Poor functional performance 1 year after ACL reconstruction increases the risk of early osteoarthritis progression
Bibliographic record
Abstract
BACKGROUND: Not meeting functional performance criteria increases reinjury risk after ACL reconstruction (ACLR), but the implications for osteoarthritis are not well known. OBJECTIVE: To determine if poor functional performance post-ACLR is associated with risk of worsening early osteoarthritis features, knee symptoms, function and quality of life (QoL). METHODS: Seventy-eight participants (48 men) aged 28±15 years completed a functional performance test battery (three hop tests, one-leg-rise) 1 year post-ACLR. Poor functional performance was defined as <90% limb symmetry index (LSI) on each test. At 1 and 5 years, MRI, Knee injury Osteoarthritis Outcome Score (KOOS) and International Knee Documentation Committee (IKDC) subjective form were completed. Primary outcomes were: (i) worsening patellofemoral and tibiofemoral MRI-osteoarthritis features (cartilage, bone marrow lesions (BMLs) and meniscus) and (ii) change in KOOS and IKDC scores, between 1 and 5 years. RESULTS: Only 14 (18%) passed (≥90% LSI on all tests) the functional test battery. Poor functional performance on the battery (all four tests <90% LSI) 1 year post-ACLR was associated with 3.66 times (95% CI 1.12 to 12.01) greater risk of worsening patellofemoral BMLs. A triple-crossover hop <90% LSI was associated with 2.09 (95% CI 1.15 to 3.81) times greater risk of worsening patellofemoral cartilage. There was generally no association between functional performance and tibiofemoral MRI-osteoarthritis features, or KOOS/IKDC scores. CONCLUSION: Only one in five participants met common functional performance criteria (≥90% LSI all four tests) 1 year post-ACLR. Poor function on all four tests was associated with a 3.66 times increased risk of worsening patellofemoral BMLs, and generally not associated with decline in self-reported outcomes.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".