Cerebral Vasospasm after Subarachnoid Hemorrhage: Putative Role of Inflammation
Bibliographic record
Abstract
Cerebral vasospasm is a common, formidable, and potentially devastating complication in patients who have sustained subarachnoid hemorrhage (SAH). Despite intensive research efforts, cerebral vasospasm remains incompletely understood from both the pathogenic and therapeutic perspectives. At present, no consistently efficacious and ubiquitously applied preventive and therapeutic measures are available in clinical practice. Recently, convincing data have implicated a role of inflammation in the development and maintenance of cerebral vasospasm. A burgeoning (although incomplete) body of evidence suggests that various constituents of the inflammatory response, including adhesion molecules, cytokines, leukocytes, immunoglobulins, and complement, may be critical in the pathogenesis of cerebral vasospasm. Recent studies attempting to dissect the cellular and molecular basis of the inflammatory response accompanying SAH and cerebral vasospasm have provided a promising groundwork for future studies. It is plausible that the inflammatory response may indeed represent a critical common pathway in the pathogenesis of cerebral vasospasm pursuant to SAH. Investigations into the nature of the inflammatory response accompanying SAH are needed to elucidate the precise role(s) of inflammatory events in SAH-induced pathologies.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".