Biomechanics Analysis of Anterior Cortical Perforation in Antegrade Femoral Nailing
Bibliographic record
Abstract
Hip and femur fractures are a common problem in an aging population. The number of hip and femur fractures are on the rise in Canada. Cephalomedullary fixation is a common method of treating hip and femur fractures, with a known complication of anterior cortical perforation of the distal femur. The literature describes risk factors, such as the influence of the start point at the greater trochanter, but there is no consensus on management. Some cases are treated with restricted weightbearing and other cases with revision surgery. Restricted weightbearing increases perioperative complications including mortality and decreases functional outcomes.\nWe analyze the effect of an anterior, neutral, and posterior start point on the axial, bending, and torsional stiffness of the femur along with the proximal and distal stresses in axial stiffness. We also compare a femur with an anterior cortical perforation of the distal femur.\nThe posterior start point has increased sagittal stiffness compared to the neutral and anterior start points. There is no difference in axial, coronal bending, or torsional stiffness, or proximal or distal stresses. Between a femur with a posterior start point with perforation or without perforation, there is no difference in axial, bending, or torsional stiffness or proximal or distal stresses.\nA case report is presented of an 89 year old woman with a basicervical fracture who underwent cephalomedullary nail fixation and suffered an anterior cortical perforation of the distal femur. Her weightbearing was not restricted postoperatively and she was ambulating at 6 weeks. She did not fracture at the perforation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.004 | 0.001 |
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".