Abstract 17722: Does Aortic Resection without an Open Distal and Hemi-Arch Procedure Address all Regions at Risk of Progression in Bicuspid Aortopathy?
Bibliographic record
Abstract
Introduction: Aggressive aortic resection strategies for bicuspid aortic valve (BAV) patients with significant aortopathy are sometimes warranted. 4D flow MRI can identify regions of the aorta with elevated wall shear stress (WSS) that may be at risk of disease progression and thus should be resected during aneurysm repair. This study assesses the efficacy of standard aortic resection practices to include areas at risk as determined by preoperative imaging. Methods: 13 BAV patients (51±17 yrs) undergoing ascending aortic repair received preoperative 4D flow MRI. 10 age-matched normal subjects (50±14 yrs) with healthy tricuspid aortic valves were used to determine the range of physiologically normal WSS. Patient WSS above the healthy 95% confidence interval classified tissue at risk. The surgeon was blinded to the results and postoperative MRI identified the exact region of resection. Results: Preoperative mean aortic diameter was 4.7±0.7 cm; the age-matched control diameter was 2.9±0.5 cm (P<0.001). 38% of patients had severe aortic stenosis. All patients had WSS above the physiologic norm. All 5 patients with open distal and hemi-arch repair had complete removal of “at-risk” tissue as defined by elevated WSS. In all 5 cases, resection with the clamp on would have resulted in residual at risk regions. Of the 8 patients with the occluding clamp left on: 4 had regions at risk that matched/were smaller than the resected regions (-9±6% of resection area) while 4 had remaining tissue at risk (36±22% of resection area). The average at risk region remaining was 14±28% of the resection area. Conclusions: In selected patients with BAV, aggressive resection using open distal/hemi-arch repair is necessary for complete resection of tissue at risk of disease progression. Less aggressive resections without an open distal anastomosis does not always completely remove “at risk” regions. With further validation, 4D flow MRI could be used to guide patient-specific resection strategies.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".