Quantitative Measurement of Hypertrophic Scar: Interrater Reliability and Concurrent Validity
Bibliographic record
Abstract
Research into the pathophysiology and treatment of hypertrophic scar (HSc) remains limited by the heterogeneity of scar and the imprecision with which its severity is measured. The objective of this study was to test the interrater reliability and concurrent validity of the Cutometer measurement of elasticity, the Mexameter measurement of erythema and pigmentation, and total thickness measure of the DermaScan C relative to the modified Vancouver Scar Scale (mVSS) in patient-matched normal skin, normal scar, and HSc. Three independent investigators evaluated 128 sites (severe HSc, moderate or mild HSc, donor site, and normal skin) on 32 burn survivors using all of the above measurement tools. The intraclass correlation coefficient, which was used to measure interrater reliability, reflects the inherent amount of error in the measure and is considered acceptable when it is >0.75. Interrater reliability of the totals of the height, pliability, and vascularity subscales of the mVSS fell below the acceptable limit ( congruent with0.50). The individual subscales of the mVSS fell well below the acceptable level (< or =0.3). The Cutometer reading of elasticity provided acceptable reliability (>0.89) for each study site with the exception of severe scar. Mexameter and DermaScan C reliability measurements were acceptable for all sites (>0.82). Concurrent validity correlations with the mVSS were significant except for the comparison of the mVSS pliability subscale and the Cutometer maximum deformation measure comparison in severe scar. In conclusion, the Mexameter and DermaScan C measurements of scar color and thickness of all sites, as well as the Cutometer measurement of elasticity in all but the most severe scars shows high interrater reliability. Their significant concurrent validity with the mVSS confirms that these tools are measuring the same traits as the mVSS, and in a more objective way.
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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 | 0.038 | 0.092 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".