Cyclic Loading of Periprosthetic Fracture Fixation Constructs
Bibliographic record
Abstract
BACKGROUND: Femur fractures are a common complication of hip arthroplasty. When the stem is well fixed, fracture fixation is the preferred treatment option. Numerous fixation methods have been advocated, using plates or allograft struts. METHODS: Vancouver type B1 periprosthetic femur fractures were created distal to a cemented hip stem in 15 third-generation composite femurs. The fractures were fixed with (1) a nonlocking plate and allograft strut, (2) a locking plate and allograft strut, or (3) a locking plate alone. The struts were fixed with cables. After fixation, the constructs underwent cyclic loading for 100,000 cycles. Stiffness of the constructs was determined during bending, torsion, and axial compression before and after cyclic loading. Load to failure was also determined. RESULTS: Overall, cyclic loading had little effect on the mechanical properties of these constructs. The two constructs with allografts were significantly stiffer in bending than the construct consisting of only a locking plate. There were no significant differences in axial or torsional stiffness between the constructs. Load to failure of the two constructs with allografts was significantly greater than the locking plate alone. CONCLUSIONS: Allograft strut-plate constructs are stiffer in bending and have a higher load to failure than a stand-alone locking plate. When an allograft plate construct is chosen, locking screw seemed to provide no mechanical advantage. All three constructs tested retained their mechanical characteristics after 100,000 cycles of loading. Our initial concern that the cables fixing the allograft strut would loosen appears unfounded.
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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 | 0.000 | 0.000 |
| 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".