Does the use of tibial stem extensions reduce the risk of aseptic loosening in obese patients undergoing primary total knee arthroplasty: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: ) patients with stemmed (ST) versus non-stemmed (NST) tibial implants in primary total knee arthroplasty (TKA). METHODS: A systematic review and meta-analysis were conducted following PRISMA and MOOSE guidelines. Studies reporting a direct comparison between ST and NST tibial implants in obese patients were included. The primary outcome of interest was revision for aseptic loosening. Outcomes were analysed using meta-analysis of relative risk. Risk of bias assessment was performed using the Newcastle-Ottawa Scale for observational studies and the RoB-2 Cochrane tool for randomised studies. RESULTS: Seven studies met the selection criteria, consisting of four cohort studies and three randomised controlled trials. Mean follow up time for the eligible cohort was 62.6 months. Meta-analysis demonstrated a statistically significant reduction in the risk of aseptic revision in the ST group compared with the NST group (risk ratio 0.25, 95% confidence interval 0.07 to 0.92). After removal of all zero-event studies, the results remained in favour of the ST group (risk ratio 0.15, 95% confidence interval 0.03 to 0.64). CONCLUSIONS: This study found that obese patients undergoing TKA with stemmed tibial implants may have a lower risk of aseptic revision compared with those with non-stemmed tibial implants. However, due to the lack of high-quality literature available, our study is unable to draw a definitive conclusion on this matter. We suggest that this topic should be re-evaluated using higher-quality study methods, particularly national joint registries studies and randomised controlled trials.
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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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.033 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".