Lung Function and Survival in Systemic Sclerosis Interstitial Lung Disease
Bibliographic record
Abstract
To the Editor: Systemic sclerosis (SSc)-associated interstitial lung disease (ILD) affects 40% of patients with SSc and leads to reduced survival, even with mild disease1. Among patients with SSc-ILD, reductions in forced vital capacity (FVC) and DLCO predict mortality, with threshold percent-predicted FVC values of < 70%2,3 and < 55%4, and DLCO values ≤ 60%5 and ≤ 70%6 identified as predictors of poor outcome. We sought to assess for threshold values of baseline FVC and DLCO that are associated with survival in SSc-ILD. Our study was approved by the University Health Network (REB number 11-0001-AE) and Mount Sinai Hospital (REB number 11-0003-C) research ethics boards, with requirement for informed consent waived. Adult patients were identified from our Scleroderma and ILD clinics (1983–2012) if they fulfilled the American College of Rheumatology (ACR) classification criteria for SSc7 and had findings of ILD on thoracic computerized tomography. Pulmonary function tests (PFT) were routinely performed. The primary outcome was death or lung transplantation (last determined May 2012) from clinic or hospital records, or obituary8. Survival was defined as time from ILD diagnosis to death/transplantation, right censored from last … Address correspondence to Dr. T.K. Marras, Toronto Western Hospital, 7E-452, 399 Bathurst St., Toronto, Ontario M5T 2S8, Canada.E-mail: Ted.Marras{at}uhn.ca
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".