Hubungan antara Stroke Iskemik dengan Gangguan Fungsi Kognitif di RSUD Dr. Moewardi
Bibliographic record
Abstract
Background: Ischemic stroke is a disorder of brain function that occur suddenly and caused a blockage in the blood vessel (thromboembolic), resulting in area under experienced ischemic blockage. The most common symptoms of a stroke is sudden weakness of one side of the body on the face, arms, and legs. Other symptoms such as impaired cognitive function. In previous studies of acute ischemic stroke to impaired cognitive function, namely a decline in cognitive function in patients with ischemic stroke . Objective: This study aims to determine the relationship between ischemic stroke with impaired cognitive function. Methods: The design study is observational method with cross sectional study design. The population in this study were stroke patients neurological polyclinic Hospital Dr. Moewardi and for controls taken from patients admitted Dr. Moewardi Hospital through the clinic diagnosed nerve and not a stroke. The sample in this study were all patients with a diagnosis based on CT - scan as ischemic stroke. Large samples of 56 patients with a comparison of cases and controls. The sampling technique is purposive sampling. Data were analyzed using Chi-square using SPSS version 21.0 for Windows. Result: There is a statistically significant relationship ischemic stroke with impaired cognitive function. Respondents in the case group included the category of normal cognitive function by 25 respondents (44.6 %), whereas impaired cognitive function as much as 31 respondents (55.4 %). While the control group of 56 respondents, which decreased cognitive impairment by 2 respondents. The results of Chi-square test of hypothesis obtained significancy 0.000 where p < 0.05. Conclusion: There is a relationship between ischemic stroke with impaired cognitive function in Dr. Moewardi Hospital of Surakarta 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.032 | 0.006 |
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".