Surgical considerations for management of distal extremity soft tissue sarcomas
Bibliographic record
Abstract
PURPOSE OF REVIEW: This review focuses on the surgical management of soft tissue sarcomas of the hands and the feet. With recent advances in limb salvage surgery and radiotherapy delivery, local control of soft tissue sarcoma in the extremity has become optimized, and the associated functional results of this treatment have taken on extreme importance. Techniques to limit the amount of normal tissue resected and to reconstruct the resulting defects are critical to the final functional result. RECENT FINDINGS: Several features of soft tissue sarcoma unique to the hand and foot have been reported. Certain histologic subtypes of soft tissue sarcoma have been noted to arise preferentially in the hand and the foot, such as epithelioid sarcoma, clear cell sarcoma, and synovial sarcoma. Patients with hand and foot sarcomas have been described as having improved overall survival, but this is likely a result of the smaller size of tumors arising in these locations. Reconstruction of bone defects using various techniques, vascular reconstruction, tendon transfers, and soft tissue reconstruction using regional flaps in the hand and free flaps in the foot have resulted in good functional outcomes. Amputation and early prosthetic fitting still have a role in management of some soft tissue sarcomas, most frequently in the foot. SUMMARY: Limb salvage remains the standard of care for extremity soft tissue sarcomas. Given the fact that patients have good oncologic and functional outcomes with limb salvage in tumors in the hand and foot, surgical oncologists should have this goal for each patient.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".