Matriderm dermal substitute in the treatment of post traumatic hand’s fingertip tissue loss
Bibliographic record
Abstract
Abstract Introduction Treatment of fingers tissue loss is particularly challenging as it often necessitates advanced reconstructive techniques such as flaps or grafts, with esthetic and functional results that are not always as good as hoped for, with long healing times. Recently, along with tissue engineering development, numerous types of dermal substitute have been commercialized, with promising possibilities of treatment in finger tissue loss. In the author's unit, Matriderm® is the most commonly used dermal substitute. As described by the manufacturer, this scaffold is designed to be covered with a split‐thickness skin graft. In using a two‐step procedure, the authors realized that in most cases of fingertips injuries, at three weeks follow‐up, the wound appeared in an advanced state of healing, which permitted to avoid grafting. Material And Methods Between October 2017 and October 2018, 27 fingers have been included in this study. Patients have been divided in two groups: those treated with Matriderm® alone (15 fingers) and those who had a skin graft three weeks after the first surgery (12 fingers). At the 6‐month follow‐up, authors evaluated the esthetic results with the Vancouver Scar Scale (VSS), the functional results with Quick Disability of the Arm, Shoulder and Hand (qDASH) score, and sensibility by the mean of two‐point discrimination test (2‐PD). Results All outcomes were overlapping in patients treated with or without skin graft: mean VSS was 2.3, mean qDASH was 13.3, and mean 2‐PD was 7.7 mm. Conclusions The results obtained allow to consider Matriderm®, used also without skin graft coverage, as a valid solution for treatment of fingertip tissue loss.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".