ArticleFrontiers in neuroscience2024
Cortical structural network characteristics in non-cognitive impairment end-stage renal disease.
Article in Frontiers in neuroscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Hippocampal Volume Mediates the Association Between Serum Ferritin and Cognition in Non-Dialysis End-Stage Renal Disease Patients.Brain and behavior · 2026Article
- Topological disruptions of metabolic brain networks in early-stage chronic kidney disease.BMC medical imaging · 2026Article
- Structural covariance network alterations across the spectrum of cognitive status in Parkinson's disease.Clinical parkinsonism & related disorders · 2026Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Explore alterations in topological features of gray matter volume (GMV) and structural networks in non-cognitive impairment end-stage renal disease (Non-CI ESRD). Materials and methods: Utilizing graph theory, we collected structural magnetic resonance imaging (sMRI) data from 38 Non-CI ESRD patients and 50 normal controls (NC). We compared, and extracted the GMV across subject groups, constructed corresponding structural covariance networks (SCNs), and investigated the alterations in SCNs feature parameters between groups. Results: In Non-CI ESRD patients, The GMV were reduced in several brain regions, predominantly on the left side ( Conclusion: This study reveals that patients with renal failure exhibited subtle changes in brain network characteristics even before a decline in cognitive scores. These changes involve compensatory activation in certain brain regions, which enhances network transitivity to maintain the efficiency of whole-brain network information integration without significant loss. Additionally, the SCNs characteristics can serve as a neuroanatomical marker for brain alterations in Non-CI ESRD patients, offering new insights into the mechanisms of early brain injury in ESRD patients.
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