<i>Editorial Commentary</i> : Causes of Failure After Arthroscopic Rotator Cuff Repair
Bibliographic record
Abstract
Causes of failure after arthroscopic rotator cuff repair include patient factors, tear factors, and surgical factors. Failure may occur at the suture-tendon interface, the bone-tendon interface, or the bone-anchor interface. Low bone mineral density (BMD) in the greater tuberosity has been reported as a prognostic factor for recurrent tears following rotator cuff repair, and although most studies suggest the tendon-to-suture interface as the "weakest link," patients with low BMD may have lower suture anchor pull-out strength. A potential alternative cause of failure is the suture cutting through the greater tuberosity bone in patients with low BMD. Knotless suture bridge constructs or single-row constructs may be more susceptible to a suture cutting through the bone. The knotted suture bridge technique, wherein the medial mattress sutures are tied, may to some extent "shield" against complete cut-through. When bone quality appears poor, a common response is to change the type of anchor, size of anchor, or the location of the anchor. Other factors, such as bone preparation, suture type, suture tensioning, and anchor type (e.g., internal vs external locking), may all potentially affect suture cutting through weak bone.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.017 | 0.015 |
| Insufficient payload (model declined to judge) | 0.017 | 0.015 |
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".