Altered functional connectivity density in the brains of hemodialysis end-stage renal disease patients: An in vivo resting-state functional MRI study
Bibliographic record
Abstract
BACKGROUND: End-stage renal disease (ESRD) patients usually suffer from a high prevalence of central nervous system abnormalities, including cognitive impairment and emotional disorders, which severely influence their quality of life. There have been many neuroimaging research developments in ESRD patients with brain function abnormalities; however, the dysfunction of the salience network (SN) of them has received little attention. The purpose of this study was to investigate the changes of global functional connectivity density (gFCD) in brains of ESRD patients undergoing hemodialysis using resting-state functional magnetic resonance imaging (re-fMRI). METHODS: re-fMRI data were collected from 30 ESRD patients undergoing hemodialysis (14 men, 38.33±7.44 years old) and 30 matched healthy controls (13 men, 39.17±5.7 years old). Neuropsychological tests including the Montreal Cognitive Assessment (MoCA) and Beck Depression Inventory (BDI) were used to evaluate the neurocognitive and psychiatric conditions of the subjects. Blood biochemistry tests, including hemoglobin level, serum albumin level, blood urea level, serum phosphate, serum calcium, and parathyroid hormone level, and dialysis-related indicators, including blood pressure fluctuations in dialysis, single-pool Kt/V(spKt/V), and ultrafiltration volume of dialysis were obtained from the ESRD patients. A two-sample t-test was used to examine the group differences in gFCD between ESRD patients and healthy controls after controlling for age, gender and education. RESULTS: Compared with healthy controls, ESRD patients exhibited a significantly increased gFCD in the salience network, including the bilateral insula, and dorsal anterior cingulated cortex (dACC), and there was no significant correlation between gFCD and the structural mean grey matter volume in patients for every cluster in the brain regions showing significant different gFCD between the two groups. Furthermore, there were significant negative correlations between the degree of connectivity in the right insula and spKt/V. CONCLUSION: Our findings revealed abnormal intrinsic dysconnectivity pattern of salience network-related regions in ESRD patients from the whole brain network perspective. The negative correlation between the right insula and spKt/V suggested that increased fractional removal of urea may reduce the pathological activity in the insula.
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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 | 0.000 | 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) | 0.001 | 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".