Abstract 18571: Stroke and Outcomes in Patients with Acute Type A Aortic Dissection
Bibliographic record
Abstract
Background: Stroke is one of the most dreaded complications of type A acute aortic dissection (TA-AAD). However, few data exist on its incidence and association with prognosis. Methods: We evaluated 2202 TA-AAD patients [pts, mean age 61.9 ± 14.4, 1487 (67.5%) male] from the International Registry of Acute Aortic Dissection (IRAD) to determine the incidence and prognostic influence of stroke in TA-AAD. Results: Stroke was present at arrival in 132 (6.0%) TA-AAD pts. Stroke pts were older (65±12 vs. 62±15 yrs; p=.002) and more likely to have hypertension (86% vs. 71%; p=.001) or atherosclerosis (29% vs. 22%; p=.042). While chest pain at arrival was less common (70% vs. 82%; p<.001), stroke pts presented more often with syncope (44% vs. 15%; p<.001), shock (14% vs. 7%; p=.005) or pulse deficit (51% vs. 29%; p=<.001). Arch vessels involvement was more frequent among the stroke pts (68% vs. 37%; p<.001). Stroke pts were treated less frequently by surgery (74% vs. 85%; p<.001). Hospital stay was significantly longer in patients presenting with stroke (median 17.9 versus 13.3 days, p<0.001). Stroke patients demonstrated more frequent in-hospital complications (Table) and higher mortality (adjusted OR 1.62, 95% CI .99-2.65, p=.055) Among hospital survivors, mortality at follow-up was similar in pts with and without stroke (adjusted HR 1.15, 95% CI 0.46-2.89, p=.761). Conclusions: Stroke occurred in greater than 1 of 20 pts with TA-AAD and was associated with increased morbidity and in-hospital, but not long-term mortality. Whether aggressive early intervention will reduce morbidity and improve mortality remains to be evaluated in future studies.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".