DEVELOPMENT OF NONINVASIVE AND QUANTITATIVE METHODOLOGIES FOR THE ASSESSMENT OF CHRONIC ULCERS AND SCARS IN HUMANS
Bibliographic record
Abstract
Chronic ulcers are a significant and common cause of morbidity and mortality worldwide. They disrupt the epidermis and dermis, resulting in a loss of barrier function. Keloids and hypertrophic scars (benign cutaneous tumors) represent an abnormal healing response. These fibroproliferative disorders are characterized by an overabundance of collagen and accumulation of extracellular matrix due to an imbalance between synthesis and degradation, culminating in excessive scarring. The objectives of this study were to evaluate and compare noninvasive biophysical methods for the measurement of outstanding quantitative parameters of scars and chronic ulcers, and to establish correlations between the parameters measured and the results of conventional subjective clinical evaluations. The development of new technologies, based on ultrasonography and laser Doppler, makes possible new dermatological evaluation methods. Fifteen patients (6 females and 9 males) with 15 chronic ulcers (4 diabetic ulcers, 10 venous ulcers and 1 pressure ulcer) and 30 patients (19 females and 11 males) with 30 scars (25 hypertrophic and 5 keloids) were included in this study. Clinical evaluation was performed by a dermatologist, an aesthetic surgeon and an endocrinologist. Biophysical measurements were used to assess local blood flow by laser Doppler flowmetry (Moor DRT4), thickness and echogenicity by high frequency ultrasonography (20 MHz, Dermascan C) and ulcer linear dimensions by image analysis. Our results show that blood flow within the ulcers and scars was higher than within normal skin. Also, skin thickness of chronic ulcers was decreased when compared to normal skin; the thickness of hypertrophic scars, but not of keloids, was increased in comparison to normal skin, and presented the possibility of measuring wound and scar surfaces with precision. In summary, this pilot study established the feasibility of measuring various biophysical parameters and adapted their potential utility to research on wounds.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".