The Absorbable Dermal Staple Device: A Faster, More Cost-Effective Method for Incisional Closure
Bibliographic record
Abstract
Background: Closure with dermal sutures is time consuming, may increase the risks of inflammation and infection secondary to foreign body reaction, exposes the surgeon to possible needlestick injuries, and has variable cosmetic outcomes depending on each surgeon's technique. The absorbable INSORB dermal stapler is hypothesized to be faster and more cost effective than sutures for dermal layer closures and provides a safer and more consistent result. Methods: This is a prospective, randomized, controlled study. Patients undergoing bilateral breast reconstruction with tissue expanders had one incision randomized to dermal closure with absorbable dermal staples. The contralateral side was closed with dermal sutures. During the expansion period, wounds were assessed by a blinded plastic surgeon using the 13-point Vancouver Scar Scale. At the time of implant exchange, both scars were excised and examined for histologic signs of inflammation. Results: Eleven patients (22 incisions) were enrolled in the study. The dermal stapler was four times faster than standard suture closure, reducing closure time by 10.5 minutes (p ≤ 0.001). Overall cost savings with the dermal stapler was $220 per case. In the early postoperative period, the dermal stapler had a higher Vancouver Scar Scale score than sutures because of superior wound eversion, a beneficial characteristic for wound healing. By 4 months postoperatively, no significant difference in scar scores was found between interventions. At 6 months, histologic analysis suggested decreased inflammatory cell invasion of the dermal stapler-closed scar. Conclusion: Closure using the absorbable dermal stapler can be performed significantly faster than standard suture closure techniques, allowing for a more cost-effective incisional closure with equivalent cosmetic results.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".