Commentary on: Vertical Reduction Mammaplasty Utilizing the Superomedial Pedicle: Is It Really for Everyone?
Bibliographic record
Abstract
In “Vertical Reduction Mammaplasty Utilizing the Supero-medial Pedicle: Is It Really for Everyone?,” Dr Neaman and his coauthors review a cohort of 290 patients (558 breasts) who underwent a vertical-style superomedial pedicle reduction mammaplasty and try to show that it is safe and effective for a wide range of patients with symptomatic macromastia. I appreciate the opportunity to comment on this article to give my perspective, gained after almost 30 years in practice. For the first 10 years of my practice, I used mainly an inferior pedicle, inverted-T-type breast reduction and, although the results were acceptable, I agreed with Madeleine Lejour1 that we could be striving for improvement. I have learned a lot by analyzing my experience since then, with over 2000 “vertical” breast reductions performed using superior, lateral, and medial pedicles. The word “vertical” is often used to describe a particular procedure, but I believe we should instead be separating out how we design the pedicle, the nature of the parenchymal resection, and the skin resection pattern. The “Wise pattern” is a term often used to describe an inverted-T, inferior pedicle breast reduction, but Robert Wise2 originally described only a skin resection design adapted from a brassiere pattern. I still occasionally apply a Wise pattern for the skin redraping when I use a superomedial pedicle in large breast reductions or in massive weight-loss patients. I always, on the other hand, apply a Wise pattern for the parenchymal design—not for what is removed, but for what is left behind (Figure 1). Figure 1. (A) The pattern as originally described by Robert Wise was not just the keyhole opening but was a skin pattern design adapted from a brassiere pattern. (B) The use of the Wise pattern for the parenchyma instead of the skin is an excellent way to remove …
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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 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".