Donor-site closure using absorbable dermal staple for deep inferior epigastric artery perforator flaps: its efficacy and cosmetic outcomes
Bibliographic record
Abstract
BACKGROUND: Surgeons tend to pay less attention to the donor site during breast reconstruction using deep inferior epigastric artery perforator flaps because attention is focused on microanastomosis and breast shaping. Therefore, donor site closure is typically performed by a secondary operator. We present consistently reduced operative times and improved scar quality using an absorbable dermal staple. METHODS: Retrospective review was performed on 25 patients who were either standard suture controls (group I, n = 15) or received absorbable staples (group II, n = 10). Mean age, flap size, whole operative time, and length of hospital stay were collected. The donor site scar was evaluated by three plastic surgeons in a blinded manner using the modified Vancouver scar scale 6 months after surgery. Data were analyzed with the independent t test, and a p value ≤0.05 was considered significant. RESULTS: No differences were detected between the groups for age, harvested flap size, or length of hospitalization. However, operative time was significantly longer in group I (1.07 ± 0.24 min/cm(2)) than that in group II (0.86 ± 0.16 min/cm(2), p = 0.015). The total scar assessment score was significantly lower in group II (3.8 3 ± 1.30) than that in group I (5.27 ± 1.83, p = 0.043). CONCLUSIONS: Absorbable dermal stapling reduced operative time, compared to that of traditional suturing. In addition, scar quality from absorbable dermal staples was superior to that resulting from traditional sutures. LEVEL OF EVIDENCE: II.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".