Vascular reconstruction with the superficial femoral vein following major oncologic resection
Bibliographic record
Abstract
INTRODUCTION: Involvement of critical vascular structures has historically been considered a contraindication to tumor resection. This study describes outcomes following radical oncologic resection with concomitant resection of critical vascular structures and reconstruction with the superficial femoral vein (SFV). METHODS: All patients undergoing radical oncologic resection requiring resection of major vascular structures and concomitant reconstruction using the SFV as conduit were retrospectively reviewed. Primary outcomes were surgical morbidity and mortality; secondary measures included long-term patency and oncologic outcomes. RESULTS: Seven patients were included. There were three retroperitoneal and two groin sarcomas, and two squamous cell carcinomas metastatic to groin lymph nodes. No perioperative mortality occurred. Five patients experienced minor morbidity. One vein graft in a patient with pre-existing chronic deep venous thrombosis (DVT) occluded post-operatively. No subsequent long-term venous or arterial graft occlusions occurred (median 20.2 months, range 9.0-49.7). Two patients died of tumor recurrence during follow-up. CONCLUSIONS: Resection of tumors involving critical vascular structures is feasible. The SFV conduit is a versatile option for major vascular reconstruction, providing good long-term patency rates with acceptable morbidity and mortality. Vascular resection and reconstruction with the SFV offers another technique to provide limb-sparing surgery in patients traditionally offered only amputation, while providing favorable oncologic outcomes.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".