Single-stage Latissimus Dorsi Breast Reconstruction Using Spectrum Devices: Outcomes and Technique
Bibliographic record
Abstract
BACKGROUND: Latissimus dorsi (LD) flap is a workhorse flap in breast reconstruction. Despite many advantages, the primary criticism of this flap is the requirement of a second surgery to exchange expansion devices for permanent implants. This study reports a single-stage reconstruction and outcomes wherein Spectrum devices (Mentor, Irving, TX), which serve as expanders and permanent implants, are used, and expansion ports are removed under local anesthetic. METHODS: A retrospective chart review of all patients undergoing LD flap reconstruction with Spectrum device by a single surgeon at a single center during a 10-year period was performed. All patients, unilateral/bilateral, immediate/delayed were included. Details of implants, surgical procedure(s), and follow-up visits were assessed for patient outcomes. RESULTS: In total, 41 patients and 56 breasts were included. Of the total patients, 58.5% retained the Spectrum device and had the expansion port removed under local anesthetic. An estimated 6 major complications occurred (14.6%), requiring return to the operating room: 3 patients required a capsulectomy, 1 a capsulotomy/implant repositioning, one had loss of implant (infection), and 1 had venous congestion of the flap. Eleven minor complications occurred (26.8%): 5 seromas (3 at the breast site, 2 at the donor site), 3 delayed wound healings (2 at donor site, 1 at breast site), 1 mastectomy flap necrosis, 2 infections (1 at each breast site, 1 at donor site). CONCLUSIONS: This study provides details of a single-stage LD flap with Spectrum device breast reconstruction that can be considered when performing an LD reconstruction. This technique is efficient and safe with comparable complication profile.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".