Reduction Mammaplasty for Macromastia in Adolescents: A Systematic Review and Pooled Analysis
Bibliographic record
Abstract
BACKGROUND: Reduction mammaplasty for macromastia is one of the most common operations performed by plastic surgeons. There remains hesitancy in operating on adolescents, as there is ongoing debate about breast regrowth and potential impact on breastfeeding. The goal of this study was to analyze these concerns by reviewing the current literature. METHODS: A systematic review of MEDLINE, Scopus, and Google Scholar was conducted using the following terms: "breast reduction" or "mammaplasty" or "breast reconstruction" and "adolescent" or "youth" or "pediatric" or "child" or "teen." Primary outcomes were success of breastfeeding after the procedure and procedure-related complications. RESULTS: Twenty-three studies (87 percent retrospective), consisting of 2926 patients with preoperative cup sizes of C to KK (mean, DDD), met inclusion criteria. Mean age at the time of surgery ranged from 16 to 21 years, with the youngest patient being 12 years old. The overall complication rate was 27.3 percent (95 percent CI, 14.4 to 42.5 percent). Minor complications (22.8 percent; 95 percent CI, 10.2 to 38.5 percent) were more common than major (4.2 percent; 95 percent CI, 1.6 to 7.9 percent). Eighteen percent of patients (95 percent CI, 2.2 to 43.8 percent) reported regrowth of their breast tissue postoperatively, with 2.7 percent (95 percent CI, 0.9 to 5.5 percent) undergoing a second revision mammaplasty. Fifty-three percent of patients (95 percent CI, 36.0 to 69.3 percent) did not attempt breastfeeding. Of those who attempted, 55.1 percent (95 percent CI, 34.4 to 74.9 percent) were successful. CONCLUSIONS: Prospective data are lacking. Patient counseling should focus on encouraging a trial of breastfeeding, despite surgical history. One-fifth of adolescent patients may notice breast regrowth postoperatively; however, the amount of regrowth is likely small and unlikely to reexacerbate symptoms, as the rate of revision surgery is small.
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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 | 0.009 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.016 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".