The Toronto Extremity Salvage Score in Unoperated Controls: An Age, Gender, and Country Comparison
Bibliographic record
Abstract
The Toronto Extremity Salvage Score (TESS) is widely used for the functional assessment of patients following surgery for musculoskeletal tumours. The aim of this study was to determine if there are gender and/or age-specific changes, unrelated to surgery, that may influence this score and the appropriateness of the questions. The TESS for lower limb was carried out in two different countries to see if there was variation between them. There were no statistically significant differences between the scores obtained between the respondents from Australia or Britain either in total or between the corresponding age groups. There were statistically significant differences in the TESS obtained between age groups with a lower score at older age groups but there was no difference between the sexes. Patients in the age group 70+ were more likely to record activities as "not applicable" and also have a lower score. This study has shown that age is the major factor in determining the TESS in both an Australian and British populations of otherwise healthy people. As there were no differences between the two populations, it supports the TESS as an international scoring system. There may be also an argument for age-specific questions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.003 | 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".