Rethinking the superficial inferior epigastric artery flap in breast reconstruction: Video demonstration of a rapid, reliable harvest technique
Bibliographic record
Abstract
Abdominal-based autologous free tissue breast reconstruction has undergone significant changes over the past decade. The evolution has focused on limiting morbidity of the donor site. The transition from the transverse rectus abdominus muscle free flap to the muscle-sparing transverse rectus abdominus muscle free flap to the deep inferior epigastric artery perforator free flap has markedly improved abdominal-based autologous breast reconstruction. However, all of these flaps involve an incision through the anterior rectus fascia and potential damage of intercostal motor and sensory nerves. The superficial inferior epigastric artery flap (SIEA) reliably perfuses the ipsilateral hemiabdomen, yet does not violate the fascia or any motor nerves. As a result, the incidence of hernia, abdominal wall weakness and bulging is essentially eliminated. Nevertheless, use of the SIEA flap remains marginal. Vessel size, dissection difficulties and lack of understanding of the relevant anatomy have limited its acceptance. The present article describes a rapid, reliable and safe dissection technique with an algorithm for harvesting the SIEA flap in autologous breast reconstruction.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".