The Impact of Obesity on Patient Satisfaction with Breast Reconstruction
Bibliographic record
Abstract
BACKGROUND: As the U.S. population becomes increasingly overweight, a growing number of patients with body mass indexes greater than 30 are seeking mastectomy reconstruction. The authors' purpose was to prospectively evaluate the effect of body mass index on patient satisfaction with breast reconstruction. METHODS: Women undergoing first-time breast reconstruction at one of 12 centers in the United States and Canada were surveyed preoperatively and at postoperative year 1. Satisfaction was evaluated with two scales assessing general and aesthetic satisfaction. Using Centers for Disease Control and Prevention criteria, patients were classified as normal weight, overweight, or obese. Logistic regressions evaluated the effects of body mass index on patient satisfaction with expander/implant, pedicled transverse rectus abdominis musculocutaneous (TRAM) flap, and free TRAM flap techniques while controlling for patient age and timing of reconstruction. RESULTS: Data were available for a total of 262 patients. Patient body mass index had a significant effect on aesthetic satisfaction, particularly among patients undergoing expander/implant procedures. Compared with normal weight individuals, obese patients with expander/implants were significantly less satisfied aesthetically (odds ratio, 0.14, p = 0.02). However, there was no significant difference between obese and normal weight patients in aesthetic satisfaction with TRAM flap reconstruction. Finally, body mass index had no significant effects on general satisfaction for either expander/implant or TRAM flap technique. CONCLUSION: Although previous investigators have reported relatively high complication rates and modest aesthetic results for breast reconstruction in overweight and obese women, the authors' study suggests that patient satisfaction with reconstruction is surprisingly high in this population, particularly in cases of autogenous tissue reconstruction.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".