Effect of mediolateral gap difference on postoperative outcomes in navigation‐assisted total knee arthroplasty using an ultracongruent insert and the medial stabilising technique
Bibliographic record
Abstract
PURPOSE: This study was aimed to compare the clinical, functional, and radiographic outcomes between symmetric and asymmetric extension and mediolateral gap balance after navigation-assisted (NA) total knee arthroplasty (TKA) using ultracongruent (UC) insets and the medial stabilising technique (MST). METHODS: In all, 363 knees of 275 patients who underwent mechanical alignment-target NA TKA with MST between January 2015 and December 2017 were analysed. Patients were divided into balanced (extension mediolateral gap difference ≤ 2 mm) and tight medial (difference ≥ 3 mm) groups. Pre- and postoperative clinical, functional (range of motion, Western Ontario and McMaster University Osteoarthritis [WOMAC] index, Knee Society Knee Score [KSKS], and Knee Society Function Score [KSFS]) and radiographic (hip-knee-ankle [HKA] angle, femoral condylar offset, extension angle [a minus indicates hyperextension], and joint line distance) outcomes were compared between the groups. Student's t- or Chi-squared test was used to compare the outcomes. RESULTS: Among the 363 knees analysed, 279 (77%) were assigned to the balanced group and 84 (23%) to the tight medial group. The preoperative HKA angle was significantly greater in the tight medial group than in the balanced group (9.7° ± 4.1° vs 14.3° ± 4.7°, P < 0.001). The postoperative WOMAC index, KSKS, and KSFS were similar between the groups. The change in the joint line distance was not significantly different (1.5 ± 3.7 vs 2.0 ± 3.3; n.s). CONCLUSION: The clinical, functional, and radiographic outcomes, including joint line distance, were comparable between the tight medial and balanced group after mechanical alignment-targeted UC TKA with MST. LEVEL OF EVIDENCE: Level III, retrospective comparative study.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".