Brain white matter microstructure in end‐stage kidney disease, cognitive impairment, and circulatory stress
Bibliographic record
Abstract
Abstract Introduction : Structural and functional brain white matter abnormalities are poorly characterized in patients with end‐stage kidney disease. Methods : We examined the prevalence of the brain white matter microstructure disruption using diffusion tensor magnetic resonance imaging and its association with hemodynamic performance and cognitive defects in 49 incident hemodialysis (HD) patients and compared these to 25 age‐matched normal controls. We analyzed fractional anisotropy (FA) and mean diffusivity (MD) maps of the images, a voxelwise statistical analysis was done using tract‐based spatial statistics. Hemodynamic assessment was done using extrema points analysis model of continuous blood pressure monitoring. Findings: We found significant white matter damage in HD patients compared with normal controls (peak FA 0.471 ± 0.031 vs 0.486 ± 0.022 P = 0.023, peak MD 0.00194 ± 0.000363 10 −3 mm 2 .s −1 vs 0.00167 ± 0.0003 10 −3 mm 2 .s −1 P = 0.002). There was diffuse pattern of white matter damage in HD patients, which was independent of age, gender, and the presence of ischaemic heart disease and diabetes with significantly lower FA values in HD patients than normal controls (0.467 ± 0.037 vs 0.507 ± 0.026, P < 0.05 corrected for family wise error. HD patients had worse cognitive scores that correlated with white matter damage (for peak FA, Montreal cognitive assessment r = 0.478 P = 0.001, Trail A r = −0.486 P = 0.001, Trail B r = −0.464 P = 0.001; for peak MD, Montreal cognitive assessment r = −0.533 P < 0.001, Trail A r = 0.641 P < 0.001, Trail B r = 0.514 P < 0.001). In a multivariable linear regression analysis that included age, smoking, the presence of ischaemic heart disease, and diabetes mellitus, higher frequency of mean arterial blood pressure extrema points during HD was independently associated with white matter damage (β = −0.296, P = 0.036, Adjusted R 2 for the whole model = 0.400). Discussion: End‐stage kidney disease patients on HD have more brain white matter damage and cognitive impairment than age‐matched controls that are linked to hemodynamic functional measures.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.009 | 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 teacher head, 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".