Dataset Information

Gender-Specific Association between Serum Uric Acid and Incident Fundus Arteriosclerosis in Chinese Population: A Retrospective Cross-Sectional Study.

ABSTRACT: Elevated levels of serum uric acid (SUA) were considered to be risk factors for cardiovascular disease, it has been found to be associated with increased arteriosclerosis. The aim of this study was to explore the gender specific relationship between SUA and fundus arteriosclerosis in a healthy population. In a retrospective cross-sectional study, 23474 individuals without diabetes and hypertension were included in the present study. SUA levels were cut to four groups as Q1 to Q4, according to the quartiles. The odds ratio and 95% confidence interval of different SUA levels were estimated by a binomial logistic regression model. A restrictive cubic spline method was used to estimate the dose-response relationship between SUA and fundus arteriosclerosis. Subgroup analysis was performed to find the gender-specific association between SUA and incident fundus arteriosclerosis. In males, after adjusting for confounding factors, the highest SUA level was significantly associated with the risk of incident fundus arteriosclerosis. The OR with 95%CI for Q4 was 1.44(1.18, 1.76), Q1 as a reference. Specially, for females, SUA level was not associated with the incidence of fundus arteriosclerosis. In conclusion, elevated levels of SUA were associated with the incidence of fundus arteriosclerosis in males, but not in females.

SUBMITTER: Liu Q

PROVIDER: S-EPMC7248060 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Publications

Gender-Specific Association between Serum Uric Acid and Incident Fundus Arteriosclerosis in Chinese Population: A Retrospective Cross-Sectional Study.

Liu Qianqian Q Liu Chunxing C Gao Yonghui Y Zhang Xinyan X Yi Nengjun N Cao Jianping J Wang Yamin Y Jiang Yongbin Y Tang Zaixiang Z

Scientific reports 20200525 1

Elevated levels of serum uric acid (SUA) were considered to be risk factors for cardiovascular disease, it has been found to be associated with increased arteriosclerosis. The aim of this study was to explore the gender specific relationship between SUA and fundus arteriosclerosis in a healthy population. In a retrospective cross-sectional study, 23474 individuals without diabetes and hypertension were included in the present study. SUA levels were cut to four groups as Q1 to Q4, according to th ...[more]

PMID: 32451435

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Project description:BackgroundDeep learning algorithms have been built for the detection of systemic and eye diseases based on fundus photographs. The retina possesses features that can be affected by gender differences, and the extent to which these features are captured via photography differs depending on the retinal image field.ObjectiveWe aimed to compare deep learning algorithms' performance in predicting gender based on different fields of fundus photographs (optic disc-centered, macula-centered, and peripheral fields).MethodsThis retrospective cross-sectional study included 172,170 fundus photographs of 9956 adults aged ≥40 years from the Singapore Epidemiology of Eye Diseases Study. Optic disc-centered, macula-centered, and peripheral field fundus images were included in this study as input data for a deep learning model for gender prediction. Performance was estimated at the individual level and image level. Receiver operating characteristic curves for binary classification were calculated.ResultsThe deep learning algorithms predicted gender with an area under the receiver operating characteristic curve (AUC) of 0.94 at the individual level and an AUC of 0.87 at the image level. Across the three image field types, the best performance was seen when using optic disc-centered field images (younger subgroups: AUC=0.91; older subgroups: AUC=0.86), and algorithms that used peripheral field images had the lowest performance (younger subgroups: AUC=0.85; older subgroups: AUC=0.76). Across the three ethnic subgroups, algorithm performance was lowest in the Indian subgroup (AUC=0.88) compared to that in the Malay (AUC=0.91) and Chinese (AUC=0.91) subgroups when the algorithms were tested on optic disc-centered images. Algorithms' performance in gender prediction at the image level was better in younger subgroups (aged <65 years; AUC=0.89) than in older subgroups (aged ≥65 years; AUC=0.82).ConclusionsWe confirmed that gender among the Asian population can be predicted with fundus photographs by using deep learning, and our algorithms' performance in terms of gender prediction differed according to the field of fundus photographs, age subgroups, and ethnic groups. Our work provides a further understanding of using deep learning models for the prediction of gender-related diseases. Further validation of our findings is still needed.

