Preferences in Choosing between Breast Reconstruction Options: A Survey of Female Plastic Surgeons [Outcomes Article]
Bibliographic record
Abstract
BACKGROUND: Female plastic surgeons are well suited to make a personal choice regarding breast reconstruction options, based on their knowledge of the actual procedures and first-hand experience with results. The authors surveyed this group to elicit their personal views on various modalities of breast reconstruction and to ascertain which types of reconstruction they would choose if faced with such a decision. METHODS: All board-certified female plastic surgeons in the United States and Canada were surveyed by means of e-mail. This survey included questions regarding basic demographic and practice data. Respondents were requested to rank desired methods of reconstruction for themselves and to cite reasons for these choices. RESULTS: A total of 435 surveys were sent: 350 were delivered (85 had invalid e-mail addresses), and 143 were returned (response rate, 41 percent). Overall, 66 percent of respondents chose implant-based reconstruction, 25 percent chose autologous reconstruction, and 9 percent chose no reconstruction. Respondents selecting autologous reconstruction cited cosmetic outcome as the most important factor considered in 47 percent of cases, compared with 14 percent of those choosing implant-based breast reconstruction (p = 0.0001). Invasiveness of the procedure/recovery time was cited as the most important factor by 83 percent of those surgeons opting for no breast reconstruction and by 51 percent of those choosing implant-based breast reconstruction (p = 0.0175). CONCLUSIONS: Board-certified female plastic surgeons exhibit a strong desire to pursue implant-based breast reconstruction over autologous reconstruction. When it was chosen, autologous reconstruction was felt to offer improved aesthetic outcomes. When making such a decision, patients can use female plastic surgeons as a resource for information, thus helping them to make an informed decision.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".