A review of 105 subscapular-based flaps harvested using a new dorsal decubitus position: how far can we go?
Bibliographic record
Abstract
OBJECTIVE: Interest in flaps based on the subscapular vascular system has decreased because of the need for intraoperative patient repositioning and the inability to employ a simultaneous 2-team approach. The aims of this study are to review our experience using dorsal decubitus patient positioning for subscapular-based flap harvest and to demonstrate the effectiveness and safety of this approach. METHODS: A retrospective review of all subscapular-based flap cases performed by the senior author at 2 hospital centers from 1995 to 2010 was conducted. Variables studied included indications for reconstruction, flap characteristics, and postoperative complications. A longitudinal roll placed between the scapulae as well as an optional perpendicularly placed shoulder roll are used to achieve dorsal decubitus patient positioning. RESULTS: One hundred five flaps were performed during the study period, and dorsal decubitus positioning was used in all cases. Eighty-four flaps were free and 21 were pedicled. Indications for reconstruction included cancer resection (n = 58), trauma (n = 32), infection (n = 9), and others (n = 6). A simultaneous 2-team approach was carried out in 70 cases. Major complications included 9 cases of arterial or venous thrombosis/insufficiency, 2 of which resulted in total flap failure. Intraoperative conversion to lateral decubitus positioning was never required. CONCLUSIONS: Dorsal decubitus harvesting for subscapular-based flaps is a practical and effective technique that enables a simultaneous 2-team approach in complex reconstructive cases. Previous limitations of these highly versatile flaps, such as the need for intraoperative patient repositioning, can thus be avoided. This approach is employed for all subscapular-based flap reconstructions performed by the senior author.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".