Clinical and Subclinical Characteristics in Adults with Acute Ischemic Stroke Before Revascularization at E Hospital
Bibliographic record
Abstract
The study aimed to analyze clinical characteristics, subclinical features, risk factors, and causes in patients with acute ischemic stroke before revascularization at E Hospital. Research method: The descriptive study with retrospective and prospective data on 81 patients with acute ischemic stroke before revascularization admitted to E Hospital from November 2020 to April 2023. Results: The mean age of patients was 65 ± 13 years old. The male/female ratio was 1.3/1. 80.2% of the patients were admitted to the Emergency Department less than 3 hours after the onset of symptoms. At admission, the mean Glasgow and National Institutes of Health Stroke Scale (NIHSS) scores were 14.0 ± 1.4 and 11.3 ± 5.3, respectively. On the brain Computerized Tomography (CT) scan of an ischemic stroke, the mean Alberta Stroke Program Early CT Score (ASPECT) score for the cerebral artery blood supply area was 9.16 ± 0.92. Risk factors for stroke commonly included hypertension (64.2%), previous ischemic stroke (22.2%), diabetes (14.8%), and smoking (9.9%). Classification of causes of ischemic stroke according to Trial of ORG 10172 in Acute Stroke Treatment (TOAST): small vessel disease (35.9%), large atherosclerosis artery (22.2%), cardiac embolism (16.0%), and stroke of undetermined source (25.9%). Conclusion: Most patients with acute ischemic stroke were admitted to the hospital in a conscious state with a moderate level of stroke. Most patients with an ASPECT score above 8 had a good prognosis of treatment. Some paraclinical features, such as glucose, LDL-cholesterol, and triglyceride, remained high. The cause of acute ischemic stroke was noted to be caused by small vessel diseases. ASPECT and the time for onset to the hospital were not statistically significant.
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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 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".