Seroprevalence of SARS-CoV-2 antibodies in South Korea.

In 2020, Korea Disease Control and Prevention Agency reported three rounds of surveys on seroprevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies in South Korea. SARS-CoV-2 is the virus which inflicts the coronavirus disease 2019 (COVID-19). We analyze the seroprevalence surveys using a Bayesian method with an informative prior distribution on the seroprevalence parameter, and the sensitivity and specificity of the diagnostic test. We construct the informative prior of the sensitivity and specificity of the diagnostic test using the posterior distribution obtained from the clinical evaluation data. The constraint of the seroprevalence parameter induced from the known confirmed coronavirus 2019 cases can be imposed naturally in the proposed Bayesian model. We also prove that the confidence interval of the seroprevalence parameter based on the Rao's test can be the empty set, while the Bayesian method renders interval estimators with coverage probability close to the nominal level. As of the 30th of October 2020, the 95 % credible interval of the estimated SARS-CoV-2 positive population does not exceed 318, 685, approximately 0.62 % of the Korean population. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s42952-021-00131-7.

Bayesian semiparametric mixed effects models for meta-analysis of the literature data : An application to cadmium toxicity studies.

We propose Bayesian semiparametric mixed effects models with measurement error to analyze the literature data collected from multiple studies in a meta-analytic framework. We explore this methodology for risk assessment in cadmium toxicity studies, where the primary objective is to investigate dose-response relationships between urinary cadmium concentrations and ß2 -microglobulin. In the proposed model, a nonlinear association between exposure and response is described by a Gaussian process with shape restrictions, and study-specific random effects are modeled to have either normal or unknown distributions with Dirichlet process mixture priors. In addition, nonparametric Bayesian measurement error models are incorporated to flexibly account for the uncertainty resulting from the usage of a surrogate measurement of a true exposure. We apply the proposed model to analyze cadmium toxicity data imposing shape constraints along with measurement errors and study-specific random effects across varying characteristics, such as population gender, age, or ethnicity.

Comparison of diffusion-weighted imaging and MR elastography in staging liver fibrosis: a meta-analysis.

PURPOSE: To compare the diagnostic performance of diffusion-weighted imaging (DWI), gradient-recalled echo-based magnetic resonance elastography (GRE-MRE), and spin-echo echo-planar imaging-based MRE (SE-EPI-MRE) in liver fibrosis staging. METHODS: A systematic literature search was done to collect studies on the performance of DWI, GRE-MRE, and SE-EPI-MRE for diagnosing liver fibrosis. Pooled sensitivity, specificity, diagnostic odds ratio, positive and negative likelihood ratio, and a summary receiver operating characteristic (ROC) curve were estimated with a bivariate random effects model. Subgroup analyses on various study characteristics were performed. RESULTS: Sixty studies with a total of 6620 patients were included in the meta-analysis. Pooled sensitivity and specificity of GRE-MRE and SE-EPI-MRE showed high diagnostic accuracy and did not differ significantly. The area under the summary ROC curve for all stages of fibrosis differed significantly between DWI (0.83-0.88) and either GRE-MRE (0.95-0.97) or SE-EPI-MRE (0.95-0.99). Substantial heterogeneity was detected for all three imaging methods. CONCLUSIONS: Both GRE-MRE and SE-EPI-MRE are highly accurate for detection of each liver fibrosis stage, with high potential to replace liver biopsy. Although DWI had a moderate accuracy in distinguishing liver fibrosis, it could be regarded as an alternative to MRE, since it is widely available and easily implemented in routine liver MRI.

Quantification of Carotid Intraplaque Hemorrhage: Comparison between Manual Segmentation and Semi-Automatic Segmentation on Magnetization-Prepared Rapid Acquisition with Gradient-Echo Sequences.

