Changing Pattern of Sputum Cell Counts During Successive Exacerbations of Chronic Obstructive Pulmonary Disease.
Bibliographic record
Abstract
BACKGROUND: Chronic Obstructive Pulmonary Disease exacerbations are associated with worsening of airway inflammation, the nature of which may be neutrophilic, eosinophilic, or both. OBJECTIVE: The primary objective was to examine the cellular nature of airway inflammation in successive COPD exacerbations in order to ascertain if they changed in individual patients. The secondary objective was to estimate the relative risk indicating the extent to which a particular type of exacerbation changed as a function of the most recent exacerbation. DESIGN: This was a retrospective survey performed on a computerised sputum cell count database of a referral respiratory service in Hamilton, Canada. Recurrent event analyses were used to model the incidence of exacerbations and subtypes of exacerbations. RESULTS: 359 patients and 148 patients had sputum examined during stable condition and during exacerbations, respectively. It was found 65 patients had sputum examined during both situations. The exacerbations were eosinophilic in 15.9%, neutrophilic in 18%, combined in 2.6%, of unknown clinical significance in 19.6% and normal in 19.6%. There were missing counts for 24.3% samples. In 85.2% of patients, a different subtype of bronchitis was noted in successive exacerbations. The relative risk of a subsequent neutrophilic or eosinophilic exacerbation was 6.24 (p = 0.02) and 2.8 (p = 0.24) when the previous exacerbation was neutrophilic or eosinophilic respectively. CONCLUSIONS: This non-intervention study suggests that the cellular nature of bronchitis is largely unpredictable and needs to be examined at each COPD exacerbation This has important implications in choosing the appropriate therapy. Future intervention studies would provide further evidence.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".