Insights into the Pathophysiology of Hypertrophic Scars and Keloids: How Do They Differ?
Bibliographic record
Abstract
GENERAL PURPOSE: To provide information about the clinical presentation of hypertrophic scars and keloids based on their varied structural components. TARGET AUDIENCE: This continuing education activity is intended for physicians, physician assistants, nurse practitioners, and nurses with an interest in skin and wound care. LEARNING OBJECTIVES/OUTCOMES: After completing this continuing education activity, you should be able to: ABSTRACT: Hypertrophic scars and keloids are firm, raised, erythematous plaques or nodules that manifest when the cicatrix fails to properly heal. They result from pathologic wound healing and often cause pain and decreased quality of life. The appearance of such cosmetically unappealing scars affects the confidence and self-esteem of many patients. These scars can also cause dysfunction by interfering with flexion and extension across joints. Both possess some unique and distinct histochemical and physiologic characteristics that set them apart morphologically and at the molecular level. While these entities have been the focus of research for many years, differentiating between them remains challenging for clinicians.This article reviews the clinical presentation of aberrant scars and illustrates how they can be differentiated. It outlines their pathophysiology and emphasizes the unique molecular mechanisms underlying each disorder. It also examines how altered expression levels and the distribution of several factors may contribute to their unique clinical characteristics and presentation. Further research is needed to elucidate optimal treatments and preventive measures for these types of aberrant scarring.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".