Arthroscopic repair of massive, contracted, immobile tears using interval slides: clinical and MRI structural follow‐up
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to determine clinical and structural outcomes of arthroscopic repair of massive, contracted, immobile rotator cuff tears using interval slides. METHODS: Eleven patients who had rotator cuff tears that were irreparable using standard mobilization techniques, but were repaired using interval slides were reviewed. Patients were evaluated at mean 25.2 months (±10.3) post-operatively utilizing a standardized clinical examination and by magnetic resonance imaging (MRI). RESULTS: American Shoulder and Elbow Surgeons (ASES) and Simple Shoulder Test (SST) scores improved significantly (ASES p = 0.0001; SST p = 0.0001) from pre- to post-operative. Range of motion in forward elevation and external rotation increased from pre- to post-operative, though not significantly. Strength via manual muscle testing improved on forward elevation (p = 0.001) and external rotation (p = 0.007) from pre- to post-operative. Post-operative MRI demonstrated massive re-tearing to the original size in 6 patients (55 %) and intact rotator cuffs with tissue spanning the defects in 5 (45 %) patients. CONCLUSIONS: In patients with massive, contracted, immobile tears, an interval slide technique may be utilized as a salvage procedure. Arthroscopic repair of massive, contracted, immobile rotator cuff tears using interval slide techniques can lead to good clinical and satisfactory structural outcomes. LEVEL OF EVIDENCE: IV.
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".