A randomised controlled clinical trial and gait analysis of fixed- and mobile-bearing total knee replacements with a five-year follow-up
Bibliographic record
Abstract
This study compared the outcome of total knee replacement (TKR) in adult patients with fixed- and mobile-bearing prostheses during the first post-operative year and at five years' follow-up, using gait parameters as a new objective measure. This double-blind randomised controlled clinical trial included 55 patients with mobile-bearing (n = 26) and fixed-bearing (n = 29) prostheses of the same design, evaluated pre-operatively and post-operatively at six weeks, three months, six months, one year and five years. Each participant undertook two walking trials of 30 m and completed the EuroQol questionnaire, Western Ontario and McMaster Universities osteoarthritis index, Knee Society score, and visual analogue scales for pain and stiffness. Gait analysis was performed using five miniature angular rate sensors mounted on the trunk (sacrum), each thigh and calf. The study population was divided into two groups according to age (≤ 70 years versus > 70 years). Improvements in most gait parameters at five years' follow-up were greater for fixed-bearing TKRs in older patients (> 70 years), and greater for mobile-bearing TKRs in younger patients (≤ 70 years). These findings should be confirmed by an extended age controlled study, as the ideal choice of prosthesis might depend on the age of the patient at the time of 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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".