Validation of the 10‐Item Lower Extremity Functional Scale (LEFS‐10) for Individuals With Knee Osteoarthritis
Bibliographic record
Abstract
BACKGROUND: Functional capacity assessment in knee osteoarthritis (KOA) is essential because it relates to pain, disability, and quality of life. Reliable, sensitive, and validated tools are needed to measure lower limb function. PURPOSE: To validate the Brazilian Portuguese version of the 10-item Lower Extremity Functional Scale (LEFS-10) for people with KOA. METHODS: A cross-sectional validation study involved 100 participants with KOA. The agreement between the 10-item (LEFS-10) and 20-item (LEFS-20) scales was examined using Spearman's correlation coefficient (rho) between the LEFS-10 and the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), the Numeric Pain Rating Scale (NPRS), and the World Health Organization Disability Assessment Schedule (WHODAS). Test-retest reliability was measured with the intraclass correlation coefficient (ICC), the standard error of measurement (SEM), and the minimum detectable change (MDC). Internal consistency was assessed using Cronbach's alpha. Ceiling and floor effects were also evaluated. RESULTS: Most individuals had right or bilateral KOA, with diagnosis duration and persistent pain exceeding 5 years. LEFS-10 scores showed strong correlations with the original LEFS-20 (rho = 0.92), NPRS (rho = -0.78), WOMAC pain (rho = -0.69), stiffness (rho = -0.67), physical function (rho = -0.70), and WHODAS (rho = -0.74). Internal consistency was adequate (Cronbach's alpha = 0.89). In a subsample of 50 participants, test-retest reliability was excellent (ICC = 0.98, 95% CI 0.97-0.99), with a SEM of 1.05 points (6.7%) and an MDC of 2.91 points (18.6%), with no ceiling or floor effects. DISCUSSION: The LEFS-10 demonstrates excellent concordance compared with LEFS-20, good convergent validity, adequate internal consistency, high reliability, and favorable measurement error parameters, making it suitable for individuals with KOA.
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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 | 0.010 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".