A MULTICENTRE RETROSPECTIVE COHORT STUDY COMPARING CONVENTIONAL DOUBLE-ROW WITH SUTURE BRIDGE FIXATION IN ARTHROSCOPIC ROTATOR CUFF REPAIRS
Bibliographic record
Abstract
Double-row and suture bridge techniques have emerged as effective methods for arthroscopic rotator cuff repair (ARCR). Biomechanical studies have shown that suture bridge technique improves contact areas and mean pressure between the tendon and footprint, which may facilitate healing. However, few studies have directly compared both techniques. Our primary objective was to compare the functional outcomes of double-row versus suture bridge fixation in patients undergoing ARCR. The secondary objectives were to compare healing rates between the two groups as well as investigate any factors associated with healing. This was a secondary analysis of previous randomized controlled trials. Two hundred and ten patients underwent ARCR at one of three tertiary-level university hospitals. A total of 42 patients underwent conventional double-row fixation and 168 underwent suture bridge repair. Functional outcomes measures included the Western Ontario Rotator Cuff Index, the American Shoulder and Elbow Surgeons score, and the Constant score measured at baseline as well as at 3-, 6-, 12- and 24-months post-operatively. Healing rates were determined by ultrasound at 24-months post-operatively. No statistically significant differences were found between outcomes at any of the follow-up times, except a significant difference observed in Constant total score at 24-months in favor for the double-row group (85.5 and 80.5 for double row and suture bridge respectively, p=0.04). The changes from baseline were statistically significant for all outcomes in both groups (p<0.0001). Healing rates were 77.8% for double row and 82.5% for suture bridge (OR, 95% CI:1.34 (0.53,3.38), p=0.53). Multivariable regression analysis showed a strong positive correlation between non-healing rates and size of rotator cuff tear in the sagittal plane (OR, 95% CI:1.97 (1.02,3.78) p=0.043). A statistically significant, but not clinically relevant difference was observed in Constant score at 24-months in favor of double-row fixation. The remaining outcomes measures and healing rates were similar between group. An association was found between non-healing rates and the size of the rotator cuff tear in the sagittal plane.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".