Pain, balance and mobility in people one year after total knee arthroplasty: A pilot cross-sectional study contrasting posterior-stabilized and medial-pivot designs
Bibliographic record
Abstract
Abstract Background Total knee arthroplasty (TKA) is a common treatment for severe knee osteoarthritis. TKA designs have evolved from posterior-stabilized systems (PS-TKA) developed in the late 70 s that replicate posterior-cruciate ligament function to medial-pivot systems (MP-TKA) developed in the early 90 s that more closely mimic natural knee kinematics. This study aimed to test the hypothesis that people with MP-TKA have better postoperative outcomes than PS-TKA, and their balance control is more akin to age-matched asymptomatic controls.Methods Fifty-seven participants (20 PS-TKA, 18 MP-TKA and 19 asymptomatic controls) were recruited. At 1-year post-TKA, pain, knee stiffness and physical function were assessed using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). Static balance, mobility and gait stability were assessed using wearable devices during the near tandem stance, timed-up-and-go (TUG) and six-minute walk (6MWT) tests.Results Compared to asymptomatic controls, both TKA groups reported significantly more pain and stiffness, and demonstrated reduced functional mobility, increased stride-time-variability and impaired balance; indicating increased fall risk. After Bonferroni adjustment, no significant differences were observed between PS-TKA and MP-TKA participants. However, there was a trend for increased anteroposterior sway of the lumbar and head regions in the MP-TKA participants when undertaking the near tandem stance test.Conclusions Contrary to the hypothesis, the MP-TKA patients did not have less pain or better balance and mobility performance than the PS-TKA patients 1 year after surgery. Future longitudinal research should determine whether the two types of patients display different pain, balance controls and mobility over the first year postoperative period.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".