Comparison of Different Materials in the Same-Sized Cemented Stems on Periprosthetic Fractures in Bone Models
Bibliographic record
Abstract
Objective: The increasing number of aging patients with total hip arthroplasties (THA) causes an increased incidence of periprosthetic fractures (PPF). The study aimed to evaluate the impacts of two different materials in the same-sized cemented stems on PPF in bone models. Methods: This study compared the maximum rotational torque leading to PPF when stems made of cobalt–chromium–molybdenum (Co–Cr–Mo) alloy and stainless use steel (SUS) were implanted using simulated bone models (Sawbones, 3403). The maximum destruction torque was compared statistically for each material (Co–Cr–Mo alloy vs. SUS stainless steel) in this model, and fracture patterns were examined. Results: The PPF occurred with a spiral propagation from the proximal femur towards the diaphysis, with breakage occurring near the distal end of the stem. There were no significant differences in the destruction torque values between the Co–Cr–Mo alloy (103.0 ± 14.9 Nm) and SUS (98.7 ± 15.1 Nm) samples (p = 0.575). The fractures using the bone models exhibited similar patterns in all specimens, resembling clinical PPF fracture types clinically, specifically Vancouver classification B2. Conclusions: The comparison of the maximum destruction torques of the Co–Cr–Mo alloy and SUS cemented stems in simulating PPF showed no significant differences. The results suggest that the materials of the cemented stems might not significantly affect the occurrence of PPF in THA.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".