A Retrospective Study of Breast Reconstruction in Northern Ontario
Bibliographic record
Abstract
Abstract Background: Breast reconstruction is often the final step for women diagnosed with breast cancer. For many in Northern Ontario, lack of access to a plastic surgeon is a significant barrier to breast reconstruction surgery. The aim of this study is to characterize the types of breast reconstruction surgeries performed in Northern Ontario by describing patient demographics and identifying the most commonly performed procedures. Materials and Methods: This is a retrospective review of patient electronic medical records who received reconstructive breast surgery in Thunder Bay between January 2013 and August 2019. Outcome measures included place of residence, clinicopathologic characteristics, complications, timing of reconstruction, type of procedure, and adjunctive procedures. Results: A total of 95 breast reconstruction procedures were performed, 37 patients underwent immediate reconstruction postmastectomy and 58 patients had reconstruction delayed. The average distance traveled by patients was 253.39 km. Of these patients, 36 had tissue expander with implants, 11 each received 1-step implants and autologous flaps with implants, 4 underwent a resection-reduction approach, 13 received a delayed balancing procedure, 9 received fat grafting, 3 received nipple reconstruction, and 8 were referred elsewhere. Some postsurgical complications included infections, seromas, hematomas, tissue expander exposures, T-junction wound breakdown, flap necrosis, implant failure, and blocked drains. Conclusion: Providing information to physicians and patients about patient trends within their population can not only help improve referral rates but also can enhance patient-provider communication and increase patient involvement in care.
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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 | 0.000 |
| 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 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".