DuraGraft vascular conduit preservation solution in patients undergoing coronary artery bypass grafting: rationale and design of a within-patient randomised multicentre trial
Bibliographic record
Abstract
Introduction: Saphenous vein grafts (SVGs) remain the most often used conduits in coronary artery bypass grafting (CABG). However, they are prone to vein graft disease (VGD) during follow-up, which may compromise clinical outcomes. Injury to the SVG endothelium during harvesting and storage promotes neointimal hyperplasia that can advance to atherosclerosis characterised by SVG failure. This trial investigates the potential benefit of DuraGraft, a novel, one-time intraoperative graft treatment developed to efficiently protect the structural and functional integrity of the vascular endothelium, on the development and progression of VGD in CABG patients. Methods and analysis: (SOC; heparinised saline) using a within-patient randomisation (with one SVG treated with DuraGraft and the other treated with SOC). Besides clinical assessments, patients undergo longitudinal 64-slice or better multidetector CT (MDCT) angiography of paired grafts (within each patient) at 4-6 weeks, 3 months and 12 months. Primary endpoints will be the magnitude of change in mean wall thickness and lumen diameter (stenosis) of paired grafts, at 3 and 12 months, respectively. Besides the evaluation of overall safety, longitudinal assessment of each graft (secondary endpoint) is performed in order to obtain insight into graft behaviour after CABG. Enrolment of 119 patients was successfully completed, and analysis of MDCT angiography follow-up is ongoing with the completed analysis becoming available by end of first quarter of 2018. Ethics and dissemination: The regional ethics committees have approved the trial. Results will be submitted for publication. Clinical trial identifier: NCT02272582 and NCT02774824.
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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 | 0.020 | 0.013 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".