Short-term safety profile of COVID-19 vaccination in children and adolescents with underlying medical conditions: a prospective cohort study
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- Childhood Kidney Diseases
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- v.27 no.1
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- pp.34-39
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- 2023
Purpose: This article was to collect data on the safety of coronavirus disease 2019 (COVID-19) vaccines in children with underlying medical conditions. Methods: We constructed a prospective cohort of children and adolescents aged 5 to 19 years who had received at least one dose of COVID-19 vaccine. Patients diagnosed with and treated for chronic kidney disease, autoimmune disease, or other chronic conditions at the Seoul National University Children's Hospital were recruited from June to December 2022. A mobile survey questionnaire was sent to their guardians. The presence of adverse events on the day (day 0), 3 weeks (day 21), and 6 months (day 180) after the 1st dose of COVID-19 vaccine was recorded by the guardians. Results: A total of 73 children participated. The median age was 14 years, and 64.4% of the patients were male. On the day of immunization, 65.8% of the patients reported at least one adverse event. Pain at the injection site, fatigue, headache, arthralgia, and myalgia were the most common symptoms. The prevalence of adverse events decreased over time (65.8% on day 0, 27.4% between days 0 and 21, and 24.6% between days 21 and 180). Severe acute respiratory syndrome coronavirus 2 infection after the 1st dose occurred in 17 patients (23.3%) and one of the patients (5.88%) was hospitalized due to infection. Conclusions: Adverse events after COVID-19 vaccination were generally mild in children and adolescents with underlying medical conditions. Our findings provide evidence for the safety of COVID-19 vaccination in the vulnerable pediatric population.
Objectives This study aims to identify differences in clinical manifestations of COVID-19 between different Sasang constitution. Methods Subjects were recruited from August 29, 2022, to July 11, 2023. COVID-19 clinical symptoms were self-reported via questionnaires. Sasang constitutional diagnosis was performed using the K-PRISM, and Sasang constitutional specialist. Results A total of 66 subjects were recruited for the study, and the Sasang constitutional distribution of the subjects was 19 soyangin, 25 taeeumin, and 22 soeumin. For most of the COVID-19 clinical manifestations, the study found that soyangin experienced symptoms at a higher rate than other constitutions. Among the symptoms observed in the study, sore throat, pantalgia, and cough were severe in all subjects regardless of constitution. Soeumin was more likely to experience abdominal pain, chest pain, and diarrhea, while soyangin was more likely to experience chest pain, nausea/vomiting, diarrhea, and cutaneous symptoms compared to other constitutions. Taeeumin had more sputm, nasal congestion, and skin symptoms, but fewer digestive symptoms. There were differences in the onset and duration of symptoms by constitution. Conclusions This study is an important contribution to our understanding of the differences in response to the COVID-19 virus among different Sasang constitutions. Symptomatic differences between constitutions may have important implications for prevention and treatment strategies for infectious diseases, and personalized treatment and management based on these differences may be needed in the future.
Objectives: The coronavirus disease 2019 (COVID-19) pandemic led to increased mortality rates. To assess this impact, this ecological study aimed to estimate the excess death counts in southern Iran. Methods: The study obtained weekly death counts by linking the National Death Registry and Medical Care Monitoring Center repositories. The P-score was initially estimated using a simple method that involved calculating the difference between the observed and expected death counts. The interrupted time series analysis was then used to calculate the mean relative risk (RR) of death during the first year of the pandemic. Results: Our study found that there were 5571 excess deaths from all causes (P-score=33.29%) during the first year of the COVID-19 pandemic, with 48.03% of these deaths directly related to COVID-19. The pandemic was found to increase the risk of death from all causes (RR, 1.26; 95% confidence interval [CI], 1.19 to 1.33), as well as in specific age groups such as those aged 35-49 (RR, 1.21; 95% CI, 1.12 to 1.32), 50-64 (RR, 1.38; 95% CI, 1.28 to 1.49), and ≥65 (RR, 1.29; 95% CI, 1.12 to 1.32) years old. Furthermore, there was an increased risk of death from cardiovascular diseases (RR, 1.17; 95% CI, 1.11 to 1.22). Conclusions: There was a 26% increase in the death count in southern Iran during the COVID-19 pandemic. More than half of these excess deaths were not directly related to COVID-19, but rather other causes, with cardiovascular diseases being a major contributor.
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 (