Patient Reported Outcomes Following Lower Extremity Soft Tissue Sarcoma Resection with Microsurgical Preservation of Ambulation
Bibliographic record
Abstract
BACKGROUND: Lower extremity soft tissue sarcoma treatment has evolved from primarily amputation procedures toward limb salvage. This series assesses whether soft tissue sarcoma tissue defects, extensive enough to require microsurgical reconstruction, can reliably result in preservation of ambulation, as well as objectively evaluate functional outcomes utilizing a patient-reported validated scale. It will also look at whether immediate functional muscle reconstructions and tendon transfers can be successful at restoring ambulation, potentially expanding the indications for limb salvage procedures. METHODS: A retrospective review of all microsurgical reconstructions for limb salvage in lower extremity sarcoma patients was completed at our institution (2009-2013). Patients were additionally asked to complete the Toronto Extremity Salvage Score(TESS) quality of life survey. RESULTS: Over a 5-year period, 23 patients (mean age: 53 years) underwent free flap reconstructions for 23 sarcomas (mean follow-up: 14 months). Seventy-eight percent of patients received neoadjuvant radiation. The thigh was the most common tumor site (61%) and three muscles were resected on average. Perforator flaps were most frequently used (61%), and functional muscle transfers or immediate tendon transfers were used in four patients. There were no flap take-backs or failures, and 22 patients achieved independent ambulation. Three patients in the series died, two from metastatic disease found postoperatively and one from local recurrence. A 74% response rate was achieved for the TESS survey, with a mean score of 83. CONCLUSION: Microsurgical reconstruction of lower extremity sarcoma defects enables preservation of independent ambulation. Restoration of function utilizing immediate functional microsurgical reconstructions and tendon transfers should be considered.
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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 | 0.004 |
| 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".