Validity and Responsiveness of the Knee Injury and Osteoarthritis Outcome Score: A Comparative Study Among Total Knee Replacement Patients
Bibliographic record
Abstract
OBJECTIVE: To evaluate validity and responsiveness of the Knee Injury and Osteoarthritis Outcome Score (KOOS) in relation to other patient-reported outcome measures before and after total knee replacement (TKR). METHODS: Pre-TKR and 6-month post-TKR data from 1,143 patients in a US joint replacement cohort were used to compare the KOOS, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), and the SF-36 Health Survey (SF-36). Validity was evaluated with multiple methods, including correlations of pre-TKR scale scores and analysis of variance models that used pre-TKR data to compare the relative validity of scales in discriminating between groups differing in assistive walking device use and number of comorbid conditions. Validity was also evaluated by using post-TKR minus pre-TKR change scores to assess relative validity of scales in discriminating between groups rating themselves as better, same, or worse (BSW) in their capability to do activities at 6 months. Responsiveness also was described using effect sizes and standardized response means. RESULTS: In support of convergent and discriminant validity, KOOS scale scores were worse for patients using an assistive device but only declined weakly with increasing comorbid conditions. While all knee-specific scales discriminated between BSW groups, the KOOS quality of life (QOL) scale was significantly better (P < 0.05) than all measures except the SF-36 physical component summary. KOOS QOL also had the highest effect size, while SF-36 measures had lower effect sizes and standardized response means. KOOS pain and symptoms scales discriminated better than WOMAC pain and stiffness scales among BSW groups. CONCLUSION: KOOS scales were valid and responsive in this cohort of US TKR patients. KOOS QOL performed particularly well in capturing aggregate knee-specific outcomes.
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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 | 0.003 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".