Effect of activity level after a posterior-stabilized TKA on the relative bone mineral density measured on standard radiographs in periprosthetic tibial bone: a five-year follow-up study
Bibliographic record
Abstract
Abstract Background: The aim of this study was to evaluate the effect of activity level after a posterior-stabilized TKA on the relative bone mineral density measured on standard radiographs in periprosthetic tibial bone. Methods: A retrospective review identified 121 patients (121 knees，19 men/102 women) that underwent PS TKA with 5-year follow-up. Patients activity level was evaluated by University of California Los Angeles (UCLA) activity score, and the relative BMD in periprosthetic tibial bone was measured by ImageJ software on anteroposterior X-ray images. Clinical assessments included Western Ontario and McMaster Universities (WOMAC), Knee Society, VAS score and UCLA activity score. Nonlinear regression analysis was used to assess the impact of activity levels on periprosthesis bone density.Results: Activity level significantly affected rBMD in the proximal tibia, with the smallest reduction in rBMD observed with moderate activity. The difference in rBMD% between the lateral and medial metaphysis was significant. The regions with a significant difference in rBMD% between the lateral and medial metaphysis were closest to the base plate of the prosthesis. The lateral and medial regions closest to the stem of the prosthesis showed no significant difference in rBMD%.Conclusions: We found that activity level had a significant effect on radiographic measurements of BMD at 1 and 3 years but not at 5 years and moderate activity was associated with a minimal reduction in proximal tibial BMD.
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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 | 0.000 | 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".