6-month migration sufficient for evaluation of total knee replacements: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: This updated meta-analysis evaluates the migration pattern of the tibial component of primary total knee replacements measured with radiostereometric analysis (RSA). We aimed to evaluate whether 6-month maximum total point motion (MTPM) values could be used instead of 1-year MTPM for RSA threshold testing and to present the pooled migration patterns for different implant designs that can be used as a benchmark. PATIENTS AND METHODS: The search included all published RSA studies on migration patterns of tibial components until 2023. Study groups were classified according to their prosthesis brand, fixation, and insert (PFI). Sub-analyses were performed to compare the mean tibial component migration patterns of different implant variables, stratified according to fixation. RESULTS: 96 studies (43 new studies), including 197 study groups and 4,706 knees, were included. Most migration occurred within the first 6 postoperative months (126 study groups: mean 0.58 mm, 95% confidence interval [CI] 0.50-0.65), followed by minimal migration between 6 and 12 months (197 study groups: mean 0.04 mm, CI 0.03-0.06), irrespective of the fixation method used. Distinct migration patterns were observed among the different fixation methods. No differences were found in migration patterns among cemented components in any of the sub-group analyses conducted. For uncemented implants, trabecular metal surfaced components seemed to migrate less than porous-coated or uncoated components Conclusion: Based on the small difference between MTPM values at 6 months and 1 year, MTPM at 6 months could be used instead of MTPM at 1 year for RSA threshold testing. The pooled migration patterns can be used as benchmark for evaluation of new implants by defining fixation-specific RSA thresholds when combined with implant survival.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.004 |
| 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) | 0.000 | 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".