Tricompartment offloader knee brace reduces contact forces in adults with multicompartment knee osteoarthritis
Bibliographic record
Abstract
The levitation tricompartment offloader (TCO) brace is designed to unload all three knee compartments by reducing compressive forces caused by muscle contraction. This study aimed to determine the effect of the TCO on knee contact forces and quadriceps muscle activity in individuals with knee osteoarthritis. Lower limb kinematics, kinetics, and electromyography data were collected during a chair rise-and-lower task. A three-dimensional inverse dynamics model of the lower leg and foot was used with a sagittal plane knee model to compute knee joint forces. TCO brace use significantly decreased forces in the tibiofemoral [p = 0.001; mean difference, MD (97.5% confidence interval, CI) -0.62 (-0.91, -0.33) body weight (BW)] and patellofemoral [p = 0.001; MD (97.5% CI) -0.88 (-1.36, -0.39) BW] compartments in high-power mode. Significant reductions in quadriceps tendon force [p = 0.002; MD (97.5% CI) -0.53 (-0.83, -0.23) BW] and electromyography intensity of the vastus medialis [p = 0.018, MD (97.5% CI) -30.7 (-59.1, -2.3)] and vastus lateralis [p = 0.012, MD (97.5% CI) -26.2 (-48.5, -3.9)] were also observed. The TCO significantly reduced tibiofemoral and patellofemoral contact forces throughout chair lower, and when knee flexion was greater than 50° during chair rise in high power. These results demonstrate that the TCO reduces contact forces in the tibiofemoral and patellofemoral joint compartments and confirms that the TCO unloads the joint by reducing compressive forces caused by the quadriceps. Clinical significance: The magnitude of knee joint unloading provided by the TCO is similar to that achieved by clinically recommended levels of bodyweight loss and is therefore expected to result in clinical benefits for knee osteoarthritis patients.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".