Pelnac® artificial dermis assisted by vacuum sealing drainage for treatment of severe avulsion injuries of the fingers
Bibliographic record
Abstract
PURPOSE: This study aimed to evaluate the outcomes of Pelnac assisted by vacuum sealing drainage in managing severe avulsion injuries of the fingers. METHODS: This prospective study was conducted from May 2017 to September 2023, involving 12 consecutive patients with severe avulsion injuries of the fingers. Patients underwent single-stage or two-stage procedures employing Pelnac assisted by vacuum sealing drainage (VSD) for the management of severe avulsion injuries of the fingers. Post-operative follow-up was routinely scheduled, and aesthetic and functional outcomes, sensory recovery, complications were recorded. RESULTS: Twelve patients were included in the analysis, consisting of 9 males and 3 females, with a mean age of 30.6 ± 11.0 years. All patients presented with severe damage to tendons and deep tissues, as well as varying degrees of bone exposure and injury, with average defect area of 36.9 cm² (range, 11 to 180 cm²). At the final follow-up (mean, 14 months; range, 12 to 29 months), the average score on the Fingertip Injuries Outcome Score (FIOS) was 14.3 (SD 3.9, range 10 to 22), with 6 patients achieving excellent result, 4 classified as good and 2 as fair. Patients reported an average satisfaction score of 74.0 (SD 11.6; range 51 to 94) regarding the aesthetic appearance. The average score on the Vancouver Scar Scale score was 2.3 (SD 2.1, range 1.0 to 7.4). Ten patients reported normal or near-normal sensation, while 2 patients experienced slight sensory loss. The average score on the Disabilities of the Arm, Shoulder, and Hand (DASH) questionnaire was 13.2 (SD 8.5, range 0 to 47). No infections or hematomas were reported during hospitalization or after discharge. CONCLUSION: Pelnac, assisted by VSD, proved to be an effective approach for managing severe avulsion injuries of the fingers. This approach can be considered as a viable alternative for addressing severe injuries or complex wound conditions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".