P005 <break /> Rate of progression in short-term and long-term survivors with systemic sclerosis-associated interstitial lung disease
Bibliographic record
Abstract
Rationale: Interstitial lung disease (ILD) progression has been hypothesized to be more rapid early in the course of systemic sclerosis (SSc); however, there are limited data to support this. We studied a cohort of SSc-ILD patients to determine whether progression is more rapid early in the disease and to identify predictors of mortality. Methods: Patients with SSc-ILD were recruited from an ILD centre. High-resolution computed tomography scans (HRCTs) were objectively scored by a chest radiologist. Clinical parameters were extracted from medical records. Mixed effects models were used to assess trends in lung function over time. Bivariate and multivariate analyses were used to identify predictors of mortality. Results: 172 patients with SSc-ILD were included (mean age 55.3 years, 83% women). Most patients had mild-to-moderate lung function impairment. There was no difference in rate of progression between patients that died within 4 years of diagnosis, died between 4-8 years, and survived >8 years after adjusting for age and sex (FVC%-predicted: p = 0.072, HRCT fibrosis score: p = 0.056; Figure 1A). Those living >4 years had a rapid decline in FVC%-predicted within 2 years of diagnosis, then stabilized before progressing again at 8 years (Figure 1B). Scl70, FVC%-predicted, DLCO%-predicted, 6-minute walk distance, right ventricular systolic pressure, and HRCT fibrosis score predicted mortality on bivariate analysis. Scl70, FVC%-predicted, and walk distance predicted mortality on multivariate analysis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".