Nipple-Sparing Mastectomy via Inframammary Fold: Reconstructive Red Flags
Bibliographic record
Abstract
Background: Nipple-sparing mastectomy (NSM) is a technically feasible and oncologically sound option for patients who meet eligibility criteria. Inframammary fold (IMF) incision results in a well-hidden scar and enhanced final aesthetic result. While oncologic eligibility criteria have been well established, reconstructive criteria are less defined. We report Moffitt Cancer Center's (MCC) outcomes with IMF incision for NSM and immediate reconstruction, and factors associated with increased complication rate.Methods: IRB approved retrospective cohort study of patients who underwent NSM through an IMF approach with immediate reconstruction at MCC from 2006-2013 was conducted. Analysis included patient demographics, tumor characteristics, ancillary treatment, reconstructive method, and nipple and skin flap necrosis. A literature review was performed to compare outcomes with other types of incisions.Results: 115 patients met inclusion criteria, representing 199 breasts. The average age was 48.1 (range 18-74). The two main complication categories evaluated were nipple necrosis (8%) and skin flap necrosis (10.6%). Older age demonstrated a significant relationship with skin flap necrosis (p=0.0155) and overall complications (p=0.0492). Complication rate was significantly higher in the cancer side vs. prophylactic side in patients who underwent bilateral mastectomies (p=0.0088). Factors with trends related to increased skin flap necrosis included increased mastectomy specimen weight (p=0.0704), smoking (p=0.0726), and significant comorbidities (p=0.0665).Conclusion: Our institution's results substantiate that NSM through an IMF approach with immediate reconstruction is a viable option. Recognized risk factors such as age, laterality, breast weight, smoking history, and comorbidities associated with increased complications should be considered when determining patient selection for reconstruction.
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 | 0.001 |
| 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".