Association of Intracranial Artery Calcification with Cognitive Impairment in Hemodialysis Patients
Bibliographic record
Abstract
BACKGROUND Chronic kidney disease (CKD) is one of risk factors for dementia and cognitive decline. Cardiovascular and dialysis-related factors might also be involved in the mechanism of cognitive impairment in hemodialysis patients. The objective of this study was to investigate whether cardiovascular risk factors including intracranial artery calcification and dialysis-related factors such as fibroblast growth factor 23 (FGF23) might be associated with cognitive impairment in hemodialysis patients. MATERIAL AND METHODS A cross-sectional observational study included patients receiving in-center hemodialysis over 6 months at our hospital. All patients underwent non-contrast computed tomography (CT) examinations. Internal carotid artery (ICA) calcium scores were measured using the Agatston method. The Korean version of the Montreal Cognitive Assessment was used for measurement of cognitive function at each study visit. Serum concentrations of FGF23, osteoprotegerin, and klotho were analyzed using commercial enzyme-linked immunosorbent assay kits. RESULTS This study included 69 patients. Cognitive impairment was observed in 22 patients (31.9%), including 3 patients with dementia. ICA calcium score in patients with cognitive impairment was higher than that in those without cognitive impairment (177.3 versus 87.6, P=0.022). Intracranial artery calcification was significantly associated with cognitive impairment after adjusting for FGF23 and 25-OH vitamin D, but not significant after adjusting for age, FGF23, and 25-OH vitamin D. Low level of FGF23 was associated with cognitive impairment. CONCLUSIONS Intracranial artery calcification and low FGF23 could be associated with cognitive impairment in hemodialysis patients. Longitudinal studies are needed to investigate whether intracranial artery calcification and FGF23 could affect cognitive function of hemodialysis patients.
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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 | 0.001 |
| 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) | 0.001 | 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".