Abstract 18106: Short- and Long-Term Outcomes of Patients With Type A Acute Aortic Dissection and Cardiogenic Shock: Contemporary Results From the International Registry of Acute Aortic Dissection (IRAD)
Bibliographic record
Abstract
Background: Shock is a highly dreaded complication of type A acute aortic dissection (TAAAD). However, few data exist on its incidence and association with prognosis. Methods: We evaluated 2704 TAAAD patients [mean age 61.4 ± 14.5, (67.6%) male] from the International Registry of Acute Aortic Dissection. Results: Shock was present at arrival in 407 (15.1%) TAAAD patients. These patients demonstrated no difference in age (61.5 ± 15.2 with shock vs. 61.4 ± 14.4 years without; p=0.873), but were more likely to have history of hypertension (83.1% vs. 73.0%; p<0.001), atherosclerosis (36.5% vs. 21.7%, p<0.001) and diabetes (12.3% vs. 7.0%, p=0.001) than patients without shock. They had more surgical management (90.9% vs. 86.0%; p=0.007). In-hospital complications such as hypotension (49.8% vs. 28.6%; p<0.001), coma (11.4% vs. 5.8%; p<0.001), tamponade (33.6% vs. 18.2%; p<0.001) and myocardial ischemia/infarction (19.7% vs. 13.7%; p=0.006) were more common among shock patients. Overall in-hospital mortality (30.2% vs. 23.9%; p=0.007) and mortality by management (surgical: 24.6% vs. 19.1%; p=0.015; medical: 88.9% vs. 53.3%, p<0.001) were higher among shock patients. Independent predictors of in-hospital mortality in shock patients are displayed in Table 1. Among hospital survivors, Kaplan-Meier estimates of follow-up mortality were similar between groups (p=0.609). Conclusions: Shock occurred in 15.1% of patients with TAAAD and was associated with increased in-hospital morbidity and mortality, but not long-term 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 | 0.000 |
| 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) | 0.001 | 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".