Mid‐Term Outcomes of Navigation‐Assisted Primary Total Knee Arthroplasty Using Adjusted Mechanical Alignment
Bibliographic record
Abstract
OBJECTIVE: The adjusted mechanical alignment (aMA) technique is an extension of conventional mechanical alignment (MA), which has rarely been reported. The purpose of this study was to evaluate mid-term outcomes of navigation-assisted total knee arthroplasty (TKA) using aMA. METHODS: This retrospective cohort study enrolled 63 consecutive patients (77 knees) who underwent navigation-assisted TKA using aMA between September 2017 and October 2019. Fifty-two consecutive patients (61 knees) who underwent TKA using MA during the same period were assessed as the controlled group. The demographic data and perioperative data were recorded. The parameters of resection and soft tissue balance including tibia resection angle, frontal femoral angle, axial femoral angle, joint line translation, medial and lateral gap in extension and flexion position were recorded. Radiographic parameters and functional scores including the Hospital for Special Surgery (HSS) score, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score, and Forgotten Joint Score-12 (FJS-12) were evaluated. Surgery-related complications were recorded. The average follow-up was 3.5 years, with a minimum of 2.4 years. RESULTS: The frontal femoral angle was 2.55° ± 1.08° in aMA group versus 0.26° ± 0.60° in MA group (p < 0.001). The axial femoral angle was 3.07° ± 2.23° external in aMA group versus 2.30° ± 1.70° in MA group (p = 0.027). The lateral flexion gap was wider in the aMA group, with a mean of 0.71 mm more laxity (p = 0.001). Postoperative coronal alignment was 177.03° ± 1.82° in aMA group versus 178.14° ± 1.69° in MA group (p < 0.001). The coronal femoral component angle was 92.62° ± 2.78° in aMA group versus 90.85° ± 2.01° in MA group (p < 0.001). Both aMA-TKA and MA-TKA achieved satisfactory mid-term clinical outcomes. However, the HSS scores at 1 month postoperatively were significantly higher using aMA than using MA (p < 0.001). CONCLUSION: Navigation-assisted TKA using aMA technique obtained satisfactory mid-term clinical outcomes. The aMA technique aims to produce a biomimetic wider lateral flexion-extension gap and minimize releases of soft tissues, which might be associated with better early clinical outcomes than MA technique.
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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 | 0.000 | 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".