Knee instruments and rating scales designed to measure outcomes
Bibliographic record
Abstract
In this article, the knee instruments and rating scales that are designed to measure outcomes are revised. Although the International Knee Documentation Committee Subjective Knee Form can be used as a general knee measure, no instrument is currently universally applicable across the spectrum of knee disorders and patient groups. Clinicians and researchers looking to use a patient-based score for measurement of outcomes must consider the specific patient population in which it has been evaluated. The Western Ontario and McMaster Universities Osteoarthritis Index is recommended for the evaluation of treatment effect in persons with osteoarthritis (OA). This is a generic health status questionnaire that contains 36 items, is widely used, and easy to complete. The Knee Injury and Osteoarthritis Outcome Score (KOOS) questionnaire evaluates the functional status and quality of life (QoL) of patients with any type of knee injury who are at increased risk of developing OA; i.e., patients with anterior cruciate ligament (ACL) injury, meniscus injury, or chondral injury. So far, the KOOS questionnaire has been validated for several orthopedic procedures such as total knee arthroplasty, ACL reconstruction, and meniscectomy. The utilization of QoL questionnaires is crucial to the adequate assessment of a number of orthopedic procedures of the knee. The questionnaires are generally well accepted by the patients and open up new perspectives in the analysis of prognostic factors for optimal QoL of patients undergoing knee surgery.
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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 | 0.009 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.005 |
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".