Titanium-Nitride Coating Does Not Result in a Better Clinical Outcome Compared to Conventional Cobalt-Chromium Total Knee Arthroplasty after a Long-Term Follow-Up: A Propensity Score Matching Analysis
Bibliographic record
Abstract
Background: The impact of titanium nitride (TiN) coating on implant components is controversial. TiN coating is proposed as having superior biomechanical properties compared to conventional cobalt-chromium (CoCr) alloy. This study compared long-term clinical data as well as meteoro-sensitivity in patients who underwent total knee arthroplasty (TKA), with either CoCr alloy or TiN coating. Methods: In this retrospective observational study, the clinically approved cemented “low contact stress” (LCS) TKA with conventional CoCr coating, was compared to un-cemented TiN-coated “advanced coated system” (ACS) TKA. Propensity score matching identified comparable patients based on their characteristics in a one-to-one ratio using the nearest-neighbor method. The final cohort comprised 260 knees in each cohort, with a mean follow-up of 10.1 ± 1.0 years for ACS patients and 14.9 ± 3.0 years for the LCS group. Physical examinations, meteoro-sensitivity, and knee scoring were assessed. Results: The clinical and functional Knee Society Score (KSS) (82.6 vs. 70.8; p < 0.001 and 61.9 vs. 71.1; p = 0.011), the postoperative Visual Analogue Scale (VAS) (2.9 vs. 1.4; p = 0.002), and the postoperative Tegner Score (2.6 vs. 2.2; p = 0.001) showed significant intergroup differences. The postoperative Western Ontario & McMaster Universities Osteoarthritis Index (WOMAC) was similar (79.9 vs. 81.3; p = 0.453) between groups. Meteoro-sensitivity of the artificial joint was significantly more prevalent in the ACS patient cohort (56% vs. 23%; p < 0.001). Conclusion: This study suggests that TiN coating does not provide improved clinical outcomes in this patient cohort after a long-term follow-up. Interestingly, sensitivity to weather changes were more correlated with un-cemented ACS implants.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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 teacher head, 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".