Cerebral Infarction After Subarachnoid Hemorrhage Contributes to Poor Outcome by Vasospasm-Dependent and -Independent Effects
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The pathogenesis of delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage remains incompletely understood. It is generally assumed that it is caused by angiographic vasospasm. Our aim was to clarify the relationship among angiographic vasospasm, neurological worsening, cerebral infarction, and poor outcome and to investigate whether cerebral infarction also contributes to poor outcome by vasospasm-independent effects. METHODS: This exploratory analysis used data from 413 patients included in the Clazosentan to Overcome Neurological Ischemia and Infarction Occurring After Subarachnoid Hemorrhage (CONSCIOUS-1) trial. We studied the incidence of neurological worsening, cerebral infarction, and poor outcome in patients with and without angiographic vasospasm. Path analysis implemented by structural equation modeling was performed to determine direct and indirect path coefficients. RESULTS: Of the 194 patients with moderate to severe vasospasm, 43% had neurological worsening of any cause, 20% had cerebral infarction, and 46% poor outcome. Path coefficients for direct effects on poor outcome were 0.20 for World Federation of Neurological Surgeons Grade 4 to 5, 0.13 for history of hypertension, 0.19 for angiographic vasospasm, 0.16 for neurological worsening, and 0.11 for new cerebral infarction. Cerebral infarction contributed to poor outcome by vasospasm-dependent and -independent effects. CONCLUSIONS: Our data show that the majority of patients with moderate to severe angiographic vasospasm did not have neurological worsening of any cause or cerebral infarction. Besides, cerebral infarction also has a direct effect on outcome independent of angiographic vasospasm. This suggests that other coexisting factors might be involved in the pathogenesis of delayed cerebral ischemia, which should also be an important research target to improve outcome after subarachnoid hemorrhage.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".