Background: Kidney stones are a common urologic disease with an increasing incidence year by year, and there are similar influences between gout status and kidney stone incidence. Therefore the contribution of gout status to the incidence of kidney stones is unclear. The aim of this study was to investigate the relationship between gout status and kidney stones and to further explore the causal relationship by Mendelian randomization (MR) analysis.
Method: An epidemiologic study of 49,693 participants in the 2009-2018 National Health and Nutrition Examination Survey (NHANES) was conducted to examine the association between the two. The causal relationship between gout status and kidney stones was assessed by Mendelian randomization analysis of data from the GWAS database.
Result: A total of 28,742 participants were included in the NHANES analysis. We found that gout status was associated with an increased risk of kidney stones [odds ratio (OR) = 1.45 (95%CI, 1.243-1.692); < 0.001]. In the MR analysis, we found a causal relationship between gout status and the risk of developing kidney stones (OR = 1.047, 95%CI, 1.011-1.085, = 0.009).
Conclusion: There may be an association between gout status and kidney stone risk. This finding requires further large-sample studies and adequate follow-up.
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http://dx.doi.org/10.3389/fgene.2024.1417663 | DOI Listing |
BMC Med
December 2024
Department of Rheumatology and Immunology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Background: Pulmonary function is increasingly recognized as a key factor in metabolic diseases. However, its link to gout risk remains unclear. The study aimed to investigate the relationship between pulmonary function and the risk of developing gout and the underlying biological mechanisms.
View Article and Find Full Text PDFCureus
November 2024
Orthopedics, Jawaharlal Nehru Medical College and Hospital, Bhagalpur, IND.
Introduction Arthritis affects a significant number of adults in the United States, leading to pain and limited mobility. This study explores the impact of physical activity on patients with arthritis, including rheumatoid arthritis, gout, lupus, and fibromyalgia. Using data from the Behavioral Risk Factor Surveillance System (BRFSS), it examines how exercise may improve symptoms and quality of life for these patients.
View Article and Find Full Text PDFBMC Musculoskelet Disord
December 2024
School of Clinical Medicine, Jiangxi University of Chinese Medicine, Nanchang City, Jiangxi Province, 330004, China.
Objective: This study aims to investigate the diagnostic, biochemical, and hematological characteristics of patients with gouty arthritis and analyze their correlations with baseline characteristics to guide clinical practice, develop personalized treatment strategies, and improve patient outcomes.
Methods: A single-center retrospective analysis was conducted on 8,344 patients with acute gouty arthritis admitted to our hospital between January 2014 and December 2023. Baseline characteristics and laboratory data, including uric acid, blood glucose, triglycerides, total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), alanine aminotransferase (ALT), aspartate aminotransferase (AST), creatinine, erythrocyte sedimentation rate (ESR), high-sensitivity C-reactive protein (hs-CRP), C-reactive protein (CRP), white blood cell count, neutrophil count, lymphocyte count, monocyte count, fibrinogen, and serum albumin, were collected.
Front Nutr
November 2024
Department of Endoscopy, Shijiazhuang Traditional Chinese Medicine Hospital, Shijiazhuang, China.
Objectives: Gout is associated with hyperuricemia, and serum magnesium levels are negatively correlated with uric acid levels. Magnesium intake is also associated with a reduced risk of hyperuricemia. However, the relationship between the magnesium depletion score (MDS), which represents the systemic magnesium status, and gout is unclear.
View Article and Find Full Text PDFJ Inflamm Res
November 2024
Department of Public Health and Institute of Public Health, Chung Shan Medical University, Taichung, Taiwan.
Purpose: We assessed the risk of gout in the Taiwan Biobank population by applying various machine learning algorithms. The study aimed to identify crucial risk factors and evaluate the performance of different models in gout prediction.
Patients And Methods: This study analyzed data from 88,210 individuals in the Taiwan Biobank, identifying 19,338 cases of gout and 68,872 controls.
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