Esophageal Dilation and Other Clinical Factors Associated With Pulmonary Function Decline in Patients With Systemic Sclerosis
Bibliographic record
Abstract
OBJECTIVE: To identify clinical factors, including esophageal dilation on chest high-resolution computed tomography (HRCT), that are associated with pulmonary function decline in patients with systemic sclerosis (SSc). METHODS: Patients fulfilled 2013 SSc criteria and had ≥ 1 HRCT and ≥ 2 pulmonary function tests (PFTs). According to published methods, widest esophageal diameter (WED) and radiographic interstitial lung disease (ILD) were assessed, and WED was dichotomized as dilated (≥ 19 mm) vs not dilated (< 19 mm). Clinically meaningful PFT decline was defined as % predicted change in forced vital capacity (FVC) ≥ 5 and/or diffusion capacity for carbon monoxide (DLCO) ≥ 15. Linear mixed effects models were used to model PFT change over time. RESULTS: One hundred thirty-eight patients with SSc met the study criteria: 100 (72%) had radiographic ILD; 49 (35%) demonstrated FVC decline (median follow-up 2.9 yrs). Patients with antitopoisomerase I (Scl-70) autoantibodies had 5-year FVC% predicted decline (-6.33, 95% CI -9.87 to -2.79), whereas patients without Scl-70 demonstrated 5-year FVC stability (+1.78, 95% CI -0.59 to 4.15). Esophageal diameter did not distinguish between those with vs without FVC decline. Patients with esophageal dilation had statistically significant 5-year DLCO% predicted decline (-5.58, 95% CI -10.00 to -1.15), but this decline was unlikely clinically significant. Similar results were observed in the subanalysis of patients with radiographic ILD. CONCLUSION: In patients with SSc, Scl-70 positivity is a risk factor for FVC% predicted decline at 5 years. Esophageal dilation on HRCT was associated with a minimal, nonclinically significant decline in DLCO and no change in FVC during the 5-year follow-up. These results have prognostic implications for SSc-ILD patients with esophageal dilation.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".