Cerebral Haemodynamics and Cognitive Impairment in Chronic Haemodialysis Patients: A Pilot Study
Bibliographic record
Abstract
Background: Patients with chronic kidney disease (CKD) have a substantially higher risk of developing cognitive impairment (CI) than the general population. Patients with CKD undergoing haemodialysis (HD) treatment also have an elevated risk of developing cerebrovascular and cardiovascular diseases. This study aims to investigate the relationship between the cognitive performance of haemodialysis patients and cerebral and carotid haemodynamic indices. Methods: This study was a non-interventional observational study; the sample consisted of 32 patients (age 65 ± 12 years) undergoing chronic HD treatment. The patients underwent neuropsychological and haemodynamic instrumental investigations, including Supra-Aortic Trunk Echodoppler (SAT) and Transcranial Doppler (TCD). Results: Patients were 17% deficient at Montreal Cognitive Assessment (MoCA), 45% deficient at Frontal Assessment Battery (FAB), 55% deficient at Trail-Making Test-A (TMT-A) and 65% deficient at TMT-B. The TCD investigation detected a decrease in flow (MFV) and an increase in Breath Hold Index (BHI) predominantly in the right cerebral arterial district. The SAT investigation revealed an altered IMT, plaques and the presence of severe carotid stenosis. A strong association between cerebral and carotid indices and cognitive scores was also observed. Correlation analyses reported statistically significant correlations between TMT-A and TMT-B and cerebral flow indices. Conclusions: Among haemodialysis patients, there is a high percentage of cognitive impairment associated and correlated with alterations in cerebral and carotid haemodynamics. Cerebral haemodynamics are a factor to be taken into consideration as a possible pathological mechanism underlying cognitive impairment in haemodialysis.
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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 | 0.000 | 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".