Breast reconstruction and radiation therapy: A Canadian perspective
Bibliographic record
Abstract
BACKGROUND: When and how best to perform breast reconstruction in the setting of radiation therapy is a much debated topic. OBJECTIVE: To investigate the approaches that Canadian plastic surgeons are taking to breast reconstruction in patients who require or may require radiation therapy. METHODS: In April 2009, a survey invitation was sent to Canadian plastic surgeons via e-mail. Survey responses were collected over a two-month period. RESULTS: Of the 307 invitees, 90 surgeons responded, of whom 76 met the inclusion criteria. Most surgeons (66%) do not perform immediate reconstruction in patients who require postmastectomy radiation. Most respondents (64%) perform immediate reconstructions for patients whose need for radiation is uncertain at the time of mastectomy. Expander and implants is their preferred option, followed by free transverse rectus abdominis myocutaneous (TRAM) flap. Thirty-five per cent use the delayed immediate technique in these cases. Twenty-one per cent are unfamiliar with the delayed-immediate technique. For delayed reconstruction of the irradiated patient, the pedicled TRAM is the most common choice. CONCLUSIONS: The reconstructive options are increasing for patients who may need postmastectomy radiation. The use of the delayed immediate technique could increase as physicians gain more knowledge of the technique.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 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".