Supraspinatus tendon repair using anchors: a biomechanical evaluation in the rabbit
Bibliographic record
Abstract
BACKGROUND: Arthroscopic rotator cuff repairs are mostly secured with suture anchors and often supplemented by footprint decortication. The objectives of this study were to characterize the strength of bone-tendon healing following anchor repair and assess the effect of channeling the supraspinatus (SSP) humeral footprint 1 week ahead of reattachment surgery. METHODS: One hundred twelve rabbits underwent unilateral detachment of one SSP tendon and were randomly assigned to two groups: channeling the footprint at time of detachment and no channeling. One week later, reattachment was performed using an anchor. The repaired and contralateral shoulders were harvested at 0, 1, 2, or 4 weeks after repair and mechanically tested to failure. Outcome measures included load at failure, stiffness, and site of failure. RESULTS: Anchor fixation had a mean load at failure of 81 ± 32 N and a stiffness of 27 ± 9 N/mm immediately after repair compared to 166 ± 47 N and 66 ± 13 N/mm in the contralateral (both p < 0.05). Mechanical recovery of the reattached SSP tendon was achieved after 4 weeks (221 ± 73 N, 206 ± 59 N, and 198 ± 49 N in the channeling, no channeling, and contralateral groups, respectively, p > 0.05). The dominant site of failure shifted from the footprint at 0/1 week to bone avulsion/mid-substance tear at 4 weeks (p < 0.05). There were no differences in outcomes between the channeling and no channeling groups. CONCLUSIONS: This study is the first of its kind to provide quantitative data on the mechanical properties of the enthesis following anchor repair in a rabbit model. Anchor repair led to rapid and complete restoration of SSP mechanical properties. Further evidence is needed before recommending channeling ahead of repair surgery.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".