Safety of COVID-19 Vaccines among Patients with Type 2 Diabetes Mellitus: Real-World Data Analysis

Background@#Little is known about the adverse events (AEs) associated with coronavirus disease 2019 (COVID-19) vaccination in patients with type 2 diabetes mellitus (T2DM). @*Methods@#This study used vaccine AE reporting system data to investigate severe AEs among vaccinated patients with T2DM. A natural language processing algorithm was applied to identify people with and without diabetes. After 1:3 matching, we collected data for 6,829 patients with T2DM and 20,487 healthy controls. Multiple logistic regression analysis was used to calculate the odds ratio for severe AEs. @*Results@#After COVID-19 vaccination, patients with T2DM were more likely to experience eight severe AEs than controls: cerebral venous sinus thrombosis, encephalitis myelitis encephalomyelitis, Bell’s palsy, lymphadenopathy, ischemic stroke, deep vein thrombosis (DVT), thrombocytopenia (TP), and pulmonary embolism (PE). Moreover, patients with T2DM vaccinated with BNT162b2 and mRNA-1273 were more vulnerable to DVT and TP than those vaccinated with JNJ-78436735. Among patients with T2DM administered mRNA vaccines, mRNA-1273 was safer than BNT162b2 in terms of the risk of DVT and PE. @*Conclusion@#Careful monitoring of severe AEs in patients with T2DM may be necessary, especially for those related to thrombotic events and neurological dysfunctions after COVID-19 vaccination.

Myopic Open-angle Glaucoma Prevalence in Northeast Asia: A Systematic Review and Meta-analysis of Population-based Studies

Purpose@#Investigation of myopic open-angle glaucoma (OAG) prevalence in Northeast Asia by systematic review and meta-analysis. @*Methods@#Systematic PubMed, Embase and Cochrane database searches for Northeast Asian population-based studies published up to 30 November 2020 and reporting on myopia and OAG diagnosis. By random-effect models, pooled OAG prevalence in a myopic population and pooled myopic OAG prevalence in a general population were generated, with 95% confidence intervals (CIs). @*Results@#The meta-analysis encompassed five population-based studies in four countries (12,830 individuals, including 7,723 patients with myopia and 1,112 patients with OAG). In a myopic population, OAG prevalence was 4.10% (95% CI, 3.00–5.70; I2 = 93%); in a general population, myopic OAG prevalence was 1.10% (95% CI, 0.60–1.70; I2 = 94%). A visual examination of funnel plot symmetry raised a suspicion of publication bias. Notwithstanding, Begg and Mazumbar’s adjusted rank correlation test showed no such evidence (p = 0.6242). @*Conclusions@#Our systematic review and meta-analysis returned an estimate of OAG prevalence in a myopic Northeast Asian population. Our findings will inform future glaucoma studies as well as public health guidelines for Northeast Asian populations.

Possible Association between Differences in Nasalance Scores and Early Spread of COVID-19 Based on Linguistic Analysis

Objective@#The World Health Organization (WHO) declared a pandemic on March 11, 2020 after more than 118,000 cases of coronavirus disease 2019 (COVID-19) had been reported in 114 countries. Our study analyzed the cumulative incidence rate based on WHO data starting with the first confirmed patient until the peak of transmission. In addition, the numerical values of nasometry from normal subjects were quantified to analyze the linguistic features. @*Methods@#This study consisted of two main methodologies including a meta-analysis based on nasometry data involving normal adults and cumulative incidence rate based on WHO data. In addition, the numerical values of nasometry from normal subjects were quantified to analyze the linguistic features. @*Results@#The pooled overall mean differences (MDs) for oral text nasalance among linguistic families were 14.655 (95% confidence interval [CI], 7.986–21.324) in Arabic, 24.441 (95% CI, 17.920–30.962) in Chinese, 14.964 (95% CI, 13.677–16.251) in European, and 11.437 (95% CI, 9.880–12.994) in Ural-Altaic. The pooled overall MDs for cumulative incidence rate of COVID-19 were 190.3 (95% CI, 56.10–324.60) in Arabic, 283.20 (95% CI, 1.80–564.60) in European, and 5.70 (95% CI, 4.90–6.60) in Ural-Altaic. Correlation between oral nasalance score and cumulative incidence was significant (P=0.0004). @*Conclusion@#Our study showed the possible association between language characteristics and early spread of COVID-19. Further studies are needed to validate our outcomes based on various epidemiologic and behavioral factors including mask wearing.

