Comparison of clinical outcomes of arthroscopic rotator cuff repair utilizing suture-bridge procedures with or without medial knots: a meta-analysis
Bibliographic record
Abstract
PURPOSE: This investigation aimed to compare the medical efficacy of the knotted and knotless suture-bridge procedures in rotator cuff repair. METHODS: The Pubmed, Embase, and Cochrane Library datasets were searched for all available publications comparing the medical results of arthroscopic rotator cuff repairs utilizing knotted or knotless suture-bridge procedures. Two researchers utilized Newcastle-Ottawa Scale and Cochrane risk-of-bias tool to evaluate the included studies. Employing Revman 5.3 software, meta-analysis was conducted following the PRISMA reporting guideline. RESULTS: Eleven investigations with 1083 patients were considered suitable for the final meta-analysis. 522 individuals were assigned to the knotted group, whereas 561 were assigned to the knotless group. No statistical difference was found between the knotted and knotless groups, regarding VAS score (WMD, 0.17; 95% CI, - 0.10 to 0.44; P = 0.21); Constant score (WMD, -1.50; 95% CI, - 3.52 to 0.52; P = 0.14); American Shoulder and Elbow Surgeons Shoulder (WMD, -2.02; 95% CI, - 4.53 to 0.49; P = 0.11); University of California Los Angeles score (WMD, -0.13; 95% CI, - 0.89 to 0.63; P = 0.73); ROM of flexion (WMD, 1.57; 95% CI, - 2.11 to 5.60; P = 0.37), abduction (WMD, 1.08; 95% CI, - 4.53 to 6.70; P = 0.71) and external rotation (WMD, 1.90; 95% CI, - 1.36 to 5.16; P = 0.25); re-tear rate (OR, 0.74; 95% CI, 0.50 to 1.08; P = 0.12), and medical complications (OR, 0.90; 95% CI, 0.37 to 2.20; P = 0.82). CONCLUSION: For arthroscopic rotator cuff repairs, there were no statistical differences in medical results among knotted and knotless suture-bridge procedures. Overall, both techniques showed excellent clinical outcomes and could be safely utilized to treat rotator cuff injuries.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.016 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.054 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".