The Correlation of Glial Fibrillary Acid Protein Level to Cognitive Function Outcome in Acute Lacunar Ischemic Stroke Patient
Bibliographic record
Abstract
ABSTRACT : Introduction : Glial fibrillary acidic protein (GFAP) is a filamentous protein found in central nervous system astrocytes. Increased serum GFAP levels are caused by the process of astrogliosis after ischemic stroke and are associated with multisynaptic disorders so that they are at risk of causing cognitive disorders. Objective: To analyze the correlation between GFAP levels and cognitive function output in acute lacunar ischemic stroke patients. Research Methods : Analytical observational with prospective cohort approach. The subjects of this study were Acute lacunar ischemic stroke patients with mild to moderate NIHSS scores. Serum GFAP levels were taken at the onset of 48-72 hours of stroke. Cognitive function was measured using the Indonesian version of MoCA (MoCA Ina) test on the seventh and thirtieth day. Bivariate and multivariate analyzes were performed to assess the correlation between GFAP levels, cognitive functions and the confounding factors. Results: There was a significant correlation between GFAP levels and the MoCA Ina scores on the seventh day (r= -0.32, p=0.044), the thirtieth day (r= -0.398, p=0.011), and improvement in MoCA Ina scores (r= -0.342, p = 0.031). There was a significant correlation between GFAP levels on the executive domain on the seventh day (p= 0.01) and thirtieth day (p= 0.005), visuospatial on seventh day (p= 0.004) and thirtieth day (p= 0.016), language on the thirtieth day (p = 0.005), and memory on thirtieth day (p= 0.001). There was no significant correlation between GFAP levels and improvements in attentional, memory, language, visuospatial, and executive domains. Conclusion: There was a significant correlation between GFAP levels and MoCA Ina scores on the seventh, thirtieth day and the improvement of MoCA Ina scores. There was a significant correlation between GFAP levels with the executive, visuospatial, language, and memory domains. Keywords: cognitive, GFAP, lacunar ischemic stroke, MoCA Ina
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".