Factors Influencing the Rate of Post-Mastectomy Breast Reconstruction in a Canadian Teaching Hospital
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Post-mastectomy breast reconstruction (PMBR) improves psychosocial well-being, quality of life, and body image. Reconstruction rates vary widely (up to 42% in the United States), but the few Canadian studies available report rates of 3.8% to 7.9%. We sought to evaluate the current state of breast reconstruction in 1 Canadian teaching hospital and factors determining patients' access to reconstruction. METHODS: We performed a retrospective chart review of all patients with breast cancer undergoing mastectomy alone or mastectomy and reconstruction at a Canadian hospital between 2010 and 2013. We calculated rates of breast reconstruction and compared patient characteristics between the 2 groups, and then performed a multiple logistic regression to determine factors increasing the odds of receiving breast reconstruction. RESULTS: A total of 152 patients underwent 154 total or modified radical mastectomies. We obtained a rate of PMBR of 21%, 14% immediate reconstruction, and 8% delayed. Statistical analysis showed that compared to patients with mastectomy alone, patients who received PMBR were significantly younger, with a larger percentage having bilateral mastectomies, non-invasive breast cancer, and residing further from the hospital. Patients less than 50 years old and those with bilateral mastectomies had significantly greater odds of having a reconstruction. CONCLUSIONS: Our Canadian tertiary care institution has a high volume of breast surgery and an active breast reconstruction team. However, the rate of immediate reconstruction remains low compared to similar centers in the United States. We recommend a united effort to increase awareness regarding PMBR and address common misconceptions hindering patients' access to breast reconstruction. LEVEL OF EVIDENCE: Epidemiologic study, Level III.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it