Gynecomastia: Evolving Paradigm of Management and Comparison of Techniques
Bibliographic record
Abstract
BACKGROUND: Since 1997, the authors have used a minimally invasive technique for the management of gynecomastia using ultrasound-assisted liposuction and the arthroscopic shaver to remove breast tissue through a remote incision. This technique has allowed for a consistent, refined, "unoperated" postoperative appearance in this patient population. This study analyzes the outcomes of this procedure and compares the procedure against established techniques. METHODS: A retrospective study was performed on all patients who underwent surgery for gynecomastia at the authors' institution between January of 1988 and October of 2007. A total of 227 patients were divided into four groups: group 1, open excision only (n = 45); group 2, open excision plus liposuction (n = 56); group 3, liposuction only (n = 50); and group 4, liposuction plus arthroscopic shaver (n = 76). Medical records and photographs were used to compare groups for complications and results. RESULTS: Complications using the liposuction plus arthroscopic shaver technique included seroma (n = 2), hematoma (n = 1), scar revision (n = 1), and skin buttonhole from the arthroscopic shaver (n = 1). There was no difference between groups in the overall incidence of complications (p < 0.20) or the need for reoperation (p < 0.325). Results were scored on a scale of 1 (poor) to 5 (excellent). Group 4 (liposuction plus arthroscopic shaver) had the overall highest mean score, with statistical significance between group 2 (open excision plus liposuction) and group 4 (p < 0.0001). CONCLUSION: Arthroscopic mastectomy for gynecomastia is a safe and effective technique, with excellent cosmetic results and an acceptable complication rate.
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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 | 0.018 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".