Purpose : This study was performed to investigate the epidemiologic characteristics of human bocavirus (HBoV)-associated lower respiratory tract infections (LRTIs) in children. Methods : Nasopharyngeal aspirate samples were obtained from 658 children who had been hospitalized for LRTIs in Seoul National University (SNU) Children's Hospital and SNU Bundang Hospital from March 2000 to September 2005. Multiplex RT-PCR was performed to detect 11 respiratory viruses including respiratory syncytial virus, adenovirus, rhinovirus, parainfluenza viruses 1 and 3, influenza viruses A and B, human metapneumovirus, HBoV, human coronavirus (HCoV) OC43/ 229E, and HCoV-NL63. Clinical data were reviewed retrospectively. Results : Overall, respiratory viruses were detected in 325 (49.4%) among 658 patients. HBoV was detected in 62 cases (9.4%) and was responsible for 19.1% of virus-positive cases. HBoV was prevalent among infants and young children aged from 3 months to 5 years with the mean age of 25.3 months. Co-detection of HBoV and other respiratory viruses was observed in 37.1% which is significantly higher than average co-detection rate (12.3%) among overall virus-positive cases (P=0.000). HBoV was identified mainly in late spring and early summer from May to July. Conclusion : This study describes epidemiologic features of HBoV in Korean children compared with those associated with other respiratory viruses. HBoV was prevalent among LRTIs in childhood, especially in late spring and early summer season in Korea.
The purpose of this study is to provide basic data on the negative factors of oral health in masks and the importance of oral health management according to the use of masks to prevent novel coronavirus infection (COVID-19). From May 3 to 31, 2021, 232 adults aged 20 to 59 across the country were surveyed and statistically analyzed. As for the mask selection, 63.9% of men and 61.3% of women chose the KF_94 mask for both men and women, and it was found that the older they were, the more they chose the KF_94 mask. Self-recognition of dry mouth and bad breath due to wearing a mask showed that the group wearing a cotton mask felt high dry mouth, and there was a statistically significant difference. There was a significant positive correlation between mask type, dry mouth(r=.142, p<.05), and age(r=.234, p<.01). There was a significant positive correlation between mask wearing time and age(r=.158, p<.05), and it was found to be negatively correlated according to occupation, and was statistically significant(r=-.472, p< .01). Dry mouth had a statistically significant positive correlation with bad breath(r=3.04, p<.01) and age(r=.224, p<.01).
Purpose: This study aimed to identify the etiology and risk factors of community-acquired pneumonia (CAP) requiring hospitalization in Korean children during the coronavirus disease 2019 (COVID-19) pandemic. Methods: Clinical information of children admitted with CAP to Seoul National University Children's Hospital (SNUCH) between January 1, 2021, and February 28, 2022, was retrospectively collected and analyzed. In addition, the etiologic diagnosis and demographic data of children with CAP who were discharged at the other seven hospitals between January and February 2022 were collected. Pneumonia was diagnosed using strict criteria comprising clinical symptoms, physical examination findings, and chest radiographic findings. Results: Among 91 children hospitalized with CAP at SNUCH during the 14-month period, 68.4% were aged <5 years and 79.1% had underlying diseases. Among the 95 CAP cases, respiratory assistance was required in 70.5%, and the use of a ventilator was required in 20.0%. A total of five patients expired, all of whom were either immunocompromised or had underlying neurological diseases. Neurological diseases and immunosuppression were significantly correlated with respiratory assistance (P=0.003) and death (P=0.014). A total of 55% of the detected respiratory pathogens were viruses, the most common of which was rhinovirus at 35.9%. Among the 169 children hospitalized for CAP at the eight institutions, ≥1 respiratory virus was detected in 92.3%, among which respiratory syncytial virus (79.8%) was the most prevalent. Conclusions: Even during the COVID-19 pandemic, Korean children were hospitalized with CAP caused by seasonal respiratory viral pathogens. Although atypical and pyogenic bacteria were not detected, continuous clinical monitoring and further prospective studies should be conducted.
From January 2020 to October 2021, more than 500,000 academic studies related to COVID-19 (Coronavirus-2, a fatal respiratory syndrome) have been published. The rapid increase in the number of papers related to COVID-19 is putting time and technical constraints on healthcare professionals and policy makers to quickly find important research. Therefore, in this study, we propose a method of extracting useful information from text data of extensive literature using LDA and Word2vec algorithm. Papers related to keywords to be searched were extracted from papers related to COVID-19, and detailed topics were identified. The data used the CORD-19 data set on Kaggle, a free academic resource prepared by major research groups and the White House to respond to the COVID-19 pandemic, updated weekly. The research methods are divided into two main categories. First, 41,062 articles were collected through data filtering and pre-processing of the abstracts of 47,110 academic papers including full text. For this purpose, the number of publications related to COVID-19 by year was analyzed through exploratory data analysis using a Python program, and the top 10 journals under active research were identified. LDA and Word2vec algorithm were used to derive research topics related to COVID-19, and after analyzing related words, similarity was measured. Second, papers containing 'vaccine' and 'treatment' were extracted from among the topics derived from all papers, and a total of 4,555 papers related to 'vaccine' and 5,971 papers related to 'treatment' were extracted. did For each collected paper, detailed topics were analyzed using LDA and Word2vec algorithms, and a clustering method through PCA dimension reduction was applied to visualize groups of papers with similar themes using the t-SNE algorithm. A noteworthy point from the results of this study is that the topics that were not derived from the topics derived for all papers being researched in relation to COVID-19 (