Neuroanatomy and severity of stroke in patients with type A aortic dissection
Bibliographic record
Abstract
BACKGROUND: Strokes are a longstanding complication of acute type A aortic dissection (ATAAD) repair. Understanding the neuroanatomy, mechanism, and severity of stroke will facilitate efforts to improve prediction, prevention, and treatment strategies. METHODS: Retrospective review of patients who sustained stroke from a consecutive series of patients undergoing ATAAD repair. Neuroimaging was interpreted by two stroke neurologists blinded to clinical results. Severity of stroke was assessed by the National Institutes of Health Stroke Scale (NIHSS). Residual disability at 30 days was assessed using the modified Rankin Scale (mRS). RESULTS: Twenty percent (38/189) of patients undergoing repair for ATAAD had stroke (unilateral 58%, bi-hemispheric 42% [p = .33]). All strokes were ischemic. No significant lateralization (right vs. left) was noted with unilateral strokes (26% vs. 32%, p = .67). Etiology of stroke was embolic (58%), hypoperfusion (26%), mixed (11%), and unknown (5%). There were no intraoperative variables that correlated with the neuroanatomy or mechanism of stroke. Preoperative carotid dissection was seen in 40% (n = 15), while postoperatively 10% (n = 4) sustained intracranial large vessel occlusion (LVO). Strokes were moderate or severe (NIHSS ≥ 9) in 97% of cases, with 66% incidence of moderate residual disability (mRS ≥ 3) at 1 month postoperatively. CONCLUSIONS: Strokes associated with ATAAD are severe at presentation resulting in significant disability. One in 10 strokes is due to LVO and potentially amenable to endovascular treatment. Heterogeneity in both location and etiology of stroke makes prevention challenging. Future trials may evaluate the role of early neuroimaging and simultaneous treatment of stroke given advancements in endovascular therapy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".