Intact Calibers of Retinal Vessels in Patients with Systemic Sclerosis
Bibliographic record
Abstract
OBJECTIVE: A primary endothelial cell dysfunction is thought to be involved in systemic sclerosis (SSc)-associated fibroproliferative vasculopathy of the microcirculation and small arterioles, even in sites not affected by fibrosis. Because the role of fibroblasts in pathologic modifications and vascular wall remodeling is relatively unclear, and because the retina provides a unique opportunity to assess microcirculation in the absence of resident fibroblasts, we systematically evaluated retinal vessels in patients with SSc. METHODS: Digital retinal images were obtained from both eyes of 93 consecutive patients with fully characterized SSc and 29 healthy controls matched 1:1 for age and sex with selected patients without diabetes, hypertension history, or antihypertensive treatment. Internal microvascular calibers (erythrocyte column width in μm) by central retinal arteriolar and venular equivalents and arteriolar to venular ratio were measured using validated software. RESULTS: Arteriolar and venular calibers were similar in patients and their matched controls (mean ± SEM; 187 ± 2 vs 184 ± 3, p = 0.444, and 211 ± 2 vs 216 ± 3, p = 0.314, respectively). Both arteriolar and venular calibers and their ratio in patients with SSc were not associated with disease duration, extent of skin involvement, pulmonary fibrosis, digital ulcers or pitting scars, amputations, digital capillaroscopic findings, inflammatory indices, or autoantibodies. CONCLUSION: The evidence that retinal microcirculation is spared in SSc suggests that fibroproliferative vasculopathy may depend on specific cellular or soluble factors not present in the retinal environment.
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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 | 0.000 | 0.002 |
| 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 | 0.000 | 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".