<i>Editorial Commentary:</i> Superior Capsular Reconstruction: Indications and Proper Technique Results in Good Outcomes but Reports of Complications
Bibliographic record
Abstract
Superior capsular reconstruction is a minimally invasive option to treat massive irreparable rotator cuff tears. In the appropriately selected patient, available data suggest that while the procedure generally results in improved function, there is a not insignificant risk of complications. Moreover, the rate of complications is likely underestimated given that outcomes are typically published by those with significant technical expertise. The literature supports improved outcomes in patients without significant degenerative change (less than Hamada 3) along with an intact or repairable subscapularis. Graft failure is the most common complication, and appropriate graft selection (ideally at least 4 mm thick) and careful preparation are essential. Additionally, surgeons could consider 3 anchors on the glenoid to provide secure fixation and a double-row transosseous equivalent construct on the humerus. To prevent suture pullout or excessive tension on the graft, it is important to maintain a sufficient border of graft and measure the graft in 30° of forward elevation and 30° of abduction. Additional fixation with posterior side-to-side repair of the graft to the infraspinatus has been reported to improve biomechanical properties of the construct. Existing research is skewed toward low-level evidence at high risk of bias and the reported results of high-volume surgeons. High-quality pragmatic trials are required to truly understand the optimal indications and real-world outcomes of the superior capsular reconstruction.
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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 | 0.005 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.005 | 0.001 |
| Research integrity | 0.032 | 0.028 |
| Insufficient payload (model declined to judge) | 0.011 | 0.012 |
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".