Patients with chronic kidney disease (CKD) have increased risk of cardiovascular events. However, the association of glomerular filtration rate (GFR) and carotid intima-media thickness (CIMT) in non-diabetic CKD patients is under-investigated. This prospective study was conducted at University Clinical Hospital Mostar over a 4-year period and enrolled a total of 100 patients with stage 2 and 4 CKD (50 patients per group). Stage 4 CKD group had significantly higher baseline CIMT values (1.13 ± 0.25 vs. 0.74 ± 0.03 mm, < 0.001), and more atherosclerotic plaques at the study onset (13 (26%) vs. 0 (0%), < 0.001) compared to stage 2 CKD. A statistically significant 4-year increase in GFR (coefficient of 2.51, 3.25, 2.71 and 1.50 for 1-year, 2-year, 3-year and 4-year follow-up, respectively, < 0.05) with non-significant CIMT alterations has been observed in stage 2 CKD. Furthermore, linear mixed effects analysis revealed significant decrease in GFR (coefficient of -6.69, -5.12, -3.18 and -1.77 for 1-year, 2-year, 3-year and 4-year follow-up, respectively, < 0.001) with increase in CIMT (coefficient of 0.20, 0.14, 0.07 and 0.03 for 1-year, 2-year, 3-year and 4-year follow-up, respectively, < 0.001) in stage 4 CKD. GFR and CIMT showed significant negative correlation in both CKD groups during all follow-up phases ( < 0.001). Furthermore, multiple linear regression analysis revealed significant independent prediction of CIMT by baseline GFR (B = -0.85, < 0.001), while there was no significant prediction of CIMT with other covariates. In conclusion, this study demonstrates significant association of GFR and CIMT in non-diabetic stage 2 and stage 4 CKD during the 4-year follow-up.
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http://dx.doi.org/10.3390/life11030204 | DOI Listing |
Lancet Reg Health West Pac
January 2025
Division of Nephrology, National Clinical Research Centre for Kidney Disease, State Key Laboratory of Organ Failure Research, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Background: Early diagnosis of chronic kidney disease (CKD) is crucial for timely intervention to delay disease progression and improve patient outcomes. However, data for clinical characteristics of Chinese patients with undiagnosed, early-stage CKD are lacking.
Methods: REVEAL-CKD is a multinational, observational study using real-world data in selected countries to describe factors associated with undiagnosed stage 3 CKD, time to diagnosis, and CKD management post diagnosis.
Front Med (Lausanne)
January 2025
Department of General Medicine, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research (DMIHER), Wardha, India.
Background: Cardiac autonomic neuropathy (CAN) is a significant complication in chronic kidney disease (CKD), leading to increased morbidity and mortality. Early detection is essential for managing CKD patients effectively, especially those on hemodialysis. This study evaluated the prevalence CAN in CKD and diagnostic accuracy of Bellavere's Score in predicting CAN in CKD patients, including those undergoing hemodialysis.
View Article and Find Full Text PDFActa Clin Croat
December 2023
Department of Digestive Surgery, Faculty of Medicine, Ss Cyril and Methodius University, Skopje, North Macedonia.
Hypertensive nephropathy (HN) is characterized by kidney damage due to chronic high blood pressure. Podocytes play a crucial role in the pathogenesis of HN, thus, nephrin could be important in the early diagnosis of HN. The aim of the study was to investigate the association of urinary nephrin (u-nephrin) levels with clinical and laboratory characteristics in patients with HN and to test diagnostic relevance of u-nephrin as an early biomarker of HN.
View Article and Find Full Text PDFBone Rep
March 2025
Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, United States of America.
High resolution peripheral quantitative computed tomography (HRpQCT) offers detailed bone geometry and microarchitecture assessment, including cortical porosity, but assessing chronic kidney disease (CKD) bone images remains challenging. This proof-of-concept study merges deep learning and machine learning to 1) improve automatic segmentation, particularly in cases with severe cortical porosity and trabeculated endosteal surfaces, and 2) maximize image information using machine learning feature extraction to classify CKD-related skeletal abnormalities, surpassing conventional DXA and CT measures. We included 30 individuals (20 non-CKD, 10 stage 3 to 5D CKD) who underwent HRpQCT of the distal and diaphyseal radius and tibia and contributed data to develop and validate four different AI models for each anatomical site.
View Article and Find Full Text PDFClin Kidney J
January 2025
Faculty of Biology, Medicine and Health, School of Medical Sciences, University of Manchester, Oxford Road, Manchester, UK.
Background And Hypothesis: Mild cognitive impairment and dementia (CI) are common in patients with CKD. We aim to clarify whether and how CKD and CI coexistence increases adverse health outcomes.
Methods: This retrospective observational cohort study was conducted on CKD patients (stages 3-5) from the TriNetX platform.
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