PRIMARY TOTAL KNEE ARTHROPLASTY USING A LONG STEM TIBIAL COMPONENT
Bibliographic record
Abstract
Introduction The tibial component of a total knee arthroplasty is subjected to eccentric medial and lateral plateau tibial loading during various phases of stance. The resultant coronal planar tilting forces may provoke early subsidence and loosening. The addition of a long non cemented stem is postulated to act as an outrigger, diminishing the rate of aseptic loosening. Methods Two hundred and thirteen primary total knee arthroplasties using proximally cemented tibial components with long non cemented Pressfit stems have been reviewed. Stem lengths varied from 110 mm to 140 mm. Patients were seen at an average of 8.7 years after surgery (two to 13 years) and were assessed using the Knee Society (IKS) pain and function scores, IKS radiographic analysis and Short Form-12 and Western Ontario Macmasters University Osteoarthritis Index (WOMAC questionnaires). Results Average range of motion was 115° at latest follow-up. The average IKS pain and function scores at the time of assessment were 90 and 89 respectively. Radiographic assessment revealed no case of tibial implant loosening. Kaplan-Meier survivorship was 98.6% at 13 years. Conclusions The results lend clinical support to the known theoretical advantages of adding a stem to the tibial component in primary knee arthroplasty. In relation to the conduct of this study, one or more the authors have received, or are likely to receive direct material benefits.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".