The Effect of Severe Varus Deformity on Clinical and Radiographic Outcomes in Mechanical Aligned Total Knee Arthroplasty with Medial Stabilizing Technique
Bibliographic record
Abstract
Background: The purpose was to compare the clinical and radiographic outcomes between preoperative mild and severe varus deformity after total knee arthroplasty (TKA) with medial stabilizing technique (MST). Methods: We retrospectively analyzed 158 knees of 125 female patients with a 2-year follow-up who underwent mechanically aligned TKA with MST between April 2018 and February 2021. Patients were divided into two groups; the severe varus group was defined as one with preoperative hip-knee ankle (HKA) angle ≥ 15° and the mild varus group with HKA angle < 15°. Pre- and post-operative clinical outcomes (Western Ontario and McMaster University Osteoarthritis Index, Knee Society Knee Score) and radiographic outcomes (medial proximal tibial angle (MPTA), HKA angle, lateral distal femoral angle (LDFA), joint line distance, and femoral component rotation angle) were compared between the groups. Results: Among the 158 knees analyzed, 131 and 27 were allocated to the mild and severe varus groups, respectively. Preoperative data showed that the MPTA (84.7° ± 2.8° vs. 80.7° ± 3.2°, p < 0.001) was significantly less in the severe varus group. In postoperative data, clinical outcomes were not different between the groups. Joint line distance (18.4 mm ± 2.8 mm vs. 18.6 mm ± 2.7 mm, p = 0.676) was also not significantly different. Femoral component rotation angle (−1.7° ± 1.0° vs. −1.0° ± 1.3°, p = 0.018) was more externally rotated in the severe varus group. Conclusions: Severe varus group showed comparable clinical and radiographic outcomes to that of mild varus group after mechanically aligned TKA with MST.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".