To investigate the correlation between chronic kidney disease (CKD) and the development of neurological disease among pediatric patients in Saudi Arabia. The present retrospective study recruited patients admitted to King Abdulaziz University Hospital during 2018. We reviewed electronic records to collect data on essential demographics including age, gender, and nationality; history of prior CNS disease or related symptoms; results of neurological physical examination; and findings of radiological investigations such as abdominal ultrasound, dimercaptosuccinic acid scan, micturating cystourethrogram, diethylene triamine pentaacetic acid scan, brain computed tomography, and magnetic resonance imaging. The most commonly diagnosed renal pathologies were neurogenic bladder and cystic kidney disease. The most common neurological manifestation was seizure disorder. Males were more frequently affected with neurological sequelae than females. The prevalence of neurological disorders was higher in patients over two years old. The most frequently observed stage of chronic kidney disease was stage 5. Most children who were affected with a neurological disorder required hemodialysis as part of their management plan. Patients with chronic kidney disease are at a high risk of neurocognitive defects. The type of management and renal diagnosis are significant factors that should be considered when anticipating central nervous system involvement in the case of chronic kidney disease.
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http://dx.doi.org/10.3390/children7060059 | DOI Listing |
J Med Internet Res
January 2025
Department of Nephrology, Hunan Key Laboratory of Kidney Disease and Blood Purification, The Second Xiangya Hospital of Central South University, Changsha, China.
Background: Acute kidney injury (AKI) is a common complication in hospitalized older patients, associated with increased morbidity, mortality, and health care costs. Major adverse kidney events within 30 days (MAKE30), a composite of death, new renal replacement therapy, or persistent renal dysfunction, has been recommended as a patient-centered endpoint for clinical trials involving AKI.
Objective: This study aimed to develop and validate a machine learning-based model to predict MAKE30 in hospitalized older patients with AKI.
Kidney360
January 2025
Department of Urology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.
Background: Epidemiological associations between kidney stone disease (KSD) and gastrointestinal disorders have been reported, and intestinal homeostasis plays a critical role in stone formation. However, the underlying intrinsic link is not adequately understood. This study aims to investigate the genetic associations between these two types of diseases.
View Article and Find Full Text PDFDiabetes
January 2025
Centre de recherche, Centre hospitalier de l'Université de Montréal (CRCHUM) and Département de médecine, Université de Montréal, 900 Saint Denis Street, Montréal, QC Canada H2X 0A9.
The role of the intrarenal renin-angiotensin system (iRAS) in diabetic kidney disease (DKD) progression remains unclear. In this study, we generated mice with renal tubule-specific deletion of angiotensinogen (Agt; RT-Agt-/-) in both Akita and streptozotocin (STZ)-induced mouse model of diabetes. Both Akita RT-Agt-/- and STZ-RT-Agt-/- mice exhibited significant attenuation of glomerular hyperfiltration, urinary albumin/creatinine ratio, glomerulomegaly and tubular injury.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
January 2025
Laboratory of Obesity and Aging Research, Cardiovascular Branch, National Heart Lung and Blood Institute, NIH, Bethesda, MD 20892.
Mitochondrial endonuclease G (EndoG) contributes to chromosomal degradation when it is released from mitochondria during apoptosis. It is presumed to also have a mitochondrial function because EndoG deficiency causes mitochondrial dysfunction. However, the mechanism by which EndoG regulates mitochondrial function is not known.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Anaesthesiology, Intensive Care and Pain Medicine, University Hospital Müunster, Müunster, Germany.
Objective: Acute kidney injury (AKI) is a frequent complication in critically ill patients, affecting up to 50% of patients in the intensive care units. The lack of standardized and open-source tools for applying the Kidney Disease Improving Global Outcomes (KDIGO) criteria to time series, requires researchers to implement classification algorithms of their own which is resource intensive and might impact study quality by introducing different interpretations of edge cases. This project introduces pyAKI, an open-source pipeline addressing this gap by providing a comprehensive solution for consistent KDIGO criteria implementation.
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