Older age at surgery and postoperative leg length discrepancy are risk factors for unfavourable patient-reported outcome measures of knee tumour endoprostheses following resection for musculoskeletal tumour of the lower limb
Bibliographic record
Abstract
Aims: To evaluate mid-to long-term patient-reported outcome measures (PROMs) of endoprosthetic reconstruction after resection of malignant tumours arising around the knee, and to investigate the risk factors for unfavourable PROMs. Methods: The medical records of 75 patients who underwent surgery between 2000 and 2020 were retrospectively reviewed, and 44 patients who were alive and available for follow-up (at a mean of 9.7 years postoperatively) were included in the study. Leg length discrepancy was measured on whole-leg radiographs, and functional assessment was performed with PROMs (Toronto Extremity Salvage Score (TESS) and Comprehensive Outcome Measure for Musculoskeletal Oncology Lower Extremity (COMMON-LE)) with two different aspects. The thresholds for unfavourable PROMs were determined using anchor questions regarding satisfaction, and the risk factors for unfavourable PROMs were investigated. Results: The thresholds for favourable TESS and COMMON were 64.8 and 70.4 points, respectively. Multivariate analysis showed that age at surgery (p = 0.004) and postoperative leg length discrepancy (p = 0.043) were significant risk factors for unfavourable TESS results, while age at surgery (p < 0.001) was a significant risk factor for unfavourable COMMON-LE results. Following receiver operating characteristic analysis, the threshold for both TESS and COMMON-LE was 29 years of age at surgery. Additionally, a leg length discrepancy of 8.2 mm was the threshold for unfavourable TESS. Conclusion: Patients aged > 29 years at the time of surgery require appropriate preoperative counselling and adequate postoperative physical and socioemotional support. Reconstruction equivalent to the length of the resected bone can reduce the risk of functional disabilities in daily living.
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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 | 0.005 |
| 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".