Correlation of Platelet Indices with Severity of Acute Ischemic Stroke in Non-Diabetic and NonHypertensive Patients in Hubli, Karnataka
Bibliographic record
Abstract
BACKGROUND Platelet size, measured as mean platelet volume (MPV), is a marker of platelet function and is positively associated with indicators of platelet activity, including aggregation and release of thromboxane A2, platelet factor 4, and thromboglobulin.1 Larger platelets are metabolically more active, produce more prothrombotic factors, aggregate more easily & act as index of homeostasis and its dysfunction thrombosis.2 The purpose of this study was to examine the relationship between platelet indices and stroke, as well as its severity and outcome. METHODS This was a prospective observational case control study. This study was conducted with 105 non-diabetic, non-hypertensive ischemic stroke patients who had no history of previous thrombotic events and who had not previously taken any antiplatelet medications. These patients were examined within 24 hours of onset of symptoms and severity of stroke was calculated by Canadian neurological scale (CNS). The results were compared with 105 age and sex match controls. RESULTS Mean age of patients was 61.72 ± 12 and of controls was 62.85 ± 10.68. Based on the CNS score, participants were allocated into two groups; the first group were those who had a comprehension deficit (1st group, 43 patients) and the second group were those without a comprehension deficit (2nd group, 62 patients). Mean values for platelet distribution width (PDW) & MPV in 1st group was 18.329 and 12.55 respectively and in 2nd group was 16.98 and 11.48 respectively. The mean value of PDW and MPV for stroke patients was 17.53 ± 0.76 and 11.92 ± 0.58 and was significantly higher than mean value of PDW & MPV respectively in controls, which were 15.47 ± 0.26 and 10.43 ± 0.23. PDW & MPV was found to be significantly associated with severity of motor deficit. CONCLUSIONS Larger studies may be required to determine its utility in day-to-day clinical practice. However, platelet indices can be used for predicting the severity of deficit in patients of acute ischemic stroke. KEYWORDS Platelet Indices, 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".