The Effect of Incision Choice On Outcomes of Nipple-Sparing Mastectomy Reconstruction
Bibliographic record
Abstract
INTRODUCTION: The indications for nipple-sparing mastectomy (NSM) are broadening as more breast surgeons appreciate the utility of preserving the nipple-areolar complex. A number of incision locations are available to the mastectomy surgeon, including inframammary, lateral and periareolar approaches. The present study investigated the effect of these three incisions on reconstructive outcomes; specifically, nipple necrosis. METHODS: A single-centre, retrospective review of 37 breast NSM reconstructions treated with immediate tissue expander reconstruction with acellular dermis between 2007 and 2008 was performed. The primary outcome was the incidence of nipple necrosis associated with periareolar, lateral and inframammary incisions. Secondary outcomes were the effects of radiation, chemotherapy and breast size on nipple necrosis. RESULTS: Thirty-seven breast procedures performed on 20 patients were included in the present study. Periareolar incisions were used in 21 cases, lateral incisions in 14 and inframammary incisions in two. The periareolar incision was associated with a significantly higher incidence of nipple necrosis compared with lateral or inframammary incisions (38.1% versus 6.3%, P=0.028). Patients receiving breast radiation (45.5% versus 15.4%, P=0.066) and those with larger breast size (540.4 g versus 425.7 g, P=0.130) also demonstrated a modest trend toward an increased rate of nipple necrosis. CONCLUSION: The periareolar incision results in a higher rate of nipple necrosis following NSM and immediate tissue expander breast reconstruction. Using the lateral or inframammary incision reduces the incidence of nipple necrosis and may help improve overall reconstructive and cosmetic outcomes.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".