PURPOSE: Carotid intraplaque hemorrhage (IPH) increases risk of territorial cerebral ischemic events, but different sequences or criteria have been used to diagnose or quantify carotid IPH. The purpose of this study was to compare manual segmentation and semi-automatic segmentation for quantification of carotid IPH on magnetization-prepared rapid acquisition with gradient-echo (MPRAGE) sequences. METHODS: Forty patients with 16-79% carotid stenosis and IPH on MPRAGE sequences were reviewed by two trained radiologists with more than five years of specialized experience in carotid plaque characterization with carotid plaque MRI. Initially, the radiologists manually viewed the IPH based on the MPRAGE sequence. IPH volume was then measured by three different semi-automatic methods, with high signal intensity 150%, 175%, and 200%, respectively, above that of adjacent muscle on the MPRAGE sequence. Agreement on measurements between manual segmentation and semi-automatic segmentation was assessed using the intraclass correlation coefficient (ICC). RESULTS: There was near-perfect agreement between manual segmentation and the 150% and 175% criteria for semi-automatic segmentation in quantification of IPH volume. The ICC of each semi-automatic segmentation were as follows: 150% criteria: 0.861, 175% criteria: 0.809, 200% criteria: 0.491. The ICC value of manual vs. 150% criteria and manual vs. 175% criteria were significantly better than the manual vs. 200% criteria (p < 0.001). CONCLUSIONS: The ICC of 150% and 175% criteria for semi-automatic segmentation are more reliable for quantification of IPH volume. Semi-automatic classification tools may be beneficial in large-scale multicenter studies by reducing image analysis time and avoiding bias between human reviewers.

Estimation of the Biological Half-Life of Methylmercury Using a Population Toxicokinetic Model.

Methylmercury is well known for causing adverse health effects in the brain and nervous system. Estimating the elimination constant derived from the biological half-life of methylmercury in the blood or hair is an important part of calculating guidelines for methylmercury intake. Thus, this study was conducted to estimate the biological half-life of methylmercury in Korean adults. We used a one-compartment model with a direct relationship between methylmercury concentrations in the blood and daily dietary intake of methylmercury. We quantified the between-person variability of the methylmercury half-life in the population, and informative priors were used to estimate the parameters in the model. The population half-life of methylmercury was estimated to be 80.2 ± 8.6 days. The population mean of the methylmercury half-life was 81.6 ± 8.4 days for men and 78.9 ± 8.6 days for women. The standard deviation of the half-life was estimated at 25.0 ± 8.6 days. Using the direct relationship between methylmercury concentrations in blood and methylmercury intake, the biological half-life in this study was estimated to be longer than indicated by the earlier studies that have been used to set guideline values.

Benchmark Dose for Urinary Cadmium based on a Marker of Renal Dysfunction: A Meta-Analysis.

BACKGROUND: Low doses of cadmium can cause adverse health effects. Benchmark dose (BMD) and the one-sided 95% lower confidence limit of BMD (BMDL) to derive points of departure for urinary cadmium exposure have been estimated in several previous studies, but the methods to derive BMD and the estimated BMDs differ. OBJECTIVES: We aimed to find the associated factors that affect BMD calculation in the general population, and to estimate the summary BMD for urinary cadmium using reported BMDs. METHODS: A meta-regression was performed and the pooled BMD/BMDL was estimated using studies reporting a BMD and BMDL, weighted by sample size, that were calculated from individual data based on markers of renal dysfunction. RESULTS: BMDs were highly heterogeneous across studies. Meta-regression analysis showed that a significant predictor of BMD was the cut-off point which denotes an abnormal level. Using the 95th percentile as a cut off, BMD5/BMDL5 estimates for 5% benchmark responses (BMR) of ß2-microglobulinuria (ß2-MG) estimated was 6.18/4.88 µg/g creatinine in conventional quantal analysis and 3.56/3.13 µg/g creatinine in the hybrid approach, and BMD5/BMDL5 estimates for 5% BMR of N-acetyl-ß-d-glucosaminidase (NAG) was 10.31/7.61 µg/g creatinine in quantal analysis and 3.21/2.24 g/g creatinine in the hybrid approach. However, the meta-regression showed that BMD and BMDL were significantly associated with the cut-off point, but BMD calculation method did not significantly affect the results. The urinary cadmium BMDL5 of ß2-MG was 1.9 µg/g creatinine in the lowest cut-off point group. CONCLUSION: The BMD was significantly associated with the cut-off point defining the abnormal level of renal dysfunction markers.