The U-Turn Tournedos (UTT) Flap: A Technical Surgical Evolution for Deep Complex Calvarial Defects
Bibliographic record
Abstract
ABSTRACT: Patients treated for complex oncological calvarial defects are at a higher risk of severe complications (38%): infection, meningitis, dehiscence, and hardware/brain exposure. The patient cohorts at our center have led to the development of the "U-Turn" technical (UTT) addition of our previously reported turnover "tournedos" myocutaneous latissimus dorsi free flap. This allows for an improved ability to fill these large, round, complex defects, maintaining the safety of our original surgical technique, while improving aesthetic outcomes.A single-institution case series of complex microsurgical reconstructions for full-thickness oncologic calvarial defects using the UTT addition was reviewed. A free 30 cm latissimus dorsi myocutaneous flap was harvested, deepithelialized in-situ, and turned over with the dermal component laying on the avascular reconstructed dura. Both ends were positioned next to each other into a U shape and sutured together, creating a 15 cm round paddle.Fifty two complex microsurgical procedures for oncological calvarial defect reconstruction were performed. The 7 most recent were ideal for the UTT addition. There were no instances of microvascular thrombosis, infection, cerebral spinal fluid leak, or major wound healing problems. All procedures provided stable volume and full coverage, with all patients requiring debulking and contouring to achieve optimal aesthetic results. All flaps remained stable after debulking.The UTT addition takes the previously established "tournedos" latissimus dorsi free flap to another level of reconstruction, providing a larger volumetric filler, round shape, better defect filling, better durability, and better aesthetics, even in irradiated and/or infected calvarial chronic wound bed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".