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Background and Objectives@#The association between bilirubin and atrial fibrillation (AF) has been evaluated previously in observational studies but with contradictory results. This study evaluated the causal association between serum bilirubin level and AF using Mendelian randomization (MR) analysis. @*Methods@#This cross-sectional study includes 8,977 participants from the Dong-gu Study.In the observational analysis, multivariate logistic regression was performed to evaluate the association between bilirubin and prevalent AF. To evaluate the causal association between bilirubin and AF, MR analysis was conducted by using the UGT1A1 rs11891311 and rs4148323 polymorphisms as instrumental variables. @*Results@#Elevated serum bilirubin levels were associated with an increased risk for AF in observational analysis (total bilirubin: odds ratio [OR], 1.31; 95% confidence interval [95% CI], 1.15–1.48 per 1 standard deviation [SD]; direct bilirubin: OR, 1.31; 95% CI, 1.18–1.46 per 1 SD), whereas the genetically predicted serum bilirubin levels in MR analysis did not show this association (total bilirubin: OR, 1.02; 95% CI, 0.67–1.53 per 1 SD; direct bilirubin: OR, 1.03; 95% CI, 0.61–1.73 per 1 SD). @*Conclusions@#Genetically predicted bilirubin levels were not associated with prevalent AF.Thus, the observational association between serum bilirubin levels and AF may be noncausal and affected by reverse causality or unmeasured confounding.
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Objectives@#This study aimed to evaluate the potential interaction between kidney function and the non-linear association between serum calcium levels and cardiovascular disease (CVD) mortality. @*Methods@#This study included 8927 participants enrolled in the Dong-gu Study. Albumin-corrected calcium levels were used and categorized into 6 percentile categories: 97.5th. Restricted cubic spline analysis was used to examine the non-linear association between calcium levels and CVD mortality. Cox proportional hazard regression was used to estimate hazard ratios (HRs) for CVD mortality according to serum calcium categories. All survival analyses were stratified by the estimated glomerular filtration rate. @*Results@#Over a follow-up period of 11.9±2.8 years, 1757 participants died, of whom 219 died from CVD. A U-shaped association between serum calcium and CVD mortality was found, and the association was more evident in the low kidney function group. Compared to the 25.0-50.0th percentile group for serum calcium levels, both low and high serum calcium tended to be associated with CVD mortality (97.5th: HR, 2.56; 95% CI, 0.76 to 8.66) in the low kidney function group. In the normal kidney function group, a similar association was found between serum calcium levels and CVD mortality (97.5th: HR, 1.65; 95% CI, 0.70 to 3.93). @*Conclusions@#We found a non-linear association between serum calcium levels and CVD mortality, suggesting that calcium dyshomeostasis may contribute to CVD mortality, and kidney function may modify the association.
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This study aimed to investigate the prevalence of depression among Koreans living in urban and rural areas, stratified by socioeconomic status. The study included 216,765 participants from the 2017 Korean Community Health Survey. Depressive symptoms were assessed using the PHQ-9, with a score of 10 or higher indicating depressive symptoms. Residences with the words Eup and Myeon in their addresses were categorized as rural areas, and residences with Dong in their addresses as urban areas. Socioeconomic status was evaluated by household income and education level. A Poisson regression analysis with sampling weights was conducted and adjusted for demographic, lifestyle, socioeconomic status, and comorbidity. The adjusted prevalence rate of depressive symptoms was 3.33% (95% CI, 3.21-3.45) in urban areas and 2.59% (95% CI, 2.43-2.74) in rural areas. The prevalence of depressive symptoms in urban areas was 1.29 times (95% CI, 1.20-1.38) higher than in rural areas. The prevalence rate ratio for depressive symptoms in urban areas compared to rural areas sorted by monthly incomes was 1.39 (95% CI, 1.28-1.51) for less than 2 million won, 1.22 (95% CI, 1.06-1.41) for 2 to 3.99 million won, and 1.09 (95% CI, 0.90-1.32) for more than 4 million won, and the urban-rural difference was more evident in lower household income subjects (p for interaction=0.033). However, urban-rural differences did not differ according to sex, age, or education level. In conclusion, we found urban-rural differences in depressive symptoms in a representative sample of Koreans, and revealed that these differences may vary according to income level. These results suggest that mental health policy must consider the health disparities according to residence and income.
