Delayed Cerebral Infarction After Aneurysmal Subarachnoid Hemorrhage
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Delayed cerebral ischemia (DCI) is one of the main contributing factors to poor clinical outcome after aneurysmal subarachnoid hemorrhage (SAH). Unsuccessful treatment can cause irreversible brain injury in the form of DCI-related infarction. We aimed to assess the association between the location, distribution, and size of DCI-related infarction in relation to clinical outcome. METHODS: Consecutive patients with SAH treated at 2 university hospitals between 2014 and 2019 (Helsinki, Finland) and between 2006 and 2020 (Aachen, Germany) were included. Size of DCI-related infarction was quantitatively measured as absolute volume (in milliliters). In a semiquantitative fashion, infarction in 14 regions of interest (ROIs) according to a modified Alberta Stroke Program Early CT Score (ASPECTS) was noted. The association of infarction in these ROIs along predefined regions of eloquent brain, with clinical outcome, was assessed. For this purpose, 1-year outcome was measured by the Glasgow Outcome Scale (GOS) and dichotomized into favorable (GOS 4-5) and unfavorable (GOS 1-3). RESULTS: = 0.003) regions were independently associated with unfavorable outcome. DISCUSSION: DCI-related infarction was associated with a 5-fold increase in the odds of unfavorable outcome, after 1 year. Ischemic lesions in specific anatomical regions are more likely to contribute to unfavorable outcome. TRIAL REGISTRATION INFORMATION: Data collection in Aachen was registered in the German Clinical Trial Register (DRKS00030505); on January 3, 2023.
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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) | 0.001 | 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 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".