Is Tissue Expansion Worth It? Comparative Outcomes of Skin-preserving versus Delayed Autologous Breast Reconstruction
Bibliographic record
Abstract
Background: The requirement for postmastectomy radiation therapy (PMRT) at the time of mastectomy is often unknown. Autologous reconstruction is preferred in the setting of radiotherapy by providing healthy vascularized tissue to the chest. To maximize mastectomy skin preservation, tissue expander (TE) placement maintains the breast pocket until definitive reconstruction. This study aims to compare outcomes of skin-preserving delayed versus standard delayed autologous breast reconstruction in the setting of PMRT. Methods: A retrospective review of a prospective database was performed of two patient cohorts at a single center between 2006 and 2016. Inclusion criteria were locally advanced breast cancer patients who completed PMRT and free autologous reconstruction. Primary outcomes were major intraoperative and postoperative TE and flap complications. Results: Over 10 years, 241 patients underwent mastectomy and PMRT. Standard delayed autologous breast reconstruction was performed in 131 breasts (non-TE group). Skin-preserving delayed autologous reconstruction was performed in 113 breasts (TE group). The TE group was associated with a higher incidence of intraoperative complications during flap reconstruction (P = 0.002) and had a higher venous thrombosis incidence than the non-TE cohort (P = 0.007). Other major postoperative complications were not significantly different between the two groups. TE patients had 7.5 times higher risk of intraoperative complications and an 18.6% TE loss rate. Conclusions: We identified higher intraoperative flap complications and a high rate of TE loss in patients who underwent skin-preserving delayed autologous breast reconstruction. The benefit of mastectomy skin preservation needs to be weighed against the increased risk of TE loss and higher rates of flap thrombosis.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".