Multisystem Inflammatory Syndrome in Children in Western Countries? Decreasing Incidence as the Pandemic Progresses?: An Observational Multicenter International Cross-sectional Study

COVID-19, Multisystemic inflammatory syndrome; Children; EpidemiologyCOVID-19, Síndrome inflamatorio multisistémico; Niños; EpidemiologíaCOVID-19, Síndrome inflamatòria multisistèmica; Nens; EpidemiologiaBackground: SARS-CoV-2 variations as well as immune protection after previous infections and/or vaccination may have altered the incidence of multisystemic inflammatory syndrome in children (MIS-C). We aimed to report an international time-series analysis of the incidence of MIS-C to determine if there was a shift in the regions or countries included into the study. Methods: This is a multicenter, international, cross-sectional study. We collected the MIS-C incidence from the participant regions and countries for the period July 2020 to November 2021. We assessed the ratio between MIS-C cases and COVID-19 pediatric cases in children <18 years diagnosed 4 weeks earlier (average time for the temporal association observed in this disease) for the study period. We performed a binomial regression analysis for 8 participating sites [Bogotá (Colombia), Chile, Costa Rica, Lazio (Italy), Mexico DF, Panama, The Netherlands and Catalonia (Spain)]. Results: We included 904 cases of MIS-C, among a reference population of 17,906,432 children. We estimated a global significant decrease trend ratio in MIS-C cases/COVID-19 diagnosed cases in the previous month ( P < 0.001). When analyzing separately each of the sites, Chile and The Netherlands maintained a significant decrease trend ( P < 0.001), but this ratio was not statistically significant for the rest of sites. Conclusions: To our knowledge, this is the first international study describing a global reduction in the trend of the MIS-C incidence during the pandemic. COVID-19 vaccination and other factors possibly linked to the virus itself and/or community transmission may have played a role in preventing new MIS-C cases

Multisystem inflammatory syndrome in children in western countries: decreasing incidence as the pandemic progresses? An observational multicenter international cross-sectional study

Multisystemic inflammatory syndrome temporally associated with SARS-CoV-2 infection in children (MIS-C) has been reported worldwide.1–7 The case definition of MIS-C has been estab- lished by different institutions and organizations such as the US Centers for Disease Control and Prevention (CDC) (May 14, 2020),8 the Royal College of Paediatrics and Child Health in the United Kingdom (RCPCH) (May 1, 2020)9,10 and the World Health Organi- zation (WHO) (May 15, 2020).1Postprint (published version

Worldwide trends in underweight and obesity from 1990 to 2022: a pooled analysis of 3663 population-representative studies with 222 million children, adolescents, and adults

Background Underweight and obesity are associated with adverse health outcomes throughout the life course. We estimated the individual and combined prevalence of underweight or thinness and obesity, and their changes, from 1990 to 2022 for adults and school-aged children and adolescents in 200 countries and territories. Methods We used data from 3663 population-based studies with 222 million participants that measured height and weight in representative samples of the general population. We used a Bayesian hierarchical model to estimate trends in the prevalence of different BMI categories, separately for adults (age ≥20 years) and school-aged children and adolescents (age 5–19 years), from 1990 to 2022 for 200 countries and territories. For adults, we report the individual and combined prevalence of underweight (BMI &lt;18·5 kg/m2) and obesity (BMI ≥30 kg/m2). For school&#x2;aged children and adolescents, we report thinness (BMI &lt;2 SD below the median of the WHO growth reference) and obesity (BMI &gt;2 SD above the median). Findings From 1990 to 2022, the combined prevalence of underweight and obesity in adults decreased in 11 countries (6%) for women and 17 (9%) for men with a posterior probability of at least 0·80 that the observed changes were true decreases. The combined prevalence increased in 162 countries (81%) for women and 140 countries (70%) for men with a posterior probability of at least 0·80. In 2022, the combined prevalence of underweight and obesity was highest in island nations in the Caribbean and Polynesia and Micronesia, and countries in the Middle East and north Africa. Obesity prevalence was higher than underweight with posterior probability of at least 0·80 in 177 countries (89%) for women and 145 (73%) for men in 2022, whereas the converse was true in 16 countries (8%) for women, and 39 (20%) for men. From 1990 to 2022, the combined prevalence of thinness and obesity decreased among girls in five countries (3%) and among boys in 15 countries (8%) with a posterior probability of at least 0·80, and increased among girls in 140 countries (70%) and boys in 137 countries (69%) with a posterior probability of at least 0·80. The countries with highest combined prevalence of thinness and obesity in school-aged children and adolescents in 2022 were in Polynesia and Micronesia and the Caribbean for both sexes, and Chile and Qatar for boys. Combined prevalence was also high in some countries in south Asia, such as India and Pakistan, where thinness remained prevalent despite having declined. In 2022, obesity in school-aged children and adolescents was more prevalent than thinness with a posterior probability of at least 0·80 among girls in 133 countries (67%) and boys in 125 countries (63%), whereas the converse was true in 35 countries (18%) and 42 countries (21%), respectively. In almost all countries for both adults and school-aged children and adolescents, the increases in double burden were driven by increases in obesity, and decreases in double burden by declining underweight or thinness. Interpretation The combined burden of underweight and obesity has increased in most countries, driven by an increase in obesity, while underweight and thinness remain prevalent in south Asia and parts of Africa. A healthy nutrition transition that enhances access to nutritious foods is needed to address the remaining burden of underweight while curbing and reversing the increase in obesit

