No differences in functional and clinical outcomes after rehabilitation between modified kinematic and mechanical alignment in total knee arthroplasty: A randomized controlled trial
Bibliographic record
Abstract
PURPOSE: Despite advancements in total knee arthroplasty (TKA), patient dissatisfaction remains notably high (15%-25%). This dissatisfaction will be multifactorial, one of which may be the alignment of the components. Kinematic alignment (KA), aimed at restoring pre-arthritic knee anatomy, is proposed as a promising alternative to mechanical alignment (MA), potentially offering better functional outcomes and improved gait characteristics. METHODS: A randomized controlled trial was conducted involving 100 patients undergoing primary TKA. Patients were randomized into two groups (KA vs. MA) using a navigation-assisted surgical approach, with follow-ups conducted at 1 year post-operatively. Outcomes assessed included patient-reported outcome measures (Knee Society Score, Western Ontario and McMaster Universities Osteoarthritis Index, Visual Analogue Scale and Forgotten Joint Score), radiological alignment and comprehensive gait analysis (kinematics, kinetics and spatio-temporal parameters). RESULTS: Navigation analyses indicated significant post-operative alignment differences, with KA showing significantly more varus tibial (KA: 2.2 ± 2.8° vs. MA: 0.3 ± 0.6°, p < 0.001) and more valgus femoral cuts (KA: -0.7 ± 2.9° vs. MA: 0.3 ± 0.8°, p = 0.02) compared to MA. However, these differences did not translate into significant clinical or functional differences between groups in patient-related outcome measures, gait kinematics, kinetics, or spatio-temporal parameters at the 1-year mark. Both alignment techniques showed similar deviations from healthy gait patterns, particularly reduced knee flexion (mean ROM healthy 57.3°, KA 48.6°, MA 47.8°), and knee valgus during walking (mean maximal valgus healthy 15.2°, KA 10.5°, MA 9.5°). Notably, KA required fewer intraoperative soft tissue releases, suggesting procedural simplicity. CONCLUSION: This study found no significant differences in clinical or functional outcomes between KA and MA despite distinct radiological alignment outcomes after 1-year follow-up. Both approaches yield comparable patient satisfaction and functional performance 1 year post-operatively. KA offers procedural advantages, specifically reduced soft tissue interventions. LEVEL OF EVIDENCE: Level I.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 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".