Cough is less common and less severe in systemic sclerosis‐associated interstitial lung disease compared to other fibrotic interstitial lung diseases
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: The objectives of this study were to determine the prevalence and characteristics of cough in idiopathic pulmonary fibrosis (IPF), chronic hypersensitivity pneumonitis (HP) and systemic sclerosis-associated interstitial lung disease (SSc-ILD). METHODS: Cough severity was measured in consecutive patients with IPF (n = 77), HP (n = 32) and SSc-ILD (n = 67) using a 10-cm visual analogue scale (VAS). Dyspnoea and quality of life were measured using established questionnaires. Cough severity was compared across ILD subtypes and predictors of cough severity were determined using multivariate analysis. RESULTS: Cough was more common in IPF and chronic HP compared to SSc-ILD (87% and 83% vs 68%, P = 0.02). The median (interquartile range) VAS score was 39 (17-65) in the IPF cohort, 29 (11-48) in HP and 18 (0-33) in SSc-ILD (P < 0.0001). Cough was more often productive in chronic HP and IPF (63% and 43% vs 21%, P < 0.001). Cough severity was independently predicted only by ILD diagnosis and higher dyspnoea score. Cough severity was not associated with other common causes of cough. Cough was a significant predictor of quality of life in IPF and SSc-ILD with adjustment for age, sex, dyspnoea and ILD severity; however, cough was not associated with quality of life in chronic HP. CONCLUSION: Cough is more frequent, more severe and more often productive in IPF and chronic HP compared to SSc-ILD, despite similar ILD severity in these cohorts. Cough severity is strongly and independently associated with dyspnoea and pulmonary function, and is a significant contributor to reduced quality of life in both IPF and SSc-ILD.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".