Pulse wave velocity is associated with cognitive impairment in hemodialysis patients
Bibliographic record
Abstract
Cognitive impairment in hemodialysis patients is common and associated with adverse outcomes. So far, the underlying pathogenesis remains unclear. Therefore, we examined the potential relationship between cognitive impairment and three different categories of risk factors with particular focus on arterial stiffness measured by pulse wave velocity (PWV). A total of 201 chronic hemodialysis patients underwent cognitive testing under standardized conditions using the Montreal Cognitive Assessment (MoCA). Demographic data including cardiovascular risk factors, dialysis-associated factors as well as factors related to chronic kidney disease (CKD) were analyzed. To account for arterial stiffness, PWV was measured by ambulatory blood pressure monitoried with an oscillometric device that records brachial blood pressure along with pulse waves. In our cohort, 60.2% of patients showed pathological MoCA test results indicating cognitive impairment. PWV was significantly associated with cognitive impairment apart from age, educational level, diabetes, and hypercholesterolemia. High prevalence of cognitive impairment in hemodialysis patients was confirmed. For the first time, an association between cognitive impairment and arterial stiffness was detected in a larger cohort of hemodialysis patients. Concerning the underlying pathogenesis of cognitive impairment, current results revealed a potential involvement of arterial stiffness, which has to be further evaluated in future studies.
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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) | 0.001 | 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".