Textured versus Smooth Tissue Expanders: A Comparison of Complications in 3526 Breast Reconstructions
Bibliographic record
Abstract
BACKGROUND: Increased understanding of breast implant-associated anaplastic large-cell lymphoma has led to a shift away from textured breast devices. A few small studies have compared the complication rates of textured and smooth tissue expanders (TEs). The aim of this study was to compare complication profiles in patients undergoing two-stage postmastectomy breast reconstruction with either textured or smooth TEs. METHODS: The authors performed a retrospective review of female patients who underwent immediate breast reconstruction with textured or smooth TEs from 2018 to 2020 at their institution. Rates of seroma, infection/cellulitis, malposition/rotation, exposure, and TE loss were analyzed in the overall cohort and subgroups undergoing prepectoral and subpectoral TE placement. A propensity score-matched analysis was used to decrease the effects of confounders comparing textured and smooth TEs. RESULTS: The authors analyzed 3526 TEs (1456 textured and 2070 smooth). More frequent use of acellular dermal matrix, SPY angiography, and prepectoral TE placement was noted in the smooth TE cohort ( P < 0.001). Univariate analysis suggested higher rates of infection/cellulitis, malposition/rotation, and exposure in smooth TEs (all P < 0.01). Rates of TE loss did not differ. After propensity matching, no differences were noted in infection or TE loss. Prepectoral smooth expanders had increased rates of malposition/rotation. CONCLUSIONS: TE surface type did not affect rates of TE loss, although increased rates of expander malposition were noted in the smooth prepectoral cohort. Further research is needed to examine breast implant-associated anaplastic large-cell lymphoma risk with temporary textured TE exposure to improve decision-making. CLINICAL QUESTION/LEVEL OF EVIDENCW: Therapeutic, III.
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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 | 0.000 |
| 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 | 0.001 |
| 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 | 0.000 |
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".