148 Muscle strength tests in individuals following an anterior cruciate ligament or meniscus injury: a systematic review of measurement properties (OPTIKNEE)
Bibliographic record
Abstract
Introduction There is a lack of consensus on the most relevant and clinically applicable tests to evaluate knee muscle strength following a knee injury. This systematic review aimed to critically appraise and summarize the measurement properties of knee muscle strength tests in young individuals with anterior cruciate ligament (ACL) or meniscus injury. Materials and Methods Studies evaluating at least one measurement property of a knee extensor or flexor strength test in individuals with an ACL or meniscus injury with a mean injury age of ≤30 years were included. The COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) Risk of Bias checklist was used to assess methodological quality. A modified Grading of Recommendations Assessment, Development, and Evaluation (GRADE) assessed evidence quality. Results Thirty-four studies evaluating 30 muscle strength tests following an ACL or meniscal injury were included. Strength tests were assessed for reliability (n=8), measurement error (n=7), construct validity (n=25) and criterion validity (n=7). Concentric extensor and flexor strength tests showed sufficient ratings for two measurement properties, namely for intra-rater reliability (very low quality of evidence) and construct validity (moderate quality of evidence). Isotonic extensor and flexor strength tests displayed sufficient criterion validity (high quality of evidence). Conclusion This review highlights an important lack of evidence on measurement properties of strength tests following ACL tear and meniscus injury. Concentric strength tests are currently the most promising tests following an ACL injury. High-quality studies on measurement properties are needed to recommend muscle strength tests in research and clinical practice.
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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 | 0.086 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.010 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".