Abstract WMP56: Association of Mean Platelet Volume and Its Genetic Variants With Stroke Severity and One-year Mortality in a Polish Stroke Cohort
Bibliographic record
Abstract
Background: Increased mean platelet volume (MPV) is a marker of worse outcomes in cardiovascular disorders, however its prognostic role in patents with ischemic stroke and possible genetic underpinnings remains uncertain. We aimed to determine whether MPV and selected single nucleotide polymorphisms (SNPs) that have been associated with MPV in genome-wide association studies (GWAS) relate to stroke severity, functional outcome on discharge, and one-year mortality in patients with ischemic stroke. Methods: We retrospectively analyzed 577 patients with first ever ischemic stroke. Genotyping of 3 SNPs (rs342293, rs1354034, rs7961894) was performed using a real-time polymerase chain reaction allelic discrimination assay. Multivariable regression was used to determine the association of MPV and MPV-associated SNPs with the National Institutes of Health Stroke Scale (NIHSS) score on admission, modified Rankin Scale (mRS) on discharge, and data on one-year mortality. Results: Rs7961894, but not rs342293 and rs1354034 SNP, was independently associated with MPV in the highest quartile (MPV Q4). MPV Q4 was associated with significantly greater admission NIHSS (p=0.004), poor discharge outcome (p=0.034), and worse one-year mortality (p=0.033). After adjustment for pertinent covariates, MPV Q4 remained independently associated with a greater admission NIHSS score (p=0.025). Patients carrying T>C variant of rs7961894 SNP had a significantly lower one-year mortality as compared to patients with CC genotype (p=0.029; Log-Rank test; Fig.1) and T>C variant of rs7961894 SNP remained an independent marker of a lower one-year mortality (HR=0.30; 95%CI:0.13-0.70; p=0.006) in the studied population. Conclusion: MPV is a marker of stroke severity and rs7961894 is independently associated with MPV in acute phase of ischemic stroke and relates to one-year mortality after stroke.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".