Dose-response meta-analysis: application and practice using the R software / 한국역학회지

The objective of this study was to describe the general approaches of dose-response meta-analysis (DRMA) available for the quantitative synthesis of data using the R software. We conducted a DRMA using two types of data, the difference of means in continuous data and the odds ratio in binary data. The package commands of the R software were “doseresmeta” for the overall effect sizes that were separated into a linear model, quadratic model, and restricted cubic split model for better understanding. The effect sizes according to the dose and a test for linearity were demonstrated and interpreted by analyzing one-stage and two-stage DRMA. The authors examined several flexible models of exposure to pool study-specific trends and made a graphical presentation of the dose-response trend. This study focused on practical methods of DRMA rather than theoretical concepts for researchers who did not major in statistics. The authors hope that this study will help many researchers use the R software to perform DRMAs more easily, and that related research will be pursued.

Diagnostic test accuracy: application and practice using R software / 한국역학회지

The objective of this paper is to describe general approaches of diagnostic test accuracy (DTA) that are available for the quantitative synthesis of data using R software. We conduct a DTA that summarizes statistics for univariate analysis and bivariate analysis. The package commands of R software were “metaprop” and “metabin” for sensitivity, specificity, and diagnostic odds ratio; forest for forest plot; reitsma of “mada” for a summarized receiver-operating characteristic (ROC) curve; and “metareg” for meta-regression analysis. The estimated total effect sizes, test for heterogeneity and moderator effect, and a summarized ROC curve are reported using R software. In particular, we focus on how to calculate the effect sizes of target studies in DTA. This study focuses on the practical methods of DTA rather than theoretical concepts for researchers whose fields of study were non-statistics related. By performing this study, we hope that many researchers will use R software to determine the DTA more easily, and that there will be greater interest in related research.

Intervention meta-analysis: application and practice using R software / 한국역학회지

The objective of this study was to describe general approaches for intervention meta-analysis available for quantitative data synthesis using the R software. We conducted an intervention meta-analysis using two types of data, continuous and binary, characterized by mean difference and odds ratio, respectively. The package commands for the R software were “metacont”, “metabin”, and “metagen” for the overall effect size, “forest” for forest plot, “metareg” for meta-regression analysis, and “funnel” and “metabias” for the publication bias. The estimated overall effect sizes, test for heterogeneity and moderator effect, and the publication bias were reported using the R software. In particular, the authors indicated methods for calculating the effect sizes of the target studies in intervention meta-analysis. This study focused on the practical methods of intervention meta-analysis, rather than the theoretical concepts, for researchers with no major in statistics. Through this study, the authors hope that many researchers will use the R software to more readily perform the intervention meta-analysis and that this will in turn generate further related research.

Network meta-analysis: application and practice using R software / 한국역학회지

The objective of this study is to describe the general approaches to network meta-analysis that are available for quantitative data synthesis using R software. We conducted a network meta-analysis using two approaches: Bayesian and frequentist methods. The corresponding R packages were “gemtc” for the Bayesian approach and “netmeta” for the frequentist approach. In estimating a network meta-analysis model using a Bayesian framework, the “rjags” package is a common tool. “rjags” implements Markov chain Monte Carlo simulation with a graphical output. The estimated overall effect sizes, test for heterogeneity, moderator effects, and publication bias were reported using R software. The authors focus on two flexible models, Bayesian and frequentist, to determine overall effect sizes in network meta-analysis. This study focused on the practical methods of network meta-analysis rather than theoretical concepts, making the material easy to understand for Korean researchers who did not major in statistics. The authors hope that this study will help many Korean researchers to perform network meta-analyses and conduct related research more easily with R software.

Dose-response meta-analysis: application and practice using the R software / 한국역학회지

The objective of this study was to describe the general approaches of dose-response meta-analysis (DRMA) available for the quantitative synthesis of data using the R software. We conducted a DRMA using two types of data, the difference of means in continuous data and the odds ratio in binary data. The package commands of the R software were “doseresmeta” for the overall effect sizes that were separated into a linear model, quadratic model, and restricted cubic split model for better understanding. The effect sizes according to the dose and a test for linearity were demonstrated and interpreted by analyzing one-stage and two-stage DRMA. The authors examined several flexible models of exposure to pool study-specific trends and made a graphical presentation of the dose-response trend. This study focused on practical methods of DRMA rather than theoretical concepts for researchers who did not major in statistics. The authors hope that this study will help many researchers use the R software to perform DRMAs more easily, and that related research will be pursued.

