Impaction allografting—The effect of impaction force and alternative compaction methods on the mechanical characteristics of the graft
Bibliographic record
Abstract
Revision total hip replacement with impaction allografting has an attractive potential for restoring bone stock, however, fractures and implant migration remain problematic. Postoperative graft deformation is believed to contribute to migration. Under compressive loading, the fluid in the graft takes up the load initially through fluid pressure that dissipates over time. Given the short duration of an impaction, we proposed two novel graft compaction techniques that allow more time for fluid flow: holding a compression force constant for 90 s (creep technique), and cycles of compressing the graft to a given force and then holding the displacement constant (cyclic relaxation technique). This study examined the effect of the impaction force on the density and mechanical characteristics of the graft, and explored the potential benefit of the proposed alternative compaction techniques. Increasing the impaction force from "low" to "high" increased graft density by 41%, and this translated to stiffness and shear strength increases of 93 and 164%, respectively. The creep technique improved the stiffness and shear strength by 14 and 16%, respectively, when compared with impaction, while the cyclic relaxation technique did not improve the mechanical properties. Although the creep technique could potentially provide a lower risk of intraoperative fracture over the use of larger impaction forces, any clinical benefit of the creep technique warrants further investigation. Our results point to the importance of maximizing impaction forces in impaction allografting surgery.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".