Principles of Breast Re-Reduction: A Reappraisal
Bibliographic record
Abstract
BACKGROUND: This article examines outcomes following breast re-reduction surgery using a random pattern blood supply to the nipple and vertical scar reduction. METHODS: A retrospective review was conducted of patients who underwent bilateral breast re-reduction surgery performed by a single surgeon over a 12-year period. Patient demographics, surgical technique, and outcomes were analyzed. RESULTS: Ninety patients underwent breast re-reduction surgery. The average interval between primary and secondary surgery was 14 years (range, 0 to 42 years). The majority of patients had previously undergone primary breast reduction using an inferior pedicle [n = 37 (41 percent)]. Breast re-reduction surgery was most commonly performed using a random pattern blood supply, rather than recreating the primary pedicle [n = 77 (86 percent)]. The nipple-areola complex was repositioned in 60 percent of patients (n = 54). The mean volume of tissue resected was 250 g (range, 22 to 758 g) from the right breast and 244 g (range, 15 to 705 g) from the left breast. Liposuction was also used adjunctively in all cases (average, 455 cc; range, 50 to 1750 cc). Two patients experienced unilateral minor partial necrosis of the areolar edge but not of the nipple itself (2 percent). CONCLUSIONS: Breast re-reduction can be performed safely and predictably, even when the previous technique is not known. Four key principles were developed: (1) the nipple-areola complex can be elevated by deepithelialization rather than recreating or developing a new pedicle; (2) breast tissue is removed where it is in excess, usually inferiorly and laterally; (3) the resection is complemented with liposuction to elevate the bottomed-out inframammary fold; and (4) skin should not be excised horizontally below the inframammary fold. CLINICAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, IV.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".