A case-control study to investigate association between serum uric acid levels and paroxysmal atrial fibrillation

Hyperuricemia is associated with metabolic syndrome: A cross-sectional analysis of the National Health and Nutrition Examination Survey (NHANES)

This study aimed to understand the prevalence of hyperuricemia and MetS in the United States and evaluate the potential effect of gender and ethnicity on hyperuricemia and MetS. Data was obtained from National Health and Nutrition Examination Survey (NHANES) between 2011 and 2018. Logistic regression analysis was utilized to investigate the association between hyperuricemia and MetS. A total of 7273 participants with an average age of 47.59 ± 16.92 years old were enrolled in our analysis. Of all the people, 1833 were diagnosed with MetS, with which 547 (29.8 %) were found with hyperuricemia. As for gender, 261 (28.3 %) females were with both Mets and hyperuricemia and this number came to 286 (31.4 %) for males.For population distribution, Non-Hispanic American white, and Hispanic American making up 61.2 % of the cohort. The logistic regression analysis showed that there was a significant association between MetS and hyperuricemia (OR = 2.608, 95 %CI: 2.281-2.982). And the relationship still existed between both males (OR = 2.172, 95 %CI: 1.829-2.579) and females (OR = 3.464, 95 %CI: 2.868-4.185); in addition, participant's ethnicity was also found to play an important role. And the association was found either in Hispanic Americans Non-Hispanic Americans White and black or from other races. In conclusion, our study found a significant association between hyperuricemia and MetS. The higher the uric acid level, the greater risk of people getting MetS and this risk was not influenced by people's gender and ethnicity.

Association between serum uric acid levels and atrial fibrillation in different fasting glucose patterns: A case-control study

BACKGROUND

Previous studies have shown both dysglycaemia and hyperuricemia are associated with an increased risk of atrial fibrillation (AF), while the relationship between serum uric acid (SUA) levels and AF in different fasting glucose patterns (FBG) is unclear. Therefore, this study aimed to determine the association between SUA and AF in different FBG patterns.

METHODS

A total of 1840 patients in this case-control study were enrolled, including 920 AF patients and 920 controls. Patients were divided into three groups according to the different FBG patterns: normoglycemic, impaired fasting glucose (IFG), and diabetes mellitus (DM). Multivariate logistic regression models were performed to evaluate the relationship between SUA and AF in different FBG patterns. Pearson correlation analysis was used to explore the correlation between SUA and metabolic factors. Receiver operating characteristic (ROC) curve models indicated the diagnostic efficiency of SUA for diagnosing AF.

RESULTS

SUA was independently associated with AF after adjusting for all confounding factors in different FBG patterns(normoglycemic: OR=1.313, 95% CI:1.120-1.539; IFG: OR=1.386, 95% CI:1.011-1.898; DM: OR=1.505, 95% CI:1.150-1.970). Pearson's correlation analysis suggested that SUA in AF patients was correlated with several different metabolic factors in different FBG patterns (p<0.05). ROC curve analysis showed that SUA in the normoglycemic group combined with CHD and APOB [AUC: 0.906 (95% CI: 0.888-0.923)], in the IFG group combined with CHD and Scr [AUC: 0.863 (95% CI: 0.820-0.907)], in the DM group combined with CHD and SBP [AUC: 0.858 (95% CI: 0.818-0.898)] had the highest AUC for predicting AF.

CONCLUSION

Findings implied a significant association between SUA and AF in different FBG patterns and provide specific models combined with other factors (CHD, APOB, SCr, SBP), which might contribute to the diagnosis of AF.