Respiratory syncytial virus (RSV) is the leading cause of lower respiratory tract infections and hospitalization in infants and young children. Here, we analyzed the genetic diversity of RSV using partial G gene sequences in 84 RSV-A and 78 RSV- B positive samples collected in Seoul, South Korea, for 10 consecutive years, from 2010 to 2019. Our phylogenetic analysis revealed that RSV-A strains were classified into either the ON1 (80.9%) or NA1 (19.0%) genotypes. On the other hand, RSV-B strains demonstrated diversified clusters within the BA genotype. Notably, some sequences designated as BA-SE, BA-SE1, and BA-DIS did not cluster with previously identified BA genotypes in the phylogenetic trees. Despite this, they did not meet the criteria for the assignment of a new genotype based on recent classification methods. Selection pressure analysis identified three positive selection sites (amino acid positions 273, 274, and 298) in RSV-A, and one possible positive selection site (amino acid position 296) in RSV-B, respectively. The mean evolutionary rates of Korean RSV-A from 1999 to 2019 and RSV-B strains from 1991 and 2019 were estimated at 3.51 × 10⁻³ nucleotides (nt) substitutions/site/year and 3.32 × 10⁻³ nt substitutions/site/year, respectively. The population dynamics in the Bayesian skyline plot revealed fluctuations corresponding to the emergence of dominant strains, including a switch of the dominant genotype from NA1 to ON1. Our study on time-scaled cumulative evolutionary analysis contributes to a better understanding of RSV epidemiology at the local level in South Korea.

Background: Currently, SARS‐CoV‐2 RNA detection using real‐time reverse‐transcription PCR (rRT‐PCR) is the standard diagnostic test for COVID‐19 infection. Various rRT‐PCR assays are currently used worldwide, targeting different genes of the SARS‐CoV‐2. Here, we compared the analytical sensitivity and clinical performance (sensitivity and specificity) of Allplex SARS‐CoV‐2/FluA/FluB/RSV assay (Seegene), Standard M nCoV real‐time detection kit (SD Biosensor), and U‐TOP COVID‐19 detection kit (Seasun Biomaterials) for SARS‐CoV‐2 detection.Methods: Two hundred and forty‐nine nasopharyngeal swab samples were evaluated to compare the clinical performance of the rRT‐PCR assays. For the analytical performance evaluation, two RNA controls with known viral loads—SARS‐CoV‐2 RNA control and SARS‐COV‐2 B.1.351 RNA control—were used to investigate the potential impact of SARS‐CoV‐2 variants, particularly the B.1.351 lineage.Results: Limits of detection ranged from 650 to 1300 copies/ml for rRT‐PCR assays, and the mean differences in cycle threshold (C_t) values of the two RNA controls were within 1.0 for each target in the rRT‐PCR assays (0.05–0.73), without any prominent C_t value shift or dropouts in the SARS‐COV‐2 B.1.351 RNA control. Using the consensus criterion as the reference standard, 89 samples were positive, whereas 160 were negative. The overall clinical performance of rRT‐PCR assays was comparable (sensitivity 98.88%–100%; specificity 99.38%–100%), whereas the sensitivities of each target gene were more variable.Conclusions: The three rRT‐PCR assays showed comparable analytical sensitivity and clinical performance. The analytical and clinical sensitivities of each target gene were influenced more by the primer and probe design than the target gene itself.

Cheonghwa Lee, M.D., Ha Nui Kim, M.D., Ph.D., Jung Ah Kwon, M.D., Ph.D., Soo-Young Yoon, M.D., Ph.D., Min Ji Jeon, M.D., Ph.D., Eun Sang Yu, M.D., Dae Sik Kim, M.D., Ph.D., Chul Won Choi, M.D., Ph.D., and Jung Yoon, M.D., Ph.D.. Ann Lab Med 2023;43:503-7. https://doi.org/10.3343/alm.2023.43.5.503

Background: Point‐of‐care (POC) testing provides quick results and includes tests for blood glucose and lipid profiles. We evaluated the newly developed POC device, the GCare Lipid Analyzer, which is used to measure glucose, total cholesterol (TC), triglyceride (TG), and high‐density lipoprotein cholesterol (HDL‐C) levels.Methods: Venous and capillary blood samples were collected from patients who visited Korea University Guro Hospital. The results obtained using the GCare Lipid Analyzer were compared with those obtained using the TBA 2000FR chemistry analyzer and YSI 2300 STAT Plus analyzer. The glucose system evaluation process was based on the International Organization for Standardization 15197:2013 guidelines.Results: The correlation coefficients (R) for TC, TG, and HDL‐C were 0.965, 0.969, and 0.943 in capillary blood and 0.969, 0.990, and 0.956 in venous blood, respectively. The total errors for TC, TG, and HDL‐C of the lipid profile using venous blood were all acceptable at 6.6%, 9.3%, and 11.6%, respectively. For glucose concentrations <100 mg/dl, 96.1% of the measured glucose levels were within ±15 mg/dl in venous samples and 100% were within ±15 mg/dl in capillary samples. For glucose concentrations ≥100 mg/dl, 100% and 99.5% of the measured glucose levels were within 15% for venous and capillary blood, respectively.Conclusion: The performance of the GCare Lipid Analyzer is acceptable for both blood glucose and lipid profile testing, indicating that it is reliable for use in patients with diabetic dyslipidemia.

Park K, et al. J Korean Med Sci. 2024 Oct;40:e4. https://doi.org/10.3346/jkms.2025.40.e4