrease in community richness correlated best with patient response to antibiotic treatment. Analysis of baseline samples from 30 participants who exacerbated within 4 months of their stable sample being collected and 72 participants who remained stable throughout the study showed that community characteristics such as lower richness at baseline may be predictive of an exacerbation in addition to several clinical parameters. However, lasso regression analysis indicated that only lung function (p = 0.014) was associated with a future exacerbation. CONCLUSIONS: The airway microbiota remains stable over periods <1 year with modest shifts related to treatment apparent which might provide some additional insights to patient-level measurements.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".