Performance‐Based Outcome Measures After Hip or Knee Arthroplasty: A Systematic Review and Content Analysis Using the International Classification of Functioning, Disability and Health (ICF)
Bibliographic record
Abstract
RATIONAL: One of the important considerations to select the appropriate outcome measures is determining if the tool is relevant to patients. Despite the availability of various performance-based tests to objectively assess function, it is unknown which performance-based tests best capture important aspects of function after hip or knee arthroplasty. AIMS AND OBJECTIVES: Our systematic review aimed to identify the existing performance-based tests used in hip or knee arthroplasty and link the activity component of each test to the modified International Classification of Functioning, Disability and Health (ICF) core set for osteoarthritis (OA). METHOD: We searched four databases from inception until April 2024. A performance-based test was included if an individual performs one or more activities, evaluated by an assessor and resulted in a numerical value. Two reviewers independently screened and extracted data and assessed the included performance-based tests. RESULTS: From 449 studies included in this review, we identified 28 performance-based tests which covered 15 categories of OA core set activity and participation. The categories of d4500:walking short distances, d4104:standing and d4103:sitting were the most frequently used, employed in 14, 10 and 10 performance-based tests, respectively. However, 34 categories of activity and participation were not found in any performance-based tests. A-test ('A' like Activity or Assessment) had the widest coverage covering 10 out of 49 core set categories. Four performance tests covered four activity and participation categories, one covered three categories, 10 covered two categories and 12 covered one category. CONCLUSION: Our ICF-based content analysis revealed that the existing performance-based tests covered certain OA core set activity and participation categories, but overlooked multiple categories. This analysis can serve as a guide for researchers and clinicians in selecting suitable performance-based tests or a battery of tests to assess function following hip or knee arthroplasty.
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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 | 0.023 | 0.099 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.010 |
| Bibliometrics | 0.025 | 0.026 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".