The aim of this study is to investigate whether GGT variability is able to predict the risk of end-stage renal disease (ESRD). The study subjects were Koreans who conducted health exams supported by the Korean National Health Insurance Corporation during 2009-2012 (baseline). After excluding individuals aged < 40 years, heavy alcoholics, or those with histories of chronic liver disease or ESRD, we followed 6,058,995 individuals. We calculated the average successive variability (ASV) of GGT values during the 5 years before the baseline as a parameter of variability. Using Cox proportional analyses, we evaluated the risk of ESRD according to GGT ASV quartiles, defined as the initiation of renal replacement therapy or kidney transplantation, or December 31, 2016. During 38,663,279.3 person-years of follow-up, 12,057 cases of ESRD were identified. Compared with GGT ASV quartile 1, the risk of ESRD was higher in ASV quartiles 3-4 and increased serially, even after adjustment for several metabolic parameters, baseline renal function, presence of comorbidities, low income, and baseline GGT and hemoglobin level. The fully adjusted hazard ratios (95% confidence intervals) of GGT ASV quartiles 3 and 4 were 1.06 (1.01-1.12) and 1.12 (1.06-1.18), respectively. In conclusion, GGT variability is a putative risk factor for ESRD in Koreans.
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http://dx.doi.org/10.1038/s41598-020-68603-0 | DOI Listing |
Am J Drug Alcohol Abuse
January 2025
Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Kratom is a plant with alkaloids acting at opioid, serotonergic, adrenergic, and other receptors. Consumers report numerous use motivations. To distinguish subgroups of kratom consumers by kratom-use motivations using latent-class analysis.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Department of Gastroenterology, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China.
Background: Gastrointestinal bleeding (GIB) is a severe and potentially life-threatening complication in patients with acute myocardial infarction (AMI), significantly affecting prognosis during hospitalization. Early identification of high-risk patients is essential to reduce complications, improve outcomes, and guide clinical decision-making.
Objective: This study aimed to develop and validate a machine learning (ML)-based model for predicting in-hospital GIB in patients with AMI, identify key risk factors, and evaluate the clinical applicability of the model for risk stratification and decision support.
PLoS One
January 2025
Faculty of Electrical and Control Engineering, Liaoning Technical University, Huludao, Liaoning, China.
To address the susceptibility of conventional vector control systems for permanent magnet synchronous motors (PMSMs) to motor parameter variations and load disturbances, a novel control method combining an improved Grasshopper Optimization Algorithm (GOA) with a variable universe fuzzy Proportional-Integral (PI) controller is proposed, building upon standard fuzzy PI control. First, the diversity of the population and the global exploration capability of the algorithm are enhanced through the integration of the Cauchy mutation strategy and uniform distribution strategy. Subsequently, the fusion of Cauchy mutation and opposition-based learning, along with modifications to the optimal position, further improves the algorithm's ability to escape local optima.
View Article and Find Full Text PDFPLoS One
January 2025
Aston Institute of Health and Neurodevelopment, Aston University, Birmingham, United Kingdom.
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View Article and Find Full Text PDFPLOS Digit Health
January 2025
Institute of Mathematical Statistics and Actuarial Science, University of Bern, Bern, Switzerland.
Risk calculators based on statistical and/or mechanistic models have flourished and are increasingly available for a variety of diseases. However, in the day-to-day practice, their usage may be hampered by missing input variables. Certain measurements needed to calculate disease risk may be difficult to acquire, e.
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