A Randomized Controlled Trial Comparing Alloderm-RTU with DermACELL in Immediate Subpectoral Implant-Based Breast Reconstruction
Bibliographic record
Abstract
BACKGROUND: The effectiveness of different acellular dermal matrices (ADM) used for implant-based reconstruction immediately following mastectomy is an important clinical question. A prospective randomized clinical trial was performed to evaluate the superiority of DermACELL over Alloderm-RTU in reducing drain duration. METHODS: Patients undergoing mastectomy with subpectoral immediate and permanent implant-based breast reconstruction were randomized to Alloderm-RTU or DermACELL. The primary outcome was seroma formation, measured by the duration of postoperative drain placement. Secondary outcomes included: post drain removal seroma aspiration, infection, redbreast syndrome, wound dehiscence, loss of the implant, and unplanned return to the operating room. RESULTS: = 0.16), with a trend towards longer duration in the Alloderm-RTU group (1.6 days; 95%CI, 0.7 to 3.9). The overall rate of minor and major complications were statistically similar between the two groups; although patients with Alloderm-RTU had 3 times as many infections requiring antibiotics (7.9% vs. 2.5%) with a risk difference of 5.4 (95%CI -4.5 to 15.2), and twice as many unplanned returns to the operating room (15.8% vs. 7.5%) with a risk difference of 8.3 (95% CI -5.9 to 22.5) as DermACELL. CONCLUSION: This is the first prospective randomized clinical trial comparing the two most commonly used human-derived ADMs. There was no statistically significant difference in drain duration, minor, or major complications between DermACELL over Alloderm-RTU in immediate subpectoral permanent implant-based breast reconstruction post-mastectomy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".