ICRS Recommendation Document
Bibliographic record
Abstract
OBJECTIVE: The purpose of this article is to describe and recommend patient-reported outcome instruments for use in patients with articular cartilage lesions undergoing cartilage repair interventions. METHODS: Nonsystematic literature search identifying measures addressing pain and function evaluated for validity and psychometric properties in patients with articular cartilage lesions. RESULTS: The knee-specific instruments, titled the International Knee Documentation Committee Subjective Knee Form and the Knee injury and Osteoarthritis and Outcome Score, both fulfill the basic requirements for reliability, validity, and responsiveness in cartilage repair patients. A major difference between them is that the former results in a single score and the latter results in 5 subscores. A single score is preferred for simplicity's sake, whereas subscores allow for evaluation of separate constructs at all levels according to the International Classification of Functioning. CONCLUSIONS: Because there is no obvious superiority of either instrument at this time, both outcome measures are recommended for use in cartilage repair. Rescaling of the Lysholm Scoring Scale has been suggested, and confirmatory longitudinal studies are needed prior to recommending this scale for use in cartilage repair. Inclusion of a generic measure is feasible in cartilage repair studies and allows analysis of health-related quality of life and health economic outcomes. The Marx or Tegner Activity Rating Scales are feasible and have been evaluated in patients with knee injuries. However, activity measures require age and sex adjustment, and data are lacking in people with cartilage repair.
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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 | 0.018 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.019 | 0.007 |
| Insufficient payload (model declined to judge) | 0.347 | 0.364 |
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".