Fracture Load for Periprosthetic Femoral Fractures in Cemented Versus Uncemented Hip Stems: An Experimental In Vitro Study
Bibliographic record
Abstract
This cadaveric study examined fracture loads in cemented and uncemented hip stems. Additionally, individual data and bone quality were analyzed and correlated to fracture patterns and fracture load. Cemented or uncemented hip stems were implanted in a randomized fashion in 10 matched paired fresh-frozen femora (donor median age, 78 years, and donor median weight, 74.2 kg). Bone density was measured before the femurs were fractured under load (maximum load of 10,000 N), and fracture patterns were analyzed according to the Vancouver and Johansson classification systems. In the uncemented group, all of the femurs fractured with a median load of 2625 N (range, 1725-7647 N). In the cemented group, 5 femurs fractured with a median maximum load of 9127 N (range, 2845-10,000 N) and 5 femurs did not fracture with a maximum load of 10,000 N. Fracture load corresponded to 4 times and 8.8 times body weight in the uncemented and cemented groups, respectively. Fracture patterns corresponded to Vancouver type A fractures in uncemented stems and Vancouver type C fractures in cemented hip stems. Analysis showed a significant correlation between fracture load and bone density in the uncemented group, whereas there was no correlation in the cemented group. Patients with poor bone quality treated with an uncemented hip stem are at higher risk for periprosthetic fractures; therefore, we recommend cemented stems in this group of patients. Cementation appears to protect against periprosthetic fractures, probably from internal stiffening of the femoral cavity.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".