Cross-cultural Adaptation, Validation, and Reliability of the Persian version of the Toronto Extremity Salvage Score (TESS) for Lower Extremity.
Bibliographic record
Abstract
Objectives: The Toronto Extremity Salvage Score for the lower extremity (LE-TESS) is a commonly used patient-reported outcome measure (PROM) designed to assess physical disability in patients following lower limb salvage surgery for bone or soft tissue tumors. Although the TESS has been widely translated and culturally adapted for clinical and research purposes in many countries, it has not yet been translated into Persian (Farsi) or validated for use in Iranian society. This study aims to provide a validated and reliable Persian version of the TESS questionnaire. Methods: The LE-TESS questionnaire was adapted for the Iranian (Persian) society in accordance with international translation and cultural adaptation guidelines. The reliability and validity of the Persian LE-TESS were assessed in patients referred to Shafa Yahyaeian Hospital who underwent lower limb salvage procedures for malignant tumors between 2016 and 2022. Cronbach's alpha was used to measure internal consistency, and test-retest reliability was assessed within two weeks to calculate the intraclass correlation coefficient (ICC). Construct validity was evaluated using Spearman's rank correlation with the Short Form-36. Results: In this study, 31 patients (54.8% male) were included, with a mean age of 26.16 ± 9.61 years. The internal consistency evaluated by Cronbach's alpha was 0.887, and the intraclass correlation coefficient (ICC) assessed by the test-retest reliability was 0.872. This research's SEM and MDC 0.95 values were as much as 11.63 and 32.23, respectively. The construct validity analysis revealed a strong correlation between the Persian LE-TESS and the SF-36. Conclusion: The Persian version of the LE-TESS demonstrated reliability and validity in assessing the physical function of patients who underwent lower limb salvage surgery for bone and soft tissue tumors.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".