Investigación (Arte + Diseño): desarrollo de discusiones críticas sobre múltiples experiencias, perspectivas y prácticas investigativas en el CIDEA.

Modalidad de graduación: Seminario para optar por el grado de licenciatrua en Arte y Comunicación VisualEntendiendo que el Seminario constituye una modalidad comprendida en el ámbito de los Trabajos Finales de Graduación como una actividad teórico - práctica dirigida al desarrollo de proyectos de investigación circunscritos a un tema propuesto por la Unidad Académica. El tema de este seminario de graduación, avalado por la mencionada entidad, coincide con el proyecto (PPAA): Nodos activos (Investigación + práctica artística). En síntesis, este tema es la exploración crítica sobre los procesos, formas prácticas y modelos destinados a diferentes formas de vivenciar, asumir y aplicar el concepto de Investigación artística y diseñística1. Por su amplitud y complejidad, este tema se ofrece como matriz para el desarrollo de proyectos de investigación alternos o asociados partiendo de una perspectiva interdisciplinaria y transdisciplinaria capaz de comprender diferentes áreas de especialización más allá incluso de las fronteras de las artes visuales y el diseño.Escuela de Arte y Comunicación Visua

Difference in mortality rates in hospitalized COVID-19 patients identified by cytokine profile clustering using a machine learning approach. An outcome prediction alternative

COVID-19 is a disease caused by the novel Coronavirus SARS-CoV-2 causing an acute respiratory disease that can eventually lead to severe acute respiratory syndrome (SARS). An exacerbated inflammatory response is characteristic of SARS-CoV2 infection, which leads to a cytokine release syndrome also known as cytokine storm associated with the severity of the disease. Considering the importance of this event in the immunopathology of COVID-19, this study analyses cytokine levels of hospitalized patients to identify cytokine profiles associated with severity and mortality. Using a machine learning approach, 3 clusters of COVID-19 hospitalized patients were created based on their cytokine profile. Significant differences in the mortality rate were found among the clusters, associated to different CXCL10/IL-38 ratio. The balance of a CXCL10 induced inflammation with an appropriate immune regulation mediated by the anti-inflammatory cytokine IL-38 appears to generate the adequate immune context to overrule SARS-CoV2 infection without creating a harmful inflammatory reaction. This study supports the concept that analyzing a single cytokine is insufficient to determine the outcome of a complex disease such as COVID-19, and different strategies incorporating bioinformatic analyses considering a broader immune profile represent a more robust alternative to predict the outcome of hospitalized patients with SARS-CoV2 infection.Universidad de Costa Rica/[807-C1-357]/UCR/Costa RicaUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias de la Salud::Centro de Investigación en Hematología y Trastornos Afines (CIHATA)UCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias de la Salud::Centro de Investigación en Enfermedades Tropicales (CIET)UCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias de la Salud::Centro de Investigación en Cirugía y Cáncer (CICICA

Multisystem Inflammatory Syndrome in Children in Western Countries? Decreasing Incidence as the Pandemic Progresses?: An Observational Multicenter International Cross-sectional Study

BACKGROUND: SARS-CoV-2 variations as well as immune protection after previous infections and/or vaccination may have altered the incidence of multisystemic inflammatory syndrome in children (MIS-C). We aimed to report an international time-series analysis of the incidence of MIS-C to determine if there was a shift in the regions or countries included into the study. METHODS: This is a multicenter, international, cross-sectional study. We collected the MIS-C incidence from the participant regions and countries for the period July 2020 to November 2021. We assessed the ratio between MIS-C cases and COVID-19 pediatric cases in children <18 years diagnosed 4 weeks earlier (average time for the temporal association observed in this disease) for the study period. We performed a binomial regression analysis for 8 participating sites [Bogotá (Colombia), Chile, Costa Rica, Lazio (Italy), Mexico DF, Panama, The Netherlands and Catalonia (Spain)]. RESULTS: We included 904 cases of MIS-C, among a reference population of 17,906,432 children. We estimated a global significant decrease trend ratio in MIS-C cases/COVID-19 diagnosed cases in the previous month ( P < 0.001). When analyzing separately each of the sites, Chile and The Netherlands maintained a significant decrease trend ( P < 0.001), but this ratio was not statistically significant for the rest of sites. CONCLUSIONS: To our knowledge, this is the first international study describing a global reduction in the trend of the MIS-C incidence during the pandemic. COVID-19 vaccination and other factors possibly linked to the virus itself and/or community transmission may have played a role in preventing new MIS-C cases