Diagnostic test accuracy: application and practice using R software / 한국역학회지

The objective of this paper is to describe general approaches of diagnostic test accuracy (DTA) that are available for the quantitative synthesis of data using R software. We conduct a DTA that summarizes statistics for univariate analysis and bivariate analysis. The package commands of R software were “metaprop” and “metabin” for sensitivity, specificity, and diagnostic odds ratio; forest for forest plot; reitsma of “mada” for a summarized receiver-operating characteristic (ROC) curve; and “metareg” for meta-regression analysis. The estimated total effect sizes, test for heterogeneity and moderator effect, and a summarized ROC curve are reported using R software. In particular, we focus on how to calculate the effect sizes of target studies in DTA. This study focuses on the practical methods of DTA rather than theoretical concepts for researchers whose fields of study were non-statistics related. By performing this study, we hope that many researchers will use R software to determine the DTA more easily, and that there will be greater interest in related research.

Intervention meta-analysis: application and practice using R software / 한국역학회지

The objective of this study was to describe general approaches for intervention meta-analysis available for quantitative data synthesis using the R software. We conducted an intervention meta-analysis using two types of data, continuous and binary, characterized by mean difference and odds ratio, respectively. The package commands for the R software were “metacont”, “metabin”, and “metagen” for the overall effect size, “forest” for forest plot, “metareg” for meta-regression analysis, and “funnel” and “metabias” for the publication bias. The estimated overall effect sizes, test for heterogeneity and moderator effect, and the publication bias were reported using the R software. In particular, the authors indicated methods for calculating the effect sizes of the target studies in intervention meta-analysis. This study focused on the practical methods of intervention meta-analysis, rather than the theoretical concepts, for researchers with no major in statistics. Through this study, the authors hope that many researchers will use the R software to more readily perform the intervention meta-analysis and that this will in turn generate further related research.

Network meta-analysis: application and practice using R software / 한국역학회지

The objective of this study is to describe the general approaches to network meta-analysis that are available for quantitative data synthesis using R software. We conducted a network meta-analysis using two approaches: Bayesian and frequentist methods. The corresponding R packages were “gemtc” for the Bayesian approach and “netmeta” for the frequentist approach. In estimating a network meta-analysis model using a Bayesian framework, the “rjags” package is a common tool. “rjags” implements Markov chain Monte Carlo simulation with a graphical output. The estimated overall effect sizes, test for heterogeneity, moderator effects, and publication bias were reported using R software. The authors focus on two flexible models, Bayesian and frequentist, to determine overall effect sizes in network meta-analysis. This study focused on the practical methods of network meta-analysis rather than theoretical concepts, making the material easy to understand for Korean researchers who did not major in statistics. The authors hope that this study will help many Korean researchers to perform network meta-analyses and conduct related research more easily with R software.

Dose-response meta-analysis: application and practice using the R software / 한국역학회지

The objective of this study was to describe the general approaches of dose-response meta-analysis (DRMA) available for the quantitative synthesis of data using the R software. We conducted a DRMA using two types of data, the difference of means in continuous data and the odds ratio in binary data. The package commands of the R software were “doseresmeta” for the overall effect sizes that were separated into a linear model, quadratic model, and restricted cubic split model for better understanding. The effect sizes according to the dose and a test for linearity were demonstrated and interpreted by analyzing one-stage and two-stage DRMA. The authors examined several flexible models of exposure to pool study-specific trends and made a graphical presentation of the dose-response trend. This study focused on practical methods of DRMA rather than theoretical concepts for researchers who did not major in statistics. The authors hope that this study will help many researchers use the R software to perform DRMAs more easily, and that related research will be pursued.

Diagnostic test accuracy: application and practice using R software / 한국역학회지

The objective of this paper is to describe general approaches of diagnostic test accuracy (DTA) that are available for the quantitative synthesis of data using R software. We conduct a DTA that summarizes statistics for univariate analysis and bivariate analysis. The package commands of R software were “metaprop” and “metabin” for sensitivity, specificity, and diagnostic odds ratio; forest for forest plot; reitsma of “mada” for a summarized receiver-operating characteristic (ROC) curve; and “metareg” for meta-regression analysis. The estimated total effect sizes, test for heterogeneity and moderator effect, and a summarized ROC curve are reported using R software. In particular, we focus on how to calculate the effect sizes of target studies in DTA. This study focuses on the practical methods of DTA rather than theoretical concepts for researchers whose fields of study were non-statistics related. By performing this study, we hope that many researchers will use R software to determine the DTA more easily, and that there will be greater interest in related research.

