Mechanisms of Stem Subsidence in Femoral Impaction Allografting
Bibliographic record
Abstract
Failure of the femoral component of total hip arthroplasty is often accompanied by bone loss that can pose a significant challenge to the orthopaedic surgeon. Femoral impaction allografting has attractive potential for restoring bone stock in deficient femurs. However, there have been reports of problematic postoperative stem subsidence with this procedure. Subsidence is highly variable among patients, and there is disagreement over the mechanisms that cause it. This article reviews the various mechanisms that can contribute to subsidence in femoral impaction allografting. Variables such as graft density, cement penetration profile, use of synthetic graft substitutes, or other graft additives are discussed, as well as their potential impact on subsidence. Finally, recommendations are made for future studies aiming to reduce the risk of excessive subsidence in femoral impaction allografting.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".