Project description:BackgroundThe relationship between serum uric acid (SUA) and several diabetic complications or co-morbidities remains a matter of debate. The study aims to explore the association between SUA levels and the prevalence of non-alcoholic fatty liver disease (NAFLD), diabetic retinopathy (DR), diabetic nephropathy (DN) and diabetic peripheral neuropathy (DPN) in patients with type 2 diabetes mellitus (T2DM).MethodsA total of 2,809 participants (1,784 males and 1,025 females) were included in this cross-sectional study. Clinical characteristics and the prevalence of each of the four diseases were analyzed based on gender-specific quartiles of SUA levels. The Pearson correlation analysis and linear-regression analysis were used to access the correlation between SUA levels and clinical characteristics. Furthermore, a binary logistic regression analysis was carried out to determine whether SUA was an independent risk factor for each of the four complications.ResultsSUA levels were positively correlated to BMI, BUN, Scr and TG, but negatively associated with eGFR, HDL, FBG, 2h-PG and HbA1c% for the patients with T2DM. The prevalence of NAFLD and DN, but not DR or DPN, were increased with SUA levels from the first to the fourth quartile. Binary logistic regression further disclosed that SUA was an independent risk factor for NAFLD (ORs Male = 1.002, ∗ P = 0.0013; ORs Female = 1.002, ∗ P = 0.015) and DN (ORs Male = 1.006, ∗ P < 0.001; ORs Female = 1.005, ∗ P < 0.001), but not for DR and DPN. After adjustment for the confounders, SUA levels were significantly associated with NAFLD within the 3rd (ORs = 1.829, P = 0.004) and 4th quartile (ORs = 2.064, P = 0.001) for women, but not independently associated with SUA for man. On the other hand, our results revealed increased prevalence of DN for SUA quartile 2 (ORs = 3.643, P = 0.039), quartile 3 (ORs = 3.967, P = 0.024) and quartile 4 (ORs = 9.133, P < 0.001) in men; however, SUA quartiles were significantly associated with DN only for quartile 4 (ORs = 4.083, P = 0.042) in women.ConclusionFor patients with T2DM, elevated SUA concentration is an independent risk factor for the prevalence of NAFLD and DN after adjustment for other indicators, but not DR or DPN.

Project description:ObjectivesDiabetes and other metabolic diseases have been linked to the development of periodontitis, but little research has been done to determine whether serum uric acid (SUA) levels and hyperuricemia play a role. This study aimed to investigate the relationship between SUA, hyperuricemia, and periodontitis.MethodsUsing data from the National Health and Nutrition Examination Survey (NHANES) 2011-2014, we created a nationally representative data set. We used multivariable logistic regression models to assess the relationship between SUA, hyperuricemia, and periodontitis and presented odds ratios (OR) in women and men, respectively.ResultsIn women, adjusted multivariable regression models showed that SUA (4.1-4.3mg/dl) was associated with higher odds of periodontitis (OR = 1.43; 95% confidence interval (CI):1.0 ~ 2.03, p = 0.047) with SUA (≤ 3.3mg/dl) as reference. The risk of periodontitis tended to increase slightly but insignificantly with increasing SUA levels, and the adverse effects occurred only when SUA increased to a certain level, and then reached a plateau. In men, the adjusted OR values for SUA (4.9-5.2mg/dl), SUA (5.3-5.5mg/dl), SUA (5.9-6.2mg/dl), and SUA (6.3-6.5mg/dl) were 0.66 (95% CI: 0.45 ~ 0.96, p = 0.029), 0.58 (95% CI: 0.40 ~ 0.85, p = 0.006), 0.67(95% CI: 0.47 ~ 0.97, p = 0.035), and 0.67 (95% CI: 0.45 ~ 0.99, p = 0.043), respectively, with SUA (≤ 4.3mg/dl) as reference. The elevated SUA levels are protective against periodontitis, but there is a range within which the risk of periodontitis decreases, followed by a non-significant tendency to increase.ConclusionsThe levels of SUA that are linked to the risk of periodontitis. Future prospective longitudinal studies and strategies are required to further confirm whether controlled SUA treatment is an effective adjunct to systematic periodontal therapy and whether SUA can be used as a diagnostic biomarker to assess the risk or progression of periodontitis.

Dataset Information

Gender-Specific Association between Serum Uric Acid and Incident Fundus Arteriosclerosis in Chinese Population: A Retrospective Cross-Sectional Study.

Publications

Gender-Specific Association between Serum Uric Acid and Incident Fundus Arteriosclerosis in Chinese Population: A Retrospective Cross-Sectional Study.

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