RELATIONSHIP BETWEEN LEVEL OF EDUCATION AND POST-STROKE COGNITIVE STATUS IN HOSPITAL-BASED ISCHEMIC STROKE SURVIVORS
Bibliographic record
Abstract
Background: Post-ischemic stroke cognitive decline is significantly affecting the quality of life of its survivors. Its prevalence was about 7.5-72% which was mostly determined by the existing of vascular risk factors and cognitive reserve of the subjects. Level of education is one of determinants of cognitive reserve, a factor that affect the susceptibility of subjects to cognitive decline after experiencing ischemic stroke-related neuronal damage. Since level of education is protective for cognitive function, the intervention on it can reduce the occurrence of cognitive decline. Objective: To investigate the relationship between level of education and cognitive status among hospital-based ischemic stroke survivors. Methods: This cross-sectional study involved post-ischemic stroke outpatients in two hospitals. The data collected in this study were demographic data, including level of education, and clinical data as well. The level of education was categorized into ≥12 years and <12 years groups. Cognitive status was assessed using Montreal Cognitive Assessment in Indonesia version (MoCA-Ina) and subjects with score of 26-30 were normal. The relationship between level of education as well as clinical data and cognitive status were analyzed using chi-square test. Results: There were 166 subjects eligible for this study (n=166). The mean age of subjects was 58 years and 68.67% of them were male. Cognitive decline were found 80.12% of subjects (n=133). The level of education was significantly associated with cognitive status of the subjects and hypertension as well. Conclusion: The level of education had significant relationship with cognitive decline in the hospital-based population of ischemic stroke survivors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".