Abstract TP294: Sex Differences in Thrombin Generation in Patients With Acute Ischemic Stroke
Bibliographic record
Abstract
Background and Purpose: Sex differences in stroke exist, including variation in stroke risk and outcome. Differences in thrombin generation may contribute to this variation between females and males. To examine this, we assessed sex differences in thrombin generation between females and males with acute ischemic stroke and the relationship to blood cell gene expression. Methods: In 97 patients with acute ischemic stroke thrombin generation was measured by thrombin generation assay. Blood cell gene expression was measured by microarray. Differences in thrombin generation between sexes were identified and the relationship to blood cell gene expression examined. Genes associated with sex differences in thrombin generation were analysed by functional pathway analysis. Results: Females and males had similar overall capacity to generate thrombin. The peak thrombin generated in females was 468.8nM (SD 91.6), comparable to males 479.3 (SD 90.8; p=0.58). Lag time, time to peak thrombin, and endogenous thrombin potential were also similar between females and males. While overall thrombin generation was comparable between females and males with stroke, differences in genes that promote this thrombin generation exist. Females with high peak thrombin had an increase in genes that promote thrombosis, and platelet activation. In contrast, males with high peak thrombin had a decrease in genes involved in thrombus degradation. Conclusion: Females and males with acute ischemic stroke have similar capacity to generate thrombin. However, differences may exist in how this thrombin generation is achieved, with females having increased thrombin signaling, and platelet activation, and males having decreased thrombus degradation. This suggests regulatory differences in thrombosis may exist between females and males that may contribute to sex differences in stroke.
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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".