Correlation between Chronic Kidney Disease Severity and Cognitive Function
Bibliographic record
Abstract
Chronic kidney disease (CKD) is an independent risk factor for cognitive impairment in all domains, especially delayed memory and executive function. The purpose of this study was to determine the correlation between chronic kidney disease severity and cognitive function. This study used a cross-sectional design in stage III, IV, and V CKD patients in the Nephrology Polyclinic of Haji Adam Malik Central General Hospital. Cognitive function tests were performed using the Montreal Cognitive Assessment (MoCA INA), digit span, and Trail Making Test A & B. The Spearman test was used to analyze the correlation between CKD severity and cognitive function. This study involved 45 chronic kidney disease patients consisting of 28 (62.2%) males and 17 (37.8%) females with a mean age of 49.67±12.18 years. The results of statistical analysis showed that there was a significant positive correlation between CKD on the MoCA-INA examination (r=0.618, p=<0.001), FDS (r=0.414, p=0.005), there was a significant negative correlation on the TMT A time examination (r=-0.425, p=0.004), TMT A error (r=-0.497, p=0.001), TMT B time (r=-0.618, p=<0.001), TMT B error (r=-0.370, p=0.012). The results of this study prove a significant correlation between the severity of CKD and cognitive function.
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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 | 0.001 | 0.003 |
| 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 | 0.000 |
| 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".