Humeral Head Reconstruction for Hill‐Sachs Defects: A Biomechanical Comparison of 2 Fixation Techniques for Bone Grafting
Bibliographic record
Abstract
PURPOSE: The purpose of this biomechanical study was to compare anterograde with retrograde screw fixation for allograft reconstruction of Hill-Sachs defects. METHODS: In 8 pairs of fresh-frozen humeral heads, a 40% Hill-Sachs defect was created. The resultant wedge-shaped osteochondral fragment was used as allograft. For each technique, two 3.75-mm screws were used for fixation. To test the strength of fixation, a custom tool was used that would apply load to the graft. By use of a materials testing machine, a staircase cyclic loading protocol was performed (500 cycles at 10, 20, 30, and 40 N) and then load to failure. Graft displacement was measured by an optical tracking system. RESULTS: For the 2 techniques, graft displacement increased with increasing load and increasing number of cycles up to a mean of 0.9 ± 0.42 mm for anterograde fixation and 1.1 ± 0.79 mm for retrograde fixation. This increase was significant within each technique across all 4 loading levels (P < .05). However, there were no significant differences in graft displacement between the 2 techniques at any loading level or number of cycles (P = .16 to P = .96). In addition, the load to failure between the anterograde and retrograde techniques (98.5 N and 95.6 N, respectively) was not significantly different (P = .706). CONCLUSIONS: The initial fixation and failure strength of anterograde and retrograde graft fixation techniques for substantial Hill-Sachs defects do not significantly differ in a biomechanical cadaveric model. CLINICAL RELEVANCE: This biomechanical study supports that in an engaging Hill-Sachs defect, both anterograde and retrograde screw fixation techniques can be used for fixation of humeral head allografts.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".