Treatment of Partial-Thickness Rotator Cuff Repairs With A Resorbable Bioinductive Bovine Collagen Implant: 1-Year Results From A Prospective Multi-Center Registry
Bibliographic record
Abstract
Objectives: 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 bioinductive resorbable bovine collagen implant has shown promise as an alternative treatment option for partial-thickness tears. It was our hypothesis that data from a comprehensive, prospective, multi-center registry will further establish the implant’s efficacy and safety across larger numbers of patients. Methods: Nineteen US centers enrolled patients >21 years old with partial-thickness tears of the rotator cuff. Patient-reported outcome (PRO) scores including the American Shoulder and Elbow Surgeons (ASES), single-assessment numeric evaluation (SANE), Veterans RAND 12-Item (VR-12) for both Physical Component Score (PCS) and Mental Component Score (MCS), and Western Ontario Rotator Cuff (WORC) outcome measures were recorded at pre-operative baseline, surgery, and postoperatively at 2 and 6 weeks, 3 and 6 months, and 1 year. 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 over the tear following bursectomy without a traditional rotator cuff repair - FIGURE 1) and 31 tradtitional take-down and repair with supplemental placement of the implant. Patients experienced statistically significant and sustained improvement from baseline for all PRO scores beginning at 3 months (TABLE 1). 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 compared with those undergoing IBR, but the difference was no longer significant at 1 year for all but VR-12 PCS. There were 11 revisions, which occurred at a mean of 188.7 days (standard deviation, 88.0) after index surgery. Conclusions: Efficacy and safety of the implant are further established across a larger data set. IBR may offer improved early clinical outcomes and equivalent long-term results to supplemented take-down and repair, potentially with lower risk of complications. This implant can improve rotator cuff healing and clinical outcomes with minimal revisions. [Table: see text]
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".