Abstract 18683: Outcomes of Patients Presenting with Acute Type A Aortic Dissection in the Setting of Prior Cardiac Surgery: An Analysis from the International Registry of Acute Aortic Dissection
Bibliographic record
Abstract
Introduction: Prior cardiac surgery can complicate the clinical presentation, diagnosis, and management of patients with type A aortic dissection (TAAAD). This report from the International Registry of Acute Aortic Dissection (IRAD) examines this hypothesis. Methods: 352 of 2289 TAAAD patients (15.4%) enrolled in IRAD had cardiac surgery prior to dissection, including coronary artery bypass grafting (CABG, 34.6%), aortic or mitral valve surgery (38.4%), aortic surgery (44.7%), and other cardiac surgery (18.1%). Results: Comparative differences in baseline demographics, clinical presentation, and management time are shown in Table 1. Patients with prior cardiac surgery were more likely to undergo CABG (p=0.006) or mitral valve replacement (p=0.001) at the time of dissection repair. Total cardiopulmonary bypass time was higher in patients with prior cardiac surgery (p<0.001); no difference was seen in cardiac arrest time (p=0.113) or cerebral ischemia time (p=0.286). In-hospital mortality was significantly higher for patients with prior cardiac surgery (33.5% vs. 24.0%, p70 (RR1.58, 95% CI 1.25-1.99), and medical management of acute dissection (RR 4.79, 95% CI 3.62-6.34). Kaplan-Meier analysis is shown in Figure 1. Conclusion: Prior cardiac surgery not only delays presentation and diagnosis of acute type A dissections, but is also an important adverse risk factor for early and late mortality. <!-- -->
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".