Preliminary Results Supporting the Bacterial Hypothesis in Red Breast Syndrome following Postmastectomy Acellular Dermal Matrix– and Implant-Based Reconstructions
Bibliographic record
Abstract
Acellular dermal matrices have become a mandatory tool in reconstructive breast surgery. Since their introduction, they have been considered to be nonreactive and nonimmunogenic scaffolds. However, some patients who undergo implant-based breast reconstruction with acellular dermal matrices develop postoperative cutaneous erythema overlying their matrices, a condition commonly referred to as red breast syndrome. The aim of this study was to gain a better understanding of this phenomenon. An analysis was conducted on consecutive patients who underwent acellular dermal matrix- and implant-based breast reconstructions and developed red breast syndrome that was treated surgically between April of 2017 and June of 2018 at the authors' institution. During surgery, 1-cm specimens of acellular dermal matrix were sampled and analyzed by scanning electron microscopy. Observations were charted to score and record the presence and thickness of biofilm, and for identification of bacteria. These measurements were performed using Adobe Photoshop CS6 Extended software. Six postmastectomy breast reconstruction patients were included, all with AlloDerm Ready-to-Use-based reconstructions. All specimens were colonized by various bacteria ranging from Gram-negative bacilli to Gram-positive microorganisms. Biofilm was present in all studied specimens. The cause of skin erythema overlying acellular dermal matrix grafts, and the so-called red breast syndrome, may be related to contamination with various bacteria. Although contamination was omnipresent in analyzed samples, its clinical significance is variable. Even if acellular dermal matrix-based reconstructions are salvaged, this could come at the price of chronic local inflammation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".