Delayed Two-Stage Breast Reconstruction with Implants: The Authors’ Recent Experience
Bibliographic record
Abstract
BACKGROUND: Presently, breast cancer detection is delayed in Poland and, thus, the only other option for patients is amputation and breast reconstruction (immediate or delayed). Reconstructive methods are based on using the patient's own tissue (pedicled or free myocutaneous flaps) or implants (a tissue expander, which is later exchanged for a prosthesis or an expandable implant). OBJECTIVE: To evaluate the aesthetic results of a delayed two-stage breast reconstruction with the use of implants (expander and prosthesis) in patients who have previously undergone cancer-related mastectomy. METHODS: From 2006 to 2009, 54 patients (34 to 65 years of age) underwent reconstruction at least one year after their mastectomy and adjuvant chemotherapy; three women also received x-ray therapy. All women underwent a two-stage treatment with a tissue expander, which was later exchanged for a prosthesis. RESULTS: Outcomes of the surgery (evaluated by the physician and the patient at least six months after all stages of reconstruction) were found to be very good in 42 patients and good in 12 patients. After amputation and x-ray therapy in two cases, a fistula developed, which necessitated implant removal. CONCLUSIONS: After amputation, breast reconstruction with implants (expander and prosthesis) provides good aesthetic results. The method is mildly burdening to the patient and does not cause severe scarring. Symmetrization of the second breast is often recommended; however, the cost is not covered by the national health system. In principle, earlier x-ray therapy disqualifies the application of implants. Dividing reconstruction into two stages (expander and prosthesis) allows for possible correction of prosthesis placement.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".