The biomechanics of plate repair of periprosthetic femur fractures near the tip of a total hip implant: the effect of cable-screw position
Bibliographic record
Abstract
Optimal surgical positioning of cable-screw pairs in repairing periprosthetic femur fractures near the tip of a total hip implant still remains unclear. No studies in the literature to date have developed a fully three-dimensional finite element (FE) model that has been validated experimentally to assess these injury patterns. The aim of the present study was to evaluate the biomechanical performance of three different implant-bone constructs for the fixation of periprosthetic femoral shaft fractures following total hip arthroplasty. Experimentally, three bone-plate repair configurations were applied to the periprosthetic synthetic femur fractured with a 5 mm gap near the tip of a total hip implant. Constructs A, B, and C, respectively, had successively larger distances between the most proximal and the most distal cable-screw pairs used to affix the plate. Specimens were oriented in 15 degrees adduction, subjected to 1000 N of axial force to simulate the single-legged stance phase of walking, and instrumented with strain gauges. Computationally, a linearly elastic and isotropic three-dimensional FE model was developed to mimic the experimental setup. Results showed excellent agreement between experimental versus FE analysis strains, yielding a Pearson linearity coefficient, R2, of 0.90 and a slope for the line of best data fit of 0.96. FE axial stiffnesses were 601 N/mm (Construct A), 849 N/mm (Construct B), and 1359 N/mm (Construct C). FE surface stress maps for cortical bone showed maximum von Mises values of 74 MPa (Construct A), 102 MPa (Construct B), and 57 MPa (Construct C). FE stress maps for the metallic components showed minimum von Mises values for Construct C, namely screw (716MPa), cable (445MPa), plate (548MPa), and hip implant (154MPa). In the case of good bone stock, as modelled by the present synthetic femur model, optimal fixation can be achieved with Construct C.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".