Does Alignment Technique in Medially Stabilized Total Knee Arthroplasty Affect the Patellofemoral Joint Biomechanics and Patient-reported Outcomes at 1 Year? A Prospective Registry-based Cohort Study
Bibliographic record
Abstract
Background Current femoral components may produce a nonanatomical trochlea position with kinematic alignment (KA). This study compared effects of alignment on patellar tilt and patient-reported outcomes in medially stabilized total knee arthroplasty (MS-TKA). Methods MS-TKA patients from a prospective registry-based consecutive cohort were subdivided by alignment technique and patella resurfacing status. Impact of alignment technique stratified by patellar resurfacing on 1-year patellar tilt was investigated with analysis of variance. For alignment technique impact stratified by patellar resurfacing on 1-year Western Ontario and McMaster Universities Arthritis Index (WOMAC), analysis of covariance including preoperative WOMAC pain and function scores as covariates were performed. Spearman's rank correlation was computed for patellar tilt vs WOMAC pain and function at 1 year. Results 295 MS-TKAs were included: mechanical alignment in 168 (56.9%), patella resurfaced in 137 (46.4%), mean age 68.0 years, mean body mass index 30.6 kg/m 2 . More women had nonresurfaced patellae (74.3%; P = .011), otherwise baseline demographics, radiological parameters, WOMAC, and lateral release rates were similar between groups. At 1 year, patellar tilt was higher for KA vs mechanical alignment (7.31 vs 5.90; P = .028) in both resurfaced and nonresurfaced TKA. No effect of alignment on baseline-adjusted WOMAC at 1 year was found in both resurfaced and nonresurfaced TKA. One-year patellar tilt did not correlate with WOMAC pain (r s = −0.004; P = .954) or function (r s = 0.016; P = .832). Conclusions Despite greater patellar tilt at 1year with KA, this study suggests alignment technique in MS-TKA does not adversely impact patella-femoral joint in a clinically significant manner, leading to similar patient-reported outcomes regardless of patellar resurfacing status.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 0.000 |
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".