Clinical effectiveness of double-layer artificial dermis transplantation repairing hand wounds with limited bone and tendon exposure
Bibliographic record
Abstract
Objective: Our objective was to investigate the clinical efficacy of double-layer artificial dermis transplantation in repairing hand wounds with limited bone and tendon exposure. Methods: This study involved 46 patients with limited bone and tendon exposure in the hand who were admitted to Dongguan Songshan Lake Central Hospital between January 2022 to January 2024. The patients were randomly divided into two groups: observation and control (N=23/group). The observation group underwent double-layer artificial dermis transplantation, whereas the control group received conventional treatment. The two groups were compared in terms of the overall wound condition, infection rate, granulation tissue growth time, wound healing time, pain scores, scar scores, and hand function recovery scores. Results: In the observation group, wound swelling and exudation were significantly reduced post-treatment, while no wound infections were observed. In contrast, the control group had significantly more severe wound swelling and exudation, with an infection rate of 13.04%. The observation group had shorter average times for granulation tissue growth and wound healing. Pain scores at days 3, 7, and 14, Vancouver Scar Scores (VSS) and Arm, Shoulder, and Hand Disability Scores (DASH) at six months were significantly lower in the observation group (P<0.05). Conclusion: The double-layer artificial dermis could effectively reduce the wound's inflammatory response, control infections, alleviate patient pain, accelerate granulation tissue growth and shorten the wound healing time. Furthermore, it could reduce scar tissue formation and restore the hand's functionality.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".