USE of arterialized saphenous vein venous flow‐through flaps as a temporizing measure for hand salvage in contaminated wounds presenting with limb ischemia: A case series
Bibliographic record
Abstract
BACKGROUND: Vascular injuries resulting in limb ischemia are traditionally treated acutely with autologous or prosthetic bypass grafts. Traumatic contaminated injuries with soft tissue and vascular segmental loss are challenging as prosthetic bypasses are at risk of erosion, infection, and occlusion; and autologous bypasses are at risk of desiccation, blow-out, infection, and clotting. We propose a novel approach to these injuries by using arterialized saphenous vein venous flow-through free flaps (S-VFTF) as an autologous bypass, and present the results of its application in a series of cases. METHODS: Spanning 2008 to 2015, four patients presenting with large contaminated crush/avulsion wounds with vascular injury underwent hand revascularization with S-VFTF, allowing the contaminated wounds to be serially debrided. Definitive soft tissue reconstruction was performed once the wound was considered clean. The S-VFTF skin paddle was de-epithelialized and the soft tissue defect covered with a free latissimus dorsi flap or a rectus abdominis myocutaneous flap. RESULTS: All ischemic limbs were successfully reperfused and there were no take backs for perfusion issues. All S-VFTF remained patent at discharge and final follow-up. No partial or complete finger/hand amputations were required. All definitive coverage free flap survived with no complications. CONCLUSION: The two-stage reconstruction presented may help reconstructive and vascular surgeons consider alternatives to traditional vascular reconstruction methods. This technique avoids an exposed vascular graft in an extensively contaminated open wound. It allows the surgeon to perform thorough and sufficient debridement of the wound, preventing definitive reconstruction in a not yet declared zone of injury.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".