Keloid scarring, but not Dupuytren’s contracture, is associated with unexplained carotid atherosclerosis
Bibliographic record
Abstract
BACKGROUND: Atherosclerosis, a response to injury, may be thought of as scarring in the artery wall. TGF-beta and associated signaling molecules have been implicated in the pathophysiology of keloid scarring, Dupuytren's Contracture and atherosclerotic plaques in independent studies. PURPOSE: To test the hypothesis that excess cutaneous scarring and Dupuytren's contractures predispose independently to carotid atherosclerosis . METHODS: Among 1,747 patients with plaque measurements and complete data for multivariable regression analysis, 57 Caucasian patients had Dupuytren's contractures and 12 had keloid scars. Carotid total plaque area (TPA) was measured by 2-Dimensional ultrasound. RESULTS: In linear multivariable regression analysis with coronary risk factors, keloid scars were associated with TPA (P= 0.018), but Dupuytren's contractures were not. Patients with keloid scarring were younger (P < 0.0001), and more likely to be diabetic (P < 0.0001) CONCLUSIONS: Keloid scarring is a clinical clue to excess atherosclerosis not explained by traditional risk factors. Such patients may benefit from therapy directed at targets related to signalling molecules common to both the process of keloid scarring and atherosclerosis. These findings suggest previously unexplored possibilities for the prevention and treatment of atherosclerosis. The differences between Dupuytren's and keloid scars that may identify such targets are discussed.
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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 | 0.001 | 0.002 |
| 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 | 0.007 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".