Anchor Design and Bone Mineral Density Affect the Pull-Out Strength of Suture Anchors in Rotator Cuff Repair
Bibliographic record
Abstract
BACKGROUND: Different metal and biodegradable suture anchors are available for rotator cuff repair. Poor bone quality may result in anchor loosening and tendon rerupture. HYPOTHESES: Higher bone mineral density is associated with higher pull-out strength of suture anchors. Depending on anchor placement, pull-out strengths of anchors are different within the greater tuberosity. STUDY DESIGN: Cadaveric biomechanical study. METHODS: Trabecular and cortical bone mineral densities were determined for different regions within the greater tuberosity. Metal screw-type and biodegradable hook-type anchors were cyclically loaded. RESULTS: Mean failure load of metal and biodegradable anchors was 273 N and 162 N, respectively, for the proximal part (P < .01) and 184 N and 112 N, respectively, for the distal part (P < .01). Both types of anchors showed higher failure loads in the proximal-anterior and -middle parts of the greater tuberosity than in the distal part (P < .01). A significant positive correlation was found between cortical bone mineral density and failure load of metal anchors (P < .01). CONCLUSION: Bone quality, anchor type, and anchor placement have a significant impact on anchor failure loads. CLINICAL RELEVANCE: Suture anchors should be placed in the proximal-anterior and -middle parts of the greater tuberosity. In the distal parts, biodegradable hook-like anchors should be used with caution.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.003 | 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".