Intervention meta-analysis: application and practice using R software / 한국역학회지

The objective of this study was to describe general approaches for intervention meta-analysis available for quantitative data synthesis using the R software. We conducted an intervention meta-analysis using two types of data, continuous and binary, characterized by mean difference and odds ratio, respectively. The package commands for the R software were “metacont”, “metabin”, and “metagen” for the overall effect size, “forest” for forest plot, “metareg” for meta-regression analysis, and “funnel” and “metabias” for the publication bias. The estimated overall effect sizes, test for heterogeneity and moderator effect, and the publication bias were reported using the R software. In particular, the authors indicated methods for calculating the effect sizes of the target studies in intervention meta-analysis. This study focused on the practical methods of intervention meta-analysis, rather than the theoretical concepts, for researchers with no major in statistics. Through this study, the authors hope that many researchers will use the R software to more readily perform the intervention meta-analysis and that this will in turn generate further related research.

Network meta-analysis: application and practice using R software / 한국역학회지

The objective of this study is to describe the general approaches to network meta-analysis that are available for quantitative data synthesis using R software. We conducted a network meta-analysis using two approaches: Bayesian and frequentist methods. The corresponding R packages were “gemtc” for the Bayesian approach and “netmeta” for the frequentist approach. In estimating a network meta-analysis model using a Bayesian framework, the “rjags” package is a common tool. “rjags” implements Markov chain Monte Carlo simulation with a graphical output. The estimated overall effect sizes, test for heterogeneity, moderator effects, and publication bias were reported using R software. The authors focus on two flexible models, Bayesian and frequentist, to determine overall effect sizes in network meta-analysis. This study focused on the practical methods of network meta-analysis rather than theoretical concepts, making the material easy to understand for Korean researchers who did not major in statistics. The authors hope that this study will help many Korean researchers to perform network meta-analyses and conduct related research more easily with R software.

Is Tamsulosin 0.2 mg Effective and Safe as a First-Line Treatment Compared with Other Alpha Blockers?: A Meta-Analysis and a Moderator Focused Study

PURPOSE: Tamsulosin 0.2 mg is used widely in Asian people, but the low dose has been studied less than tamsulosin 0.4 mg or other alpha blockers of standard dose. This study investigated the efficacy and safety of tamsulosin 0.2 mg by a meta-analysis and meta-regression. MATERIALS AND METHODS: We conducted a meta-analysis of efficacy of tamsulosin 0.2 mg using International Prostate Symptom Score (IPSS), maximal urinary flow rate (Qmax), post-voided residual volume (PVR), and quality of life (QoL). Safety was analyzed using adverse events. Relevant studies were searched using MEDLINE, EMBASE, and Cochrane library from January 1980 to June 2013. RESULTS: Ten studies were included with a total sample size of 1418 subjects [722 tamsulosin 0.2 mg group and 696 other alpha-blockers (terazosin, doxazosin, naftopidil, silodosin) group]. Study duration ranged from 4 to 24 weeks. The pooled overall standardized mean differences (SMD) in the mean change of IPSS from baseline for the tamsulosin group versus the control group was 0.02 [95% confidence interval (CI); -0.20, 0.25]. The pooled overall SMD in the mean change of QoL from baseline for the tamsulosin group versus the control group was 0.16 (95% CI; -0.16, 0.48). The regression analysis with the continuous variables (number of patients, study duration) revealed no significance in all outcomes as IPSS, QoL, and Qmax. CONCLUSION: This study clarifies that tamsulosin 0.2 mg has similar efficacy and fewer adverse events compared with other alpha-blockers as an initial treatment strategy for men with lower urinary tract symptoms.

Geographic Distribution of Urologists in Korea, 2007 to 2012

The adequacy of the urologist work force in Korea has never been investigated. This study investigated the geographic distribution of urologists in Korea. County level data from the National Health Insurance Service and National Statistical Office was analyzed in this ecological study. Urologist density was defined by the number of urologists per 100,000 individuals. National patterns of urologist density were mapped graphically at the county level using GIS software. To control the time sequence, regression analysis with fitted line plot was conducted. The difference of distribution of urologist density was analyzed by ANCOVA. Urologists density showed an uneven distribution according to county characteristics (metropolitan cities vs. nonmetropolitan cities vs. rural areas; mean square=102.329, P<0.001) and also according to year (mean square=9.747, P=0.048). Regression analysis between metropolitan and non-metropolitan cities showed significant difference in the change of urologists per year (P=0.019). Metropolitan cities vs. rural areas and non-metropolitan cities vs. rural areas showed no differences. Among the factors, the presence of training hospitals was the affecting factor for the uneven distribution of urologist density (P<0.001).Uneven distribution of urologists in Korea likely originated from the relatively low urologist density in rural areas. However, considering the time sequencing data from 2007 to 2012, there was a difference between the increase of urologist density in metropolitan and non-metropolitan cities.