The Use of AlloDerm in Postmastectomy Alloplastic Breast Reconstruction: Part I. A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Postmastectomy alloplastic breast reconstruction is a common procedure that continues to evolve. Increasingly, AlloDerm is being used in both direct-to-implant and two-stage breast reconstruction. The objective of this systematic review was to summarize the outcomes from studies describing this use of AlloDerm, and to compare outcomes to those from studies reviewing non-AlloDerm alloplastic reconstruction. METHODS: A computerized search was performed across multiple databases. Studies involving patients undergoing alloplastic breast reconstruction with AlloDerm were included. A systematic review was performed to include randomized controlled trials, comparative observational studies, noncomparative observational studies, and case series. RESULTS: A systematic review of the literature revealed 14 studies that satisfied inclusion criteria. Both acute and long-term complication rates were obtained. No objective validated outcomes were reported. Ninety-three percent of included studies were level IV evidence. Complication rates were as follows: infection, 0 to 11 percent; hematoma, 0 to 6.7 percent; seroma, 0 to 9 percent; partial flap necrosis, 0 to 25 percent; implant exposure with removal, 0 to 14 percent; implant exposure with salvage, 0 to 4 percent; capsular contracture, 0 to 8 percent; and rippling, 0 to 6 percent. No study included a cost analysis. CONCLUSIONS: Complications using AlloDerm are comparable to those of non-AlloDerm alloplastic reconstructions. AlloDerm appears to confer a low rate of capsular contracture. A formal analysis is required to determine AlloDerm's cost effectiveness in use for direct-to-implant reconstructions. In addition, a randomized controlled trial comparing AlloDerm use to conventional two-stage reconstruction is currently absent from the literature.
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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 | 0.006 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".