Pain, balance and mobility in people one year after total knee arthroplasty: A non-randomized cross-sectional pilot 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. Medial-pivot TKA systems (MP-TKA) are theoretically better than posterior-stabilized TKA systems (PS-TKA) in improving static and dynamic balance of patients although it is difficult to objectively quantify these balance parameters in a clinical setting. Therefore, this pilot study aimed to evaluate the feasibility of using wearable devices in a clinical setting to examine whether people with MP-TKA have better postoperative outcomes than PS-TKA, and their balance control is more akin to age-matched asymptomatic controls. Methods : The current cross-sectional pilot study recruited 57 participants with two different prosthesis designs (20 PS-TKA, 18 MP-TKA) and 19 asymptomatic controls. 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 of the participants were evaluated based on data collected from wearable motion sensors during the near tandem stance, timed-up-and-go , and six-minute walk 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. After Bonferroni adjustment, no significant differences in pain, balance and mobility performance were observed between PS-TKA and MP-TKA participants one year after surgery. 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. The wearable motion sensors were easy to use without any adverse effects. Conclusions: It is feasible to use wearable motion sensors in a clinical setting to compare balance and mobility performance of patients with different TKA prothesis designs. Since this was a pilot study and no definite conclusions could be drawn, future clinical trials should determine the impacts of different TKA prosthesis designs on postoperative outcomes over a longer follow-up period. Keywords: Prosthesis; Postural sway; Gait; Wearable sensors; Post-operation; Balance performance Key messages regarding feasibility What uncertainties existed regarding the feasibility?;It was unclear whether wearable motion sensors could be used to evaluate the balance and mobility of patients undergoing two different types of total knee arthroplasty (TKA) prostheses at 1-year follow-up with reference to age-matched asymptomatic controls. What are the key feasibility findings?Wearable motion sensors were a safe non-invasive tool to evaluate balance and mobility of TKA patients in a clinical setting. The results from the wearable motion sensors showed that both TKA groups demonstrated reduced functional mobility, increased stride-time-variability, and poorer balance as compared to age-matched asymptomatic controls. What are the implications of the feasibility findings for the design of the main study?Wearable motion sensors can be used in a clinical setting to measure balance and mobility of patients following TKA. A randomized controlled trial should be conducted to determine whether the two types of patients display significantly different pain, balance controls and mobility during the first two years after surgery.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".