The beneficial effect of hydroxyapatite lasts
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: In contrast to early migration, the long-term migration of hydroxyapatite- (HA-) coated tibial components in TKA has been scantily reported. This randomized controlled trial investigated the long-term migration measured by radiostereometric analysis (RSA) of HA-coated, uncoated, and cemented tibial components in TKA. PATIENTS AND METHODS: 68 knees were randomized to HA-coated (n = 24), uncoated (n = 20), and cemented (n = 24) components. All knees were prospectively followed for 11-16 years, or until death or revision. RSA was used to evaluate migration at yearly intervals. Clinical and radiographic evaluation was according to the Knee Society system. A generalized linear mixed model (GLMM, adjusted for age, sex, diagnosis, revisions, and BMI) was used to take into account the repeated-measurement design. RESULTS: The present study involved 742 RSA analyses. The mean migration at 10 years was 1.66 mm for HA, 2.25 mm for uncoated and 0.79 mm for the cemented group (p < 0.001). The reduction of migration by HA as compared to uncoated components was most pronounced for subsidence and external rotation. 3 tibial components were revised for aseptic loosening (2 uncoated and 1 cemented), 3 for septic loosening (2 uncoated and 1 cemented), and 1 for instability (HA-coated). 2 of these cases were revised for secondary loosening after a period of stability: 1 case of osteolysis and 1 case of late infection. There were no statistically significant differences between the fixation groups regarding clinical or radiographic scores. INTERPRETATION: HA reduces migration of uncemented tibial components. This beneficial effect lasts for more than 10 years. Cemented components showed the lowest migration. Longitudinal follow-up of TKA with RSA allows early detection of secondary 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".