Abstract 46: RNA Expression Profiles From Whole Blood Associated With Vasospasm in Patients With Subarachnoid Hemorrhage
Bibliographic record
Abstract
Background and Purpose: Though there are many biomarker studies of plasma and serum in patients with aneurysmal subarachnoid hemorrhage (SAH), few have examined cells in blood that might contribute to vasospasm and delayed ischemic neurological deficits (DIND). In this study we evaluate inflammatory and prothrombotic pathways by examining RNA expression in whole blood (including leukocytes, platelets) of SAH patients with vasospasm compared to those without vasospasm. Methods: Adult patients with aneurysmal SAH admitted to UCSF from 2003 to 2010 were enrolled. Patients with vasospasm (n=29) and without vasospasm (n=21) were matched for sex, race/ethnicity and aneurysm treatment method. Diagnosis of vasospasm was made by angiography. RNA expression was measured by Affymetrix Human Exon 1.0 ST Arrays. SAH patients with vasospasm were compared to those without vasospasm by ANCOVA to identify differential gene expression, exon expression and alternatively spliced transcript expression. Analyses were adjusted for age, batch, and days after SAH. Results: At the gene level there were 276 differentially expressed between SAH with vasospasm compared to patients without (P<0.05,
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".