The Influence of Implant Position on Final Clinical Outcome and Gait Analysis after Total Knee Arthroplasty
Bibliographic record
Abstract
Abstract The aim of the study was to evaluate the impact of implant component alignment on objective and subjective outcomes after total knee arthroplasty (TKA). The rotation of the femoral component and its influence on the final results were also examined. After exclusion, the study examined 102 patients (mean age, 66.28 years; range, 51–79 years) who had undergone unilateral TKA. All of the operative procedures were performed by one surgeon with one type of implant. One year after the operation, improvements in Knee Society's Knee Scoring System, functional score, Western Ontario and McMaster Universities Osteoarthritis Index, and Visual Analog Scale were observed; however, none showed a significant correlation with any of the parameters analyzed by X-ray or computed tomography (CT) (α, β, γ, δ angles and posterior condylar angle [PCA]). Significant improvements were found for the vast majority of the parameters used for gate analysis at the final follow-up. Significant correlations were found between PCA angle and differences in stance phase, swing phase of the operated limb, and step width (all p = 0.03). No other significant relationships were found between gait parameters and indicators measured by X-ray and CT. None of the analyzed radiographic parameters, including rotation of the femoral component, correlated with final clinical results. Neither femoral internal rotation of 3° to 6°, nor rotation of 0° ± 3° or 0° ± 6° influenced the outcome. One year after TKA, a significant improvement was observed in both functional and gait parameters.
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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 | 0.000 |
| Scholarly communication | 0.001 | 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".