Heterogeneity of Bronchitis in Airway Diseases in Tertiary Care Clinical Practice
Bibliographic record
Abstract
BACKGROUND: Sputum cell counts have identified inflammatory subtypes of bronchitis in relatively small numbers of subjects with asthma, chronic obstructive pulmonary disease (COPD) and chronic cough in research studies. The prevalence of different subtypes of bronchitis in routine clinical practice, however, has not been reported. OBJECTIVE: To examine the heterogeneity of bronchitis and its relationship to the severity of airflow obstruction. METHODS: A retrospective cross-sectional survey based on a computerized database of spontaneous or induced sputum cell counts examined in a large university tertiary respiratory outpatient clinic. RESULTS: The database contained 4232 consecutive sputum records from 2443 patients with chronic cough (39%), asthma (37%), asthma with COPD (9%), COPD (13%) and bronchiectasis (3%). Total and differential cell counts were obtained from 86% of successful sputum samples. Induced sputum provided more viable samples than spontaneous expectorate. Approximately one-third of patients with asthma and one-fifth of patients with COPD experience eosinophilic bronchitis. Asthmatic patients with moderate to severe airflow obstruction had a greater number of sputum eosinophils. There was a significantly higher number of total cell counts and percentage of neutrophils in the sputum of COPD patients with moderate and severe airflow obstruction than in those with mild airflow obstruction. CONCLUSION: There is heterogeneity in the cellularity of sputum in various airway diseases. Patients with clinically stable airway diseases may have high sputum cell counts. During exacerbations, more patients may experience neutrophilic bronchitis. Severity of airflow obstruction is associated with eosinophilic bronchitis in patients with asthma, and neutrophilic bronchitis in patients with nonasthmatic COPD.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".