The assessment of the stability of the tibial component of a novel knee arthroplasty system using radiostereometric analysis
Bibliographic record
Abstract
Aims The introduction of a novel design of total knee arthroplasty (TKA) must achieve outcomes at least as good as existing designs. A novel design of TKA with a reducing radius of the femoral component and a modified cam-post articulation has been released and requires assessment of the fixation to bone. Radiostereometric analysis (RSA) of the components within the first two postoperative years has been shown to be predictive of medium- to long-term fixation. The aim of this study was to assess the stability of the tibial component of this system during this period of time using RSA. Patients and Methods A cohort of 30 patients underwent primary, cemented TKA using the novel posterior stabilized fixed-bearing (ATTUNE) design. There was an even distribution of men and women (15:15). The mean age of the patients was 64 years (sd 8) at the time of surgery; their mean body mass index (BMI) was 35.4 kg/m 2 (sd 7.9). RSA was used to assess the stability of the tibial component at 6, 12, and 24 months compared with a six-week baseline examination. Patient-reported outcome measures were also assessed. Results The mean maximum total point motion (MTPM) of the tibial component between 12 and 24 months postoperatively was 0.08 mm (sd 0.08), which is well below the published threshold of 0.2 mm (p < 0.001). Patient-reported outcome measures consistently improved. Conclusion The tibial component of this novel design of TKA showed stability between assessment 12 and 24 months postoperatively, suggesting an acceptably low risk of medium- to long-term failure due to aseptic loosening.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 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".