Breast reconstruction in Nova Scotia: Rate, trends and influencing factors
Bibliographic record
Abstract
BACKGROUND: During their lifetime, approximately 10% of Canadian women will develop breast cancer. An increased awareness of breast reconstruction in patients undergoing mastectomy appears to have increased the demand for breast reconstructive surgery. OBJECTIVES: To study the rate of breast reconstructive surgeries performed in the province of Nova Scotia to determine whether the breast reconstructive services now offered are adequate to meet the needs of the population of this area. METHODS: The number of breast reconstruction procedures and mastectomies completed in the province of Nova Scotia during the time period of 1992 to 2001 was reviewed. The data were obtained from Maritime Medical Care Incorporated, the provincial medical plan. Information available on patients coded as undergoing breast surgeries was reviewed (n=10,056). The data on the trends and demographics of the Nova Scotia population were obtained from Statistics Canada. The data on incidence, prevalence and trends of breast cancer were obtained from the Canadian Cancer Society and the National Cancer Institute of Canada. RESULTS AND CONCLUSIONS: There is strong evidence of an increasing trend in the number of reconstructive surgeries among the women who underwent mastectomy. The number of breast reconstruction procedures increased 15 fold during the study period. This is mainly attributed to the increased awareness of women undergoing mastectomy and improved education by surgeons, family physicians and breast cancer support groups. Health sector employees must evaluate these trends to determine if the breast reconstructive services currently offered in this region are adequate. Reconstructive surgery was negatively associated with increasing age. Place of residency (urban versus rural) seems to play a role in women's decisions to proceed with breast 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".