Patient-reported outcome measures after total knee arthroplasty
Bibliographic record
Abstract
OBJECTIVES: A lack of connection between surgeons and patients in evaluating the outcome of total knee arthroplasty (TKA) has led to the search for the ideal patient-reported outcome measure (PROM) to evaluate these procedures. We hypothesised that the desired psychometric properties of the ideal outcome tool have not been uniformly addressed in studies describing TKA PROMS. METHODS: A systematic review was conducted investigating one or more facets of patient-reported scores for measuring primary TKA outcome. Studies were analysed by study design, subject demographics, surgical technique, and follow-up adequacy, with the 'gold standard' of psychometric properties being systematic development, validity, reliability, and responsiveness. RESULTS: A total of 38 articles reported outcomes from 47 different PROMS to 85 541 subjects at 26.3 months (standard deviation 30.8) post-operatively. Of the 38, eight developed new scores, 20 evaluated existing scores, and ten were cross-cultural adaptation of existing scores. Only six of 38 surveyed studies acknowledged all 'gold standard' psychometric properties. The most commonly studied PROMS were the Oxford Knee Score, New Knee Society Score, Osteoarthritis Outcome Score, and Western Ontario and McMaster Universities Osteoarthritis Index. CONCLUSIONS: A single, validated, reliable, and responsive PROM addressing TKA patients' priorities has not yet been identified. Moreover, a clear definition of a successful procedure remains elusive. Cite this article: Bone Joint Res 2015;4:120-127.
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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 | 0.013 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".