Serum Vascular Endothelial Growth Factor (Vegf) Levels and Alberta Stroke Program Early CT Score (Aspects) in Ischemic Stroke Patients
Bibliographic record
Abstract
Stroke is the second leading cause of death and disability worldwide. Where the most common occurrence of ischemic stroke is 85% of all stroke cases. Vascular Endothelial Growth Factor (VEGF) is a dimeric glycoprotein with angiogenic and neuroprotective effects. Alberta Stroke Program Early CT Score (ASPECTS) can be used to assess the extent of acute ischemic stroke in the middle cerebral artery territory as a simple semiquantitative instrument. Method a cross-sectional study in acute ischemic stroke patients with an onset of 3-14 days. The VEGF assessed was serum VEGF and ASPECTS assessment to determine the extent of the lesion. Total ASPECT score is 10 points (normal), score > 7 (lesion area < 1/3 MCA), score < 7 (lesion area > 1/3 MCA). Of the 37 patients, the majority of patients were women (62,2%) with hypertension being the most common comorbid. All risk factors had no significant relationship to VEGF levels (p-value>0,005). There was a significant difference between the two ASPECTS categories on serum VEGF levels (p-value=0,001), A significant correlation occurred in serum VEGF levels with ASPECTS (p-value=0,000; r-0,600). Conclusion higher VEGF levels increase cerebral infarction.
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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 | 0.001 |
| 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) | 0.001 | 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".