Evaluation of Platelet Indices and Low-Density Lipoprotein (LDL) as Predictors of Acute Ischemic Stroke Severity and Outcome
Bibliographic record
Abstract
Background: Platelets play a role in atherosclerosis, inflammation, and thrombosis. Prothrombotic events, activation, aggregation, and adhesion are all increased by elevated mean platelet volume (MPV) and platelet distribution width (PDW) levels; high low-density lipoprotein (LDL) raises the risk of cardiovascular disease. Aims: Investigate the association between platelet indices, lipid profile, stroke severity, and outcome in patients with acute ischemic stroke. Subjects and methods: A prospective case-control study involved 100 acute ischemic stroke patients and 100 controls from Mansoura University Hospitals. Patients underwent neurological assessments, including the National Institutes of Health Stroke Scale (NIHSS), modified Rankin Scale (mRS), and Alberta Stroke Program Early CT Score (ASPECTS). Laboratory investigations included the complete blood count, platelet indices, and lipid profiles. Results: The study involved a population of 63% males and 37% females. The mean of (MPV) and platelet lymphocyte ratio (PLR) were significantly higher in cases than in controls. However, the PDW was significantly lower in cases than in controls. The lipid profile showed significant differences in MPV, PLR, and LDL levels. The mean MPV in anterior circulation stroke (ACS) was 9.3 ± 1.25, while in posterior circulation stroke (PCS) it was 10.2 ± 0.9. The mortality rate in cases was 28%, with a significant difference between cases who died and those who survived regarding MPV and PLR. A significant negative correlation was found between the MPV, PDW, and mortality rate, while a positive correlation was found between the mortality rate and PLR and LDL. Conclusion: Higher platelet indices, LDL, and total cholesterol (TC) in stroke patients had a major effect on patient mortality and stroke severity.
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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 | 0.005 | 0.002 |
| 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 | 0.001 |
| 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".