Comparison of the wound healing and complications of zipper type closure adhesive tape and stapler for surgical wound suture: A randomized control, single‐centre, open‐label trial
Bibliographic record
Abstract
Xkin closure is a newly developed medical suture device for lacerations and surgical wounds that can reduce scarring, pain and the risk of infection compared with conventional sutures or staplers. A randomized controlled study was performed to compare the wound healing effects and complications of Xkin closure with stapler closure. Fifty patients who underwent robot-assisted radical prostatectomy for prostate cancer were randomly assigned. Only the wound above the navel, which was extended to take out the prostate was targeted. The wound was examined at 2, 6 and 12 weeks after surgery, and the modified Vancouver Scar Scale (mVSS), scar height and side effects were assessed with a 3D skin analyser. Forty-six patients (23 Xkin, 23 Stapler) were analysed. The mVSS scores, vascularity and pliability were significantly lower in the Xkin group compared with the stapler group at the 12-week follow-up. No significant differences in the maximum peak and depth of the scars were detected between the two groups using 3D photographs at 12 weeks. Xkin is an effective wound closure method for improving scar outcomes. This method is expected to be widely used for surgical wounds and lacerations caused by trauma in daily life.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".