Postoperative Limb Function and QOL in Elderly Patients With Malignant Bone Tumor/Soft Tissue Sarcoma
Bibliographic record
Abstract
BACKGROUND/AIM: Malignant bone tumors (MBT) and soft tissue sarcomas (STS) require wide excision. Although the number of elderly patients is increasing, wide excision may decrease limb function and quality of life (QOL) for elderly patients. However, no detailed evaluation of the functional prognosis or QOL of elderly patients with sarcoma has been reported. This study evaluated postoperative limb function and QOL in elderly patients with MBT and STS. PATIENTS AND METHODS: This retrospective study included 67 patients aged >70 years with MBT or STS who underwent surgery at a single institution. The Toronto Extremity Salvage Score (TESS), EuroQoL 5-dimension 5-level (EQ-5D-5L) questionnaire, Musculoskeletal Tumor Society (MSTS) score, and psoas muscle index (PMI) were evaluated. We also assessed factors associated with the postoperative TESS and EQ-5D-5L index. RESULTS: Detailed examination of the MSTS items perioperatively revealed significant decline in manual dexterity/walking ability and support but significant improvement in pain and emotional acceptance. The mean PMI decreased significantly from 4.7 to 4.23 perioperatively. The postoperative mean TESS and EQ-5D-5L index was 76.9 and 0.74, respectively. Patients with good performance status and clinical frailty scale scores preoperatively had better postoperative TESS and EQ-5D-5L scores. CONCLUSION: The current study strongly suggests the possibility of maintaining postoperative limb function, satisfaction, and QOL in patients with MBT and STS by choosing patients in good condition and the appropriate procedure that the patient desires. However, perioperative progression of sarcopenia should be noted.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".