Table_2_Difference in mortality rates in hospitalized COVID-19 patients identified by cytokine profile clustering using a machine learning approach: An outcome prediction alternative.XLSX

COVID-19 is a disease caused by the novel Coronavirus SARS-CoV-2 causing an acute respiratory disease that can eventually lead to severe acute respiratory syndrome (SARS). An exacerbated inflammatory response is characteristic of SARS-CoV-2 infection, which leads to a cytokine release syndrome also known as cytokine storm associated with the severity of the disease. Considering the importance of this event in the immunopathology of COVID-19, this study analyses cytokine levels of hospitalized patients to identify cytokine profiles associated with severity and mortality. Using a machine learning approach, 3 clusters of COVID-19 hospitalized patients were created based on their cytokine profile. Significant differences in the mortality rate were found among the clusters, associated to different CXCL10/IL-38 ratio. The balance of a CXCL10 induced inflammation with an appropriate immune regulation mediated by the anti-inflammatory cytokine IL-38 appears to generate the adequate immune context to overrule SARS-CoV-2 infection without creating a harmful inflammatory reaction. This study supports the concept that analyzing a single cytokine is insufficient to determine the outcome of a complex disease such as COVID-19, and different strategies incorporating bioinformatic analyses considering a broader immune profile represent a more robust alternative to predict the outcome of hospitalized patients with SARS-CoV-2 infection.</p

Image_1_Difference in mortality rates in hospitalized COVID-19 patients identified by cytokine profile clustering using a machine learning approach: An outcome prediction alternative.TIF

COVID-19 is a disease caused by the novel Coronavirus SARS-CoV-2 causing an acute respiratory disease that can eventually lead to severe acute respiratory syndrome (SARS). An exacerbated inflammatory response is characteristic of SARS-CoV-2 infection, which leads to a cytokine release syndrome also known as cytokine storm associated with the severity of the disease. Considering the importance of this event in the immunopathology of COVID-19, this study analyses cytokine levels of hospitalized patients to identify cytokine profiles associated with severity and mortality. Using a machine learning approach, 3 clusters of COVID-19 hospitalized patients were created based on their cytokine profile. Significant differences in the mortality rate were found among the clusters, associated to different CXCL10/IL-38 ratio. The balance of a CXCL10 induced inflammation with an appropriate immune regulation mediated by the anti-inflammatory cytokine IL-38 appears to generate the adequate immune context to overrule SARS-CoV-2 infection without creating a harmful inflammatory reaction. This study supports the concept that analyzing a single cytokine is insufficient to determine the outcome of a complex disease such as COVID-19, and different strategies incorporating bioinformatic analyses considering a broader immune profile represent a more robust alternative to predict the outcome of hospitalized patients with SARS-CoV-2 infection.</p

Image_3_Difference in mortality rates in hospitalized COVID-19 patients identified by cytokine profile clustering using a machine learning approach: An outcome prediction alternative.TIF

COVID-19 is a disease caused by the novel Coronavirus SARS-CoV-2 causing an acute respiratory disease that can eventually lead to severe acute respiratory syndrome (SARS). An exacerbated inflammatory response is characteristic of SARS-CoV-2 infection, which leads to a cytokine release syndrome also known as cytokine storm associated with the severity of the disease. Considering the importance of this event in the immunopathology of COVID-19, this study analyses cytokine levels of hospitalized patients to identify cytokine profiles associated with severity and mortality. Using a machine learning approach, 3 clusters of COVID-19 hospitalized patients were created based on their cytokine profile. Significant differences in the mortality rate were found among the clusters, associated to different CXCL10/IL-38 ratio. The balance of a CXCL10 induced inflammation with an appropriate immune regulation mediated by the anti-inflammatory cytokine IL-38 appears to generate the adequate immune context to overrule SARS-CoV-2 infection without creating a harmful inflammatory reaction. This study supports the concept that analyzing a single cytokine is insufficient to determine the outcome of a complex disease such as COVID-19, and different strategies incorporating bioinformatic analyses considering a broader immune profile represent a more robust alternative to predict the outcome of hospitalized patients with SARS-CoV-2 infection.</p