Tension Reduction With Force Modulating Tissue Bridges Reduces Wounds in Breast Surgery
Bibliographic record
Abstract
BACKGROUND: Tension on healing wounds increases the risk of dehiscence and poor or pathologic scar formation. Force modulating tissue bridges (FMTBs) represent a new class of wound closure and support devices designed to offload tension on healing wounds to improve wound healing and scar outcomes. OBJECTIVES: The study was undertaken to assess the efficacy of FMTBs to reduce the risk of wound healing complications in elective breast surgery. METHODS: One hundred twenty-two consecutive patients undergoing bilateral aesthetic breast surgery underwent intraoperative placement of FMTBs on the vertical limb closure site. A matched case-control cohort of 121 consecutive patients was established for comparison. Wounds were considered significant if larger than 3 mm in diameter. The primary outcome of breast wounds >3 mm was reported with a relative risk, and all outcomes were framed with number needed to treat. RESULTS: The control and intervention cohorts had similar demographics, comorbidities, type of operation, and incision pattern utilized. Within the FMTB group, 96.7% (n = 118) patients completed treatment per protocol. Significant wounds occurred in 1.7% (n = 2) of patients in the tissue bridge vs 15.2% (n = 19) in controls on a per patient/per protocol basis (89% reduction, P < .001). Statistically significant improvements were maintained on sensitivity analyses with intention to treat, even when minor wounds were included. There were no complications noted related to FMTBs. CONCLUSIONS: FMTBs are safe and highly effective at reducing the risk of wound formation in elective breast surgery. Results are consistent with sensitivity analyses based on clinical and methodological factors. Further research will assess long-term scar outcomes.
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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 | 0.000 |
| 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 | 0.000 |
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".