Comparing quality of life in lower extremity tumor patients undergoing limb salvage surgery and amputation: a meta-analysis
Bibliographic record
Abstract
Purpose: Limb salvage surgery and amputation are two commonly performed procedures for lower extremity tumors. When comparing these procedures in tumor patients, it is important to consider their impact on quality of life (QOL) and functional mobility. These patients often experience physical, emotional, and psychological challenges, making these factors crucial in determining the most suitable treatment approach. Method: The outcomes of lower extremity tumors patients for QOL were collected from PubMed, MEDLINE, EMBASE, Cochrane, and Google Scholar until 28 February 2023. The physical function, mental health, role function, social function, emotional function, Toronto Extremity Salvage Score, and Musculoskeletal Tumor Society Score outcomes were analyzed to determine the differences between the two procedures. Results: Five articles were included according to the selection criteria with a total of 245 patients. The standard mean difference (SMD) values of each parameter were slightly higher in limb salvage surgery patients but not higher enough to produce statistically significant results; the SMD values for physical function and mental health were 0.72 and 0.04, respectively. This study did not report any heterogeneity or publication bias. Conclusions: QOL is a large and enhanced term, which carries its importance and is challenging to compare between any procedures. The minimal rise in SMD of different QOL parameters highlighted only a slight advantage of limb salvage surgery over amputation. Therefore, further research is required to explore the impact of this crucial topic.
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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 | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.029 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".