Incidence and Severity of Lymphoedema following Limb Salvage of Extremity Soft Tissue Sarcoma
Bibliographic record
Abstract
Background and Purpose. Lymphoedema is a serious complication following limb salvage for extremity soft tissue sarcomas (STSs) for which little is known. We aimed to evaluate its incidence, its, severity and its associated risk factors. Material and Method. Patient and tumor characteristics, treatment modalities and complications and functional outcomes (MSTS 1987, TESS), and lymphoedema severity (Stern) were all collected from prospective databases. Charts were retrospectively abstracted for BMI and comorbidities. Results. There were 289 patients (158 males). Mean age was 53 (16-88). Followup ranged between 12 and 60 months with an average of 35 and a median of 36 months. Mean BMI was 27.4 (15.8-52.1). 72% had lower extremity tumors and 38% upper extremity. Mean tumor size was 8.1 cm (1.0-35.6 cm). 27% had no adjuvant radiation, 62% had 50 Gy, and 11% received 66 Gy. The incidence of lymphoedema was 28.8% (206 none, 58 mild, 22 moderate, 3 severe, and 0 very severe). Mean MSTS score was 32 (11-35) and TESS was 89.4 (32.4-100). Radiation dose was significantly correlated with tumor size > 5 cm (P = 0.0001) and TESS score (P = 0.001), but not MSTS score (P = 0.090). Only tumor size > 5 cm and depth were found to be independent predictors of significant lymphoedema. Conclusion. Nine percent of STS patients in our cohort developed significant (grade ≥ 2) lymphoedema. Tumor size > 5 cm and deep tumors were associated with an increased occurrence of lymphoedema but not radiation dosage.
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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) | 0.000 | 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) | 0.001 | 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".