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Background@#We investigated the extent of regional disparity of recurrent falls. In addition, we examined the association between particulate matter (PM) and recurrent falls and the association between regional disparity of recurrent falls and regional PM levels.Method: We used data from Korea Community Health Survey 2019 that included 204,395 participants from 237 municipal districts. The independent variables were the annual average PM10 and PM2.5 concentrations measured at the air quality measuring stations in each municipal district. The outcome variable was the experience of falls more than twice in the previous year. Multilevel analyses were conducted to estimate the association between regional PM10 and PM2.5 levels and recurrent falls. @*Results@#The regional variation was greater in the young people than that in the older people. PM10 and PM2.5 levels were positively associated with recurrent falls after adjusting for individual and regional covariates. These associations were more evident in the older group than in the young. PM10 and PM2.5 explained 2.82% and 3.33% of the remaining regional variance in models with individual and regional confounders, respectively. These proportions were greater in the older group (PM10 and PM2.5; 4.73% and 5.27%) than those in the younger age group (PM10 and PM2.5, 0.80% and 1.39%). @*Conclusion@#PM concentration was associated with recurrent falls even after accounting for other regional variables and individual-level differences. Moreover, there were regional differences in the occurrence of falls, and the PM concentration explained a part of the gap, but the gap was explained more in the older group than in the young
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Background and Objectives@#Previous observational studies presented a positive association between alcohol and atrial fibrillation (AF). However, previous studies using genetic polymorphisms on the causal relationship between alcohol consumption and AF have reported conflicting results. This study aimed to evaluate the causality between alcohol consumption and AF using the aldehyde dehydrogenase 2 (ALDH2) rs671 polymorphism, which is the genetic variant with the most potent effect on drinking behavior. @*Methods@#A total of 8,964 participants from the Dong-gu Study were included in the present study. The causal association between alcohol consumption and AF was evaluated through a Mendelian randomization (MR) analysis using the ALDH2 rs671 polymorphism as an instrumental variable. @*Results@#No significant relationship between alcohol consumption and AF was found in the observational analysis. However, the genetic analysis using the ALDH2 polymorphism showed a significant association in men. In the MR analysis, genetically predicted daily alcohol consumption was positively related to AF. @*Conclusions@#MR analysis revealed a significant association between the amount of alcohol consumption and AF, which suggests that the association may be causal.
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Background@#Several studies have reported conflicting results regarding the relationship between alcohol consumption and cortisol levels. However, the causality between alcohol consumption and cortisol levels has not been evaluated. @*Methods@#This study examined 8,922 participants from the Dong-gu Study. The aldehyde dehydrogenase 2 (ALDH2) rs671 polymorphism was used as an instrumental variable for alcohol consumption. The association between the genetically predicted alcohol consumption and cortisol level was evaluated with Mendelian randomization (MR) using two-stage least squares regression. @*Results@#Alcohol consumption was positively associated with the serum cortisol level in both sexes in the observational analysis. In the MR analysis, the genetically predicted alcohol consumption was positively related to the cortisol level in men, with cortisol levels increasing by 0.18 µg/dL per drink per day. However, there was no relationship in women in the MR analysis. @*Conclusion@#The predicted alcohol consumption according to the ALDH2 rs671 polymorphism was positively related to the cortisol levels, suggesting a causal relationship between alcohol consumption and cortisol levels.
