Low incidence of adverse events or construct failure of a novel high-strength No.2 round suture in rotator cuff repair: An IDEAL Stage 2a assessment retrospective cohort analysis
Bibliographic record
Abstract
Abstract Background Despite technical and material improvements in rotator cuff repair (RCR) clinical and radiological failure remains common. Following suture fixation, tension and footprint compression decrease from time zero. A novel suture (Dynacord, Depuy Synthes) has been designed to shorten when submerged in liquid to maintain tension and increase repair construct security. Methods A retrospective cohort analysis was performed on the PRULO (Patient Reported Outcomes in Upper Limb Surgery) registry for 12 months follow up after RCR using this suture regarding all cause failure, rates of common complications, Quick Disability of the Arm, Shoulder and Hand (QuickDASH), and Western Ontario Rotator Cuff Index (WORC). Summary statistics were generated for patient characteristics and patient-reported outcome measures (PROMs) analysed using multiple imputation and a linear model to assess changes over 12 months follow up. Results A cohort of 236 cases was included for analysis. Complication rates and functional improvements were comparable to literature on similar sutures. At 12 months follow up, all-cause failure occurred in 12% of cases, and mean scores for QuickDASH decreased by 37 and WORC increased by 44, both of which surpass the minimum clinically important difference. Our observed rates of complications are as follows: Infection 2.1%, stiffness/capsulitis 11% and retear 12%. Conclusion The novel suture demonstrated favourable safety and efficacy profiles, with outcomes comparable to those published for commonly used sutures. This study through an IDEAL 2a framework for surgical innovation highlights this suture as safe, effective in mitigating common failure mechanisms and having satisfactory outcomes in RCR.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".