The Benefits of Using Platelet-rich Plasma with Dermal Substitutes for Extremity Posttraumatic Skin Defects: A Short-term Outcome
Bibliographic record
Abstract
Background: Skin injuries are very common. Skin grafting is an ongoing wound management procedure. The artificial dermis, PELNAC, has been considered in the treatment of several acute and chronic skin injuries. Platelet-rich plasma (PRP) is blood plasma with a platelet count higher than the baseline. It is presumed to act in a synergetic pattern to promote the healing of wounds. This study was conducted to assess the potential benefit of adding PRP to PELNAC as adjuvant therapy in treating posttraumatic skin. Methods: In this study, adult patients who were admitted to the hospital with extremity traumatic skin and soft tissue defects with exposed bare bone, exposed tendons, or exposed cartilage in the period between October 2019 and March 2021 were allocated to either being managed with dermal substitute (PELNAC) together with PRP (group I) or PELNAC alone (group II). Results: Patients in group I showed a higher mean graft take rate and a lower mean time for neovascularization of the acellular dermal matrix, with a statistically highly significant difference. The Vancouver Scar Scale values showed no significant difference in either group. The PRP-treated group showed statistically significant shorter hospital stays. Conclusions: The addition of PRP to the treatment protocol showed better outcomes in terms of graft take rate, time for neovascularization of acellular dermal matrix, and length of hospital stay, with no side effects. The present study findings emphasize the promising outcome of PRP in addition to the standard treatment of complex wounds to achieve rapid and safe healing.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".