Microbiology sampling in non-cystic fibrosis bronchiectasis cases from northern Alberta
Bibliographic record
Abstract
Non-cystic fibrosis bronchiectasis (NCFB) is a chronic respiratory disease resulting in chronic cough, thick sputum, and lower airway microbial colonization, akin to patients with cystic fibrosis (CF). NCFB is a common, yet under recognized entity which inflicts significant morbidity and mortality particularly to older individuals, with a rising prevalence in the developed world. Given that sputum cultures are a non-invasive method to characterize the lower airway microbiota in NCFB patients, for which pathogenic organisms are associated with worsened outcomes, we sought to characterize the microbiological pattern and clinical outcomes associated with sputum culture in a cohort of NCFB patients from Western Canada. A total of 20 subjects were prospectively recruited from various bronchiectasis clinics across the Greater Edmonton area. A retrospective chart review and a symptoms questionnaire was performed, gathering information not limited to symptoms, comorbidities, exacerbations, hospitalizations, sputum production, and sputum culture results over the prior 5 years. Subjects reported frequent hospitalization alongside a significant burden of symptoms. A large majority of sputum cultures grew pathogenic organisms such as Haemophilus influenzae and Pseudomonas aeruginosa. We also note the considerable waste and inefficiency associated with sputum cultures, outlining areas for which this important diagnostic modality can be improved. Accurate characterization of the airway microbiota alongside efficient delivery of health services are key to ensuring the proper treatment of individuals with NCFB, given their high disease burden and frequent hospitalization.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".