Comparison of periprosthetic femoral fracture torque and strain pattern of three types of femoral components in experimental model
Bibliographic record
Abstract
AIMS: Periprosthetic hip fractures (PPFs) after total hip arthroplasty are difficult to treat. Therefore, it is important to identify modifiable risk factors such as stem selection to reduce the occurrence of PPFs. This study aimed to clarify differences in fracture torque, surface strain, and fracture type analysis between three different types of cemented stems. METHODS: We conducted biomechanical testing of bone analogues using six cemented stems of three different types: collarless polished tapered (CPT) stem, Versys Advocate (Versys) stem, and Charnley-Marcel-Kerboull (CMK) stem. Experienced surgeons implanted each of these types of stems into six bone analogues, and the analogues were compressed and internally rotated until failure. Torque to fracture and fracture type were recorded. We also measured surface strain distribution using triaxial rosettes. RESULTS: There was a significant difference in fracture torque between the three stem types (p = 0.036). Particularly, the median fracture torque for the CPT stem was significantly lower than that for the CMK stem (CPT vs CMK: 164.5 Nm vs 200.5 Nm; p = 0.046). The strain values for the CPT stem were higher than those for the other two stems at the most proximal site. The fracture pattern of the CPT and Versys stems was Vancouver type B, whereas that of the CMK stem was type C. CONCLUSION: 2022;11(5):270-277.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".