The Conjoined TUGPAP Flap for Breast Reconstruction: Systematic Review and Illustrative Anatomy
Bibliographic record
Abstract
Background: Although abdominally based flaps continue to be the gold standard for autologous breast reconstruction, alternative donor sites are necessary when the abdominal region is unavailable or inadequate for flap harvest. In this case, thigh-based flaps, such as the profunda artery perforator (PAP), transverse upper gracilis (TUG), or newly described TUGPAP, are thought to be reliable with low morbidity and satisfactory cosmesis. The objective of this study was to perform a systematic review of breast reconstruction with PAP, TUG, or TUGPAP, and present anatomy and surgical techniques through illustrative examples. Methods: A systematic review of the literature was conducted using PubMed, Embase, and Cochrane Library. Articles were included if they used a PAP, TUG, or TUGPAP flap for oncologic, traumatic, or congenital breast reconstruction in patients 18 years or older. Results: Forty-nine studies met inclusion criteria. Seven hundred five patients underwent 906 breast reconstructions with 1037 flaps (755 TUG, 230 PAP, and 52 TUGPAP). Mean patient age was 45.9 years. The mean flap weight for TUG, PAP, and TUGPAP flaps were 323.4, 346.9, and 437.0 g, respectively. The most common recipient vessel was the internal mammary artery in 821 flaps. The overall flap survival rate was 97.2% (1008/1037). TUG flaps had a significantly higher recipient and donor complication rate compared with both PAP (recipient: 18.1% versus 7.8%, P = 0.0001; donor: 25.8% versus 7.0%, P < 0.00001) and TUGPAP flaps (recipient: 18.1% versus 2.0%, P < 0.001; donor: 25.8% versus 7.7%, P < 0.01). Conclusion: The TUGPAP flap is a safe and effective alternative for autologous breast reconstruction when the abdominal donor site is unavailable.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".