The prevalence of bronchitis and associations with spirometry in patients with interstitial lungdisease in a Canadian tertiary care centre
Bibliographic record
Abstract
Cough in diffuse interstitial lung diseases (ILD) is a common and debilitating symptom with many proposed causative factors. The contribution of airway inflammation to cough has not been quantified and the association between bronchitis and lung function has not been measured. Sputum cell counts (SCC) could potentially be theragnostic for cough in ILD. The objectives of this study are to describe the prevalence of bronchitis, as measured by SCC, in patients with chronic cough and ILD to determine if bronchitis is associated with significant changes in spirometry. This is a retrospective study of patients with ILD who had a SCC ordered for chronic cough at the Firestone Institute from 2005-2018. Patients were identified from a sputum database and ILD clinic lists and the criteria for bronchitis (based on normative values) were applied. SCC was completed 303 times for ILD patients (n=175). The most common diagnostic categories were idiopathic interstitial pneumonia (29.3%) and CTD-ILD (27.6%), with idiopathic pulmonary fibrosis the most common condition (10.2%). SCC demonstrated eosinophilic, neutrophilic, and lymphocytic bronchitis in 31.1%, 29.1%, and 6.4% of cases, respectively. The presence of bronchitis was associated with a lower FEV1 (µ=1.98 vs 2.31L, p=0.003, t-test) and FVC (µ=2.51 vs 2.92L, p=0.003, t-test), but bronchitis was not predictive of FEV1 or FVC in a multivariate model. In a Canadian tertiary care centre, bronchitis was common in patients with ILD and chronic cough. Though bronchitis was associated with lower spirometry, it was not predictive of FEV1 or FVC when incorporated in a multivariate model.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".