Abnormal neurovascular coupling exists in patients with peritoneal dialysis and hemodialysis: evidence from a multi-mode MRI study
Bibliographic record
Abstract
Background: Neurovascular coupling (NVC), as indicated by a comprehensive analysis of the amplitude of low-frequency fluctuation (ALFF) and cerebral blood flow (CBF), provides mechanistic insights into neurological disorders. Patients undergoing peritoneal dialysis (PD) and hemodialysis (HD) often face cognitive impairment, the causes of which are not fully understood. Methods: ALFF was derived from functional magnetic resonance imaging, and CBF was quantified using arterial spin labeling in a cohort comprising 58 patients with PD, 60 patients with HD and 62 healthy controls. Voxel-based global analysis for both ALFF and CBF, alongside region-based analyses of ALFF-CBF coupling coefficients, were conducted. Additionally, the study explored the correlation between clinical laboratory indices and imaging metrics. Results: Compared with HC, NVC was reduced in the bilateral medial superior frontal gyrus (SFGmed), insula, posterior cingulate cortex (PCC) and caudate (CAU) among dialysis patients. Furthermore, the PD group exhibited lower NVC in the bilateral SFGmed, bilateral PCC and left CAU compared with the HD group. Within the PD group, sodium level was negatively correlated with the ALFF-CBF coupling coefficient in the right insula. Additionally, a positive correlation emerged between the ALFF-CBF coupling coefficient in bilateral SFGmed and the dialysis adequacy. Conclusion: While Montreal Cognitive Assessment scores did not significantly differ between patients with PD and HD, PD group demonstrated poorer NVC in the bilateral SFGmed, bilateral PCC and left CAU. Sodium level and dialysis adequacy may affect NVC in patients with PD.
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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 | 0.001 | 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".