The prognostic importance of worsening dyspnoea in systemic sclerosis related interstitial lung disease
Bibliographic record
Abstract
OBJECTIVES: To determine the prognostic importance of worsening dyspnoea in systemic sclerosis (SSc) related interstitial lung disease (ILD). METHODS: SSc patients were recruited from the Australian Scleroderma Cohort Study. ILD was defined as present if characteristic fibrotic changes on high-resolution computer tomography (HRCT) scan lung were seen, performed based on clinical suspicion. Determinants of survival in SSc-ILD were analysed, specifically the prognostic impact of ILD progression, defined according to the ATS, INBUILD and spirometric definitions of progressive pulmonary fibrosis, and the presence of worsening dyspnoea using accelerated failure time survival analysis. RESULTS: In our cohort of 2198 SSc patients, 17.7% (n = 389) developed incident ILD over a median (IQR) follow-up period of 5.8 (2.8-9.9) years. A third of our incident ILD cohort (38.3%, n = 149) experienced progressive ILD. In those who experienced progressive ILD, mortality was significantly higher in those who reported recent worsening dyspnoea in the prior month irrespective of a decline in spirometric parameters. CONCLUSION: 38.8% of those with incident ILD experienced ILD progression over follow-up. Patient-reported worsening dyspnoea in the month prior, irrespective of changes in spirometry, was strongly associated with mortality, with a magnitude equivalent to that of the presence of progressive ILD as defined by the ATS, INBUILD and spirometric definitions of progressive ILD. This study has highlighted the prognostic importance of patient-reported symptoms in the evaluation of 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".