FUNCTIONAL OUTCOME IN SARCOMA MANAGEMENT: AMPUTATION VS. LIMB SALVAGE
Bibliographic record
Abstract
Introduciton In our experience, amputation is rarely indicated in osteosarcoma. Amputation is more frequently required in soft tissue sarcoma for the following reasons: 1) recurrent tumour in previously radiated field; 2) composite tissue involvement of soft tissue, bone, vessels and nerves; 3) size of lesion. We have measured functional outcome in bone and soft tissue sarcoma using a combination of clinimetric measures describing impairment and patient determined measures assessing disability ([1][1],[2][2]). Methods In a matched case-control study ([3][3]), 12 patients with amputation were matched with 24 patients treated by limb-sparing surgery on the following variables: age, gender, length of follow-up, bone versus soft-tissue tumor, anatomic site, and treatment with adjuvant chemotherapy. End points included the Toronto Extremity Salvage Score (TESS), a measure of physical disability; the Shortform-36 (SF-36), a generic health status measure; and the Reintegration to Normal Living (RNL), a measure of handicap. Results Mean TESS score for the patients with amputations was 74.5 versus 85.1 for the limb-sparing patients. (p = .15). Only the physical function subscale of the SF-36 showed statistically significant differences, with means of 45 and 71.1 for the amputation versus limb-sparing groups, respectively (p = .03). The RNL for the amputation group was 84.4 versus 97 for the limb-sparing group (p = .05). Seven of the 12 patients with amputations experienced ongoing difficulty with the soft tissues overlying their stumps. There was a trend toward increased disability for those in the amputation group versus those in the limb-sparing group, with the amputation group showing significantly higher levels of handicap. Conclusions These data suggest that the differences in disability between amputation and limb-sparing patients are smaller than anticipated. The differences may be more notable in measuring handicap. [1]: #ref-1 [2]: #ref-2 [3]: #ref-3
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".