Core Outcome Measurement Instruments for Clinical Trials of Total Knee Arthroplasty: A Systematic Review
Bibliographic record
Abstract
(1) Background: We have updated knowledge of the psychometric qualities of patient-reported outcome measures and, for the first time, systematically reviewed and compared the psychometric qualities of physical tests for patients with knee osteoarthritis who are undergoing total knee arthroplasty. This work was conducted to facilitate the choice of the most appropriate instruments to use in studies and clinical practice. (2) Methods: A search of medical databases up to December 2019 identified the studies and thus the instruments used. The quality of the measurement properties was assessed by the Bot et al. criteria. (3) Results: We identified 20 studies involving 25 instruments. Half of the instruments were questionnaires (n = 13). Among the condition-specific instruments, the Oxford knee score, Knee injury and Osteoarthritis Outcomes Score, and the Western Ontario and McMaster Universities Osteoarthritis index had the highest overall scores. Concerning generic tools, the Medical Outcomes Study Short-Form 36 (SF-36) or SF-12 obtained the highest overall score. For patient-specific tools, the Hospital Anxiety and Depression Scale ranked the highest. Some physical tests seemed robust in psychometric properties: 6-min Walk Test, five times Sit-To-Stand test, Timed Up and Go test strength testing of knee flexor/extensor by isometric or isokinetic dynamometer and Pressure Pain Threshold. (4) Conclusion: To make stronger recommendations, key areas such as reproducibility, responsiveness to clinical change, and minimal important change still need more rigorous evaluations. Some promising physical tests (e.g., actimetry) lack validation and require rigorous studies to be used as a core set of outcomes in future studies.
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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 | 0.068 | 0.248 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.013 |
| Bibliometrics | 0.017 | 0.016 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".