Association of the atherosclerosis, small vessel disease, cardioembolism, other causes with the executive function of the montreal cognitive assessment Indonesia in patients with post ischemic stroke
Bibliographic record
Abstract
Background: ASCO Phenotype classification is a new classification of stroke based on phenotypic system. ASCO classification can evaluate the etiology of ischemic stroke comprehensively to characterize patients using different grade of evidence for the subtype of ischemic stroke. ASCO classification can predict post ischemic stroke cognitive decline. This Study purpose to evaluate the association between ASCO classification with the executive function in post ischemic stroke patients.Methods: This cross sectional study followed by 28 post ischemic stroke patients (men 16, women 12) over 3 months. Mean age 52.82±8.66. Cognitive function was assessed by Montreal Cognitive Assessment Indonesia (MoCA INA).Results: There were 17 patients with grade 1 atherosclerosis (ASCO A1), ten patients with grade 1 small vessel disease (ASCO S1), one patient with grade 1 cardioembolism (ASCO C1) in post ischemic stroke. Grade 1 atherosclerosis (ASCO A1) was significantly associated with executive function decline (p=0.002), naming decline (p=0.05), abstraction decline (p=0.001), memory decline (p=0.002) and orientation decline (p=0.016)). Grade 1 small vessel disease (ASCO S1) was significantly associated with executive function decline (p=0.001) and memory decline (p = 0.001) and abstraction (p=0.001). Grade 1 cardioembolism 1 (ASCO C1) was not significantly associated with cognitive decline.Conclusions: There was significant association between ASCO classification with the executive function of Montreal Cognitive Assestment Indonesia (MoCA INA) in post ischemic stroke patients.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".