Preserving Patient‐Specific Knee Motion: A Randomized Clinical Trial of Unicompartmental and Total Knee Arthroplasty
Bibliographic record
Abstract
ABSTRACT Unicompartmental knee arthroplasty (UKA) may enable improved functional outcomes compared to total knee arthroplasty (TKA). This randomized controlled trial assessed pre‐ and postoperative patient reported outcome measures (PROMs) and knee joint gait biomechanics for UKA and TKA patients. Patients were allocated to UKA (Oxford Partial Knee, Biomet, USA) and TKA (Persona CR Knee System, Zimmer, USA) study arms. Patients completed the Oxford Knee Score (OKS) and Western Ontario & McMaster University Arthritis Index (WOMAC), as well as instrumented gait analysis before and 1‐year after surgery. Measures of interest: OKS scores; WOMAC sub‐scores; Patient‐specific correlations and root mean squared errors (RMSE) of stance phase sagittal and coronal knee angles. Statistical analysis included linear mixed‐effects models (PROMs; α = 0.0125) and multivariate analysis of variance (gait biomechanics; α = 0.05). A total of 38 patients were recruited (UKA n = 17; TKA n = 21). All PROMs improved significantly following surgery ( n = 37, p < 0.001), regardless of surgical technique. A significant effect of surgical technique on gait biomechanics was observed ( n = 30, F 4,25 , p = 0.010), where UKA patients displayed greater sagittal plane correlations [median(Q1,Q3) UKA 0.985 (0.967, 0.991), TKA 0.955 (0.942, 0.973)]; p = 0.018] and lower coronal plane RMSEs [UKA 3.6 (2.4,5.0)°, TKA 8.6 (5.1, 11.5)°; p = 0.002]. Although patient‐reported outcomes improved similarly following UKA and TKA, UKA more closely preserved native knee kinematics as indicated by the greater similarity of sagittal gait patterns shapes and lower magnitude of coronal angle changes. Clinical Significance Greater preservation of patient‐specific knee kinematics with UKA supports its use in appropriately selected patients and informs the design of targeted, functionally oriented rehabilitation protocols.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".