Altered Gait Characteristics in Individuals With Knee Osteoarthritis and Self-Reported Knee Instability
Bibliographic record
Abstract
STUDY DESIGN: Experimental laboratory study. OBJECTIVE: To characterize the differences in lower extremity gait biomechanics in individuals who have knee osteoarthritis (OA) with and without self-reported knee instability. BACKGROUND: Individuals with knee OA who experience episodes of knee instability often report gait difficulties that interfere with their daily lives. A better understanding of the alterations in gait biomechanics may help to mitigate symptomatic knee instability in this patient population. METHODS: Seventeen participants with knee OA and self-reported knee instability and 36 participants with knee OA and no self-reported knee instability underwent instrumented gait analysis on level ground. Knee-specific symptoms and functional limitations were assessed using the Western Ontario and McMaster Universities Osteoarthritis Index. RESULTS: Knee instability was associated with greater odds of reporting moderate to severe gait-related pain (odds ratio = 6.0; 95% confidence interval: 1.2, 28.9) and moderate to severe difficulty when walking on flat surfaces (odds ratio = 10.7; 95% confidence interval: 1.7, 69.2). During early stance, the group with self-reported knee instability walked with a greater knee flexion excursion (P = .02) and a smaller lower extremity support moment (P<.01), due to reduced contributions from the hip extensors (P<.01) and ankle plantar flexors (P = .04). The group with self-reported knee instability also walked with a greater knee extensor contribution to the lower extremity support moment (P = .04) during the initial knee extension phase of gait compared to their counterparts with good knee stability. CONCLUSION: These findings suggest that self-reported knee instability is associated with significant alterations in hip, knee, and ankle joint function during the stance phase of gait in individuals with knee OA.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".