Immediate Prepectoral Breast Reconstruction Without Acellular Dermal Matrices: Preliminary Results
Bibliographic record
Abstract
Background: In an effort to shed light on the recent resurgence of prepectoral breast reconstruction and mounting concerns regarding acellular dermal matrices (ADMs), the senior author's experience with non-ADM-assisted immediate prepectoral breast reconstruction and its associated complications are presented. Methods: A retrospective cohort study of the senior author's prepectoral breast reconstruction practice without ADM from November 2019 to May 2021 was carried out. Data regarding patient demographics, oncologic management, and surgical outcomes were recorded. Results: A total of 66 patients (88 breasts) were included, with an average follow-up of 7.8 months (SD: 5.4). Of these, 24 (36.4%) underwent immediate expander and 42 (63.6%) direct-to-implant (DTI) reconstructions. Major complications included nipple-areolar complex necrosis (2%), hematoma (3%), device exposure (2%), and periprosthetic infections (5.7%). The overall rate of implant failure was 5.7%. Minor complications included simple cellulitis (10%) and minor wound dehiscence (4.5%). Increasing implant size ( p < .005) in the DTI cohort and increasing body mass index (BMI) were associated with an increased likelihood of adverse events. Postmastectomy radiation had no effect on surgical complications. Conclusions: The authors hope that in the absence of large, prospective trials, our data demonstrate the safety of immediate prepectoral breast reconstruction without ADM. Our data demonstrate that our algorithm is particularly safe in patients with a low BMI and with an implant size <500cc in DTI reconstruction. Further large prospective studies are required to further support our data in demonstrating that foregoing ADM in immediate prepectoral reconstruction is a safe option.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 | 0.001 |
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 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".