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Background@#Several studies have reported conflicting results regarding the relationship between alcohol consumption and cortisol levels. However, the causality between alcohol consumption and cortisol levels has not been evaluated. @*Methods@#This study examined 8,922 participants from the Dong-gu Study. The aldehyde dehydrogenase 2 (ALDH2) rs671 polymorphism was used as an instrumental variable for alcohol consumption. The association between the genetically predicted alcohol consumption and cortisol level was evaluated with Mendelian randomization (MR) using two-stage least squares regression. @*Results@#Alcohol consumption was positively associated with the serum cortisol level in both sexes in the observational analysis. In the MR analysis, the genetically predicted alcohol consumption was positively related to the cortisol level in men, with cortisol levels increasing by 0.18 µg/dL per drink per day. However, there was no relationship in women in the MR analysis. @*Conclusion@#The predicted alcohol consumption according to the ALDH2 rs671 polymorphism was positively related to the cortisol levels, suggesting a causal relationship between alcohol consumption and cortisol levels.
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Objective@#To present new classification methods of knee osteoarthritis (KOA) using machine learning and compare its performance with conventional statistical methods as classification techniques using machine learning have recently been developed. @*Methods@#A total of 84 KOA patients and 97 normal participants were recruited. KOA patients were clustered into three groups according to the Kellgren-Lawrence (K-L) grading system. All subjects completed gait trials under the same experimental conditions. Machine learning-based classification using the support vector machine (SVM) classifier was performed to classify KOA patients and the severity of KOA. Logistic regression analysis was also performed to compare the results in classifying KOA patients with machine learning method. @*Results@#In the classification between KOA patients and normal subjects, the accuracy of classification was higher in machine learning method than in logistic regression analysis. In the classification of KOA severity, accuracy was enhanced through the feature selection process in the machine learning method. The most significant gait feature for classification was flexion and extension of the knee in the swing phase in the machine learning method. @*Conclusion@#The machine learning method is thought to be a new approach to complement conventional logistic regression analysis in the classification of KOA patients. It can be clinically used for diagnosis and gait correction of KOA patients.
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Objective@#To present new classification methods of knee osteoarthritis (KOA) using machine learning and compare its performance with conventional statistical methods as classification techniques using machine learning have recently been developed. @*Methods@#A total of 84 KOA patients and 97 normal participants were recruited. KOA patients were clustered into three groups according to the Kellgren-Lawrence (K-L) grading system. All subjects completed gait trials under the same experimental conditions. Machine learning-based classification using the support vector machine (SVM) classifier was performed to classify KOA patients and the severity of KOA. Logistic regression analysis was also performed to compare the results in classifying KOA patients with machine learning method. @*Results@#In the classification between KOA patients and normal subjects, the accuracy of classification was higher in machine learning method than in logistic regression analysis. In the classification of KOA severity, accuracy was enhanced through the feature selection process in the machine learning method. The most significant gait feature for classification was flexion and extension of the knee in the swing phase in the machine learning method. @*Conclusion@#The machine learning method is thought to be a new approach to complement conventional logistic regression analysis in the classification of KOA patients. It can be clinically used for diagnosis and gait correction of KOA patients.
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BACKGROUND: Smad4 and PTEN are prognostic indicators for various tumor types. Smad4 regulates tumor suppression, whereas PTEN inhibits cell proliferation. We analyzed and compared the performance of Smad4 and PTEN for predicting the prognosis of patients with colorectal adenocarcinoma. METHODS: Combined expression patterns based on Smad4+/– and PTEN+/– status were evaluated by immunostaining using a tissue microarray of colorectal adenocarcinoma. The relationships between the protein expression and clinicopathological variables were analyzed. RESULTS: Smad4–/PTEN– status was most frequently observed in metastatic adenocarcinoma, followed by primary adenocarcinoma and tubular adenoma (p<.001). When Smad4–/PTEN– and Smad4+/PTEN+ groups were compared, Smad4–/PTEN– status was associated with high N stage (p=.018) and defective mismatch repair proteins (p=.006). Significant differences in diseasefree survival and overall survival were observed among the three groups (Smad4+/PTEN+, Smad4–/PTEN+ or Smad4+/PTEN–, and Smad4–/PTEN–) (all p<.05). CONCLUSIONS: Concurrent loss of Smad4 and PTEN may lead to more aggressive disease and poor prognosis in patients with colorectal adenocarcinoma compared to the loss of Smad4 or PTEN alone.