The influence of uncemented femoral stem length and design on its primary stability: a finite element analysis
Bibliographic record
Abstract
One of the crucial factors for short- and long-term clinical success of total hip arthroplasty cementless implants is primary stability. Indeed, motion at the bone-implant interface above 40 μm leads to partial bone ingrowth, while motion exceeding 150 μm completely inhibits bone ingrowth. The aim of this study was to investigate the effect of two cementless femoral stem designs with different lengths on the primary stability. A finite element model of a composite Sawbones(®) fourth generation, implanted with five lengths of the straight prosthesis design and four lengths of the curved prosthesis design, was loaded with hip joint and abductor forces representing two physiological activities: fast walking and stair climbing. We found that reducing the straight stem length from 146 to 54 mm increased the average micromotion from 17 to 52 μm during fast walking, while the peak value increased from 42 to 104 μm. With the curved stem, reducing length from 105 to 54 mm increased the average micromotion from 10 to 29 μm, while the peak value increased from 37 to 101 μm. Similar findings are obtained for stair climbing for both stems. Although the present study showed that femoral stem length as well as stem design directly influences its primary stability, for the two femoral stems tested, length could be reduced substantially without compromising the primary stability. With the aim of minimising surgical invasiveness, newer femoral stem design and currently well performing stems might be used with a reduced length without compromising primary stability and hence, long-term survivorship.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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 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".