Microsurgical Preservation of Ambulation in Lower Extremity Sarcoma Treatment
Bibliographic record
Abstract
INTRODUCTION: Lower extremity sarcoma treatment has evolved from primarily amputation procedures towards limb salvage.1 A survival advantage has not been shown for amputation compared to limb salvage, although amputation is associated with a significantly higher level of handicap. 2,3 Microsurgery has the potential to further expand the options in limb preservation by allowing coverage of massive soft tissue defects as well as by restoring function following the resection of critical nerves, muscles or tendons. These immediate reconstructive procedures are capable of preserving ambulation and therefore function. This study examines our institution’s experience with microsurgical techniques as they apply to lower extremity soft tissue sarcoma treatment. MATERIALS AND METHODS: A 5-year retrospective review of all microsurgical reconstructions for limb salvage in lower extremity sarcoma patients was completed at our institution. Limb salvage rates, oncological data, surgical techniques as well as complication rates were analyzed. Patients were additionally asked to complete the Toronto Extremity Salvage Score (TESS) quality of life survey. RESULTS: Over a five-year period, 22 patients (average age 52.2 years) underwent free flap reconstructions for 23 sarcomas (mean follow-up 14 months). 85% of patients underwent neoadjuvant radiation therapy. The thigh was the most common tumor site (56.5%) and 3 named muscles were resected on average. Perforator flaps were most frequently used (68.18%), and functional muscle transfers or immediate tendon transfers were used in three patients. There were no flap take-backs or failures, and 21 patients achieved independent ambulation. Two patients in the series died, each from metastatic disease and not local recurrence. A 77.3% response rate was achieved for the TESS survey, with a mean score of 83.1% as a representation of normal lower extremity function. The lowest average TESS scores were associated with kneeling, participating in sporting activities and getting up from kneeling. There was no relationship between TESS scores and tumor location, resection surface area, number of muscles resected, or days to ambulation. CONCLUSION: Microsurgical reconstruction of lower extremity sarcoma defects enables the preservation of ambulation. Restoration of function utilizing immediate functional microsurgical reconstructions should be considered safe and effective in lower extremity sarcoma limb salvage.
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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 | 0.001 | 0.001 |
| 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) | 0.002 | 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".