Time-Dependent Clinical Results of Rotating-Platform Total Knee Arthroplasty According to Mechanical Axis Deviation
Bibliographic record
Abstract
PURPOSE: We hypothesized that the low contact stress (LCS) posterior stabilization system in knees with ≤3° deviation of coronal alignment would provide more favorable clinical outcomes and survival rate over the course of time. MATERIALS AND METHODS: A retrospective study was performed on 253 consecutive cases of primary total knee arthroplasty (TKA). Patients were classified according to the degree of deviation of coronal alignment on the initial postoperative radiograph as Group 1 (≤3° deviation) and Group 2 (>3° deviation). The clinical assessments were performed using the Knee Society score and Hospital for Special Surgery systems and Western Ontario and McMaster Universities index. RESULTS: The survival rate was 97.4% in Group 1 and 96.8% in Group 2. No statistically significant intergroup difference was observed in the clinical scores before surgery and since 1 year after surgery (p>0.05). However, a significant intergroup difference was noted between 6 months to 1 year after surgery (p<0.001). Less than 2 mm radiolucent lines were found more frequently in Group 2. Time-dependent improvement was noted within one year after TKA in both groups. CONCLUSIONS: Most of the expected improvements were achieved at 6 months after surgery in Group 1 and at 1 year after surgery in Group 2. The present study suggests that the LCS system yields time-dependent improvement regardless of coronal alignment deviation.
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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 | 0.001 |
| 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) | 0.002 | 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".