Digital Amputation in Systemic Sclerosis: Prevalence and Clinical Associations. A Retrospective Longitudinal Study
Bibliographic record
Abstract
OBJECTIVE: To evaluate the prevalence of digital necrosis requiring surgical amputation in a single-center group of patients with systemic sclerosis (SSc) and to compare the characteristics of patients with and those without this severe complication. METHODS: We reviewed the medical records of 188 patients with SSc [162 women, 26 men, mean age 59.2 yrs, mean disease duration 8.0 yrs, mean time from onset of Raynaud's phenomenon (RP) 11.7 yrs, median followup duration 92 mo] enrolled in the Rheumatology Unit since 2004. Demographic and clinical features were collected, as well as the presence of the typical risk factors for atherosclerosis. RESULTS: Nine patients (4.8%) underwent partial or total surgical digital amputation because of necrotic process; all these patients except 1 had a long history of multiple and persisting digital ulcers. All 9 patients had concomitant large-vessel involvement. Comparison of cases with and without digital amputation showed that this complication was associated with older age, long history of RP, long disease duration, presence of anticentromere antibody, and coexistence of peripheral artery disease and hypercholesterolemia. Discussion. We noted that 4.8% of patients with SSc underwent digital amputation. Our retrospective analysis suggests that peripheral artery disease is strongly associated with digital amputation. The preventive strategy for digital ulcers and amputation associated with SSc should include an extensive diagnostic and preventive investigation for peripheral atherosclerosis.
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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 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".