Optimal configuration of a three-rod ortho-bridge system in the treatment of Vancouver type B1 periprosthetic femoral fractures: A finite element analysis
Bibliographic record
Abstract
Introduction and Aim: Periprosthetic femoral fractures (PFF) represent an increasing clinical and economic burden. This study aims to determine the optimal configuration of a bridge-combined internal fixation system in the treatment of Vancouver type B1 PFF, using finite element analysis. Materials and methods: A three-rod ortho-bridge system (OBS) fixation model was used to evaluate the optimal configuration of four target parameters: position of the third rod; intersection angle between the proximal screws; connecting rod diameter; and number of screws used. Femoral displacement and the maximum von Mises stress of the OBS were used as the evaluation indices, to analyze the PFF and to determine the optimal use of an OBS. For each parameter, various candidate options were tested. Results: Finite element analysis revealed that the rate of femoral displacement and the maximum von Mises stress of the OBS were at a minimum when there was a 35 mm downward movement of the third rod from the baseline. Therefore, the optimal position of third rod fixation was 35 mm below the fovea capitis of the femur. The optimal intersection angles between the proximal screws were found to be 71.92° or 84°. A 6 mm diameter connecting rod proved to be most effective. Configuration d, utilizing 7 screws, represented the most clinically appropriate screw number configuration, despite configuration f, utilizing 9 screws, eliciting the best evaluation indices. Conclusion: An OBS used in the above-described configuration is well suited to the characteristics of PFF and provides an effective and reliable means for their treatment.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".