Treatment of Partial-Thickness Rotator Cuff Tears With a Resorbable Bioinductive Bovine Collagen Implant: 1-Year Results From a Prospective Multicenter Registry
Bibliographic record
Abstract
BACKGROUND: Surgical treatment of partial-thickness rotator cuff tears remains challenging and controversial, with several traditional options including debridement with acromioplasty, transtendon or in situ repair, and take-down and repair. A resorbable bioinductive bovine collagen implant has shown promise as an alternative treatment option for partial-thickness tears. PURPOSE: Data from a registry were analyzed to further establish that the implant contributes to improved patient-reported outcome (PRO) scores across a large number of patients treated for partial-thickness rotator cuff tears. STUDY DESIGN: Case series; Level of evidence, 4. METHODS: A total of 19 centers in the United States enrolled patients >21 years old with partial-thickness tears of the rotator cuff in a comprehensive prospective multicenter registry. PRO scores were recorded preoperatively and postoperatively at 2 and 6 weeks, 3 and 6 months, and 1 year: American Shoulder and Elbow Surgeons, Single Assessment Numeric Evaluation, Veterans RAND 12-Item Health Survey (physical and mental component scores), and Western Ontario Rotator Cuff scores. Revisions were reported throughout the study. RESULTS: The registry included 272 patients with partial-thickness tears (49 grade 1 tears, 101 grade 2 tears, and 122 grade 3 tears), 241 who underwent isolated bioinductive repair (IBR; collagen implant placed after bursectomy without a traditional rotator cuff repair), and 31 who had take-down and repair with bioinductive augmentation. Patients experienced statistically significant and sustained improvement from baseline for all PRO scores beginning at 3 months. Among patients with grade ≥2 tears, those with take-down and repair had significantly inferior scores at 2 and 6 weeks for most PRO scores as compared with those who underwent IBR, but the difference was no longer significant at 1 year for all but the physical component score of the Veterans RAND 12-Item Health Survey. There were 11 revisions, which occurred at a mean ± SD of 188.7 ± 88.0 days after the index surgery. There were no infections. CONCLUSION: This registry analysis further establishes across a large data set that this resorbable bioinductive bovine collagen implant improves PROs in all grades of partial-thickness tears, whether used as IBR or in conjunction with take-down and repair. IBR may offer improved early clinical outcomes (≤6 weeks) and comparable outcomes at 1 year when compared with a more invasive "take-down and repair" approach.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".