Symptom-based clusters of hospitalized patients with severe acute respiratory illness by SARS-CoV-2 in Brazil.

BACKGROUND: COVID-19 has shown a broad clinical spectrum, ranging from asymptomatic to mild, moderate, and severe infections. Many symptoms have already been identified as typical of COVID-19, but few studies show how they can be useful in identifying clusters of patients with different severity of illness. This interpretation may help to recognize the different profiles of symptoms of COVID-19 expressed in a population at certain time. The aim of this study was to identify symptom-based clusters of hospitalized patients with severe acute respiratory illness by SARS-CoV-2 in Brazil. The clusters were evaluated based on sociodemographic characteristics, admission to the Intensive Care Unit (ICU), use of respiratory support, and outcome. METHODS: The Multiple Correspondence Analysis (MCA)-based cluster analysis was applied to symptoms presented before admission. Pearson's chi-square test was used to compare the proportions of symptoms between the clusters and to examine differences in the calculated rates for the following variables: sex, age group, race, Brazilian region, use of respiratory support, admission to the ICU and outcome. RESULTS: Three COVID-19 clusters with distinct symptom profiles were identified by MCA-based cluster analysis. Cluster 1 had the mildest severity profile, with the lowest frequencies for most symptoms investigated. Cluster 2 had a severe respiratory profile, with the highest frequencies of patients with dyspnea, respiratory discomfort and O2 saturation< 95%. Cluster 2 was also the most prevalent in all Brazilian regions and had the highest percentages of patients who used invasive respiratory support (27.4%) (p-value<0.001), were admitted to the ICU (42.6%) (p -value<0.001) and died (39.0%) (p-value<0.001). Cluster 3 had a prominent profile of gastrointestinal symptoms. CONCLUSIONS: The study identified three distinct COVID-19 clusters based on the symptoms presented by patients with severe acute respiratory illness by SARS-CoV-2, but without distinction in their prevalence in the Brazilian regions.

Eating habits of children and adolescents during the COVID-19 pandemic: The impact of social isolation.

BACKGROUND: The social isolation enforced as a result of the new coronavirus (COVID-19) pandemic may impact families' lifestyle and eating habits. The present study aimed to assess the behaviour and dietary patterns of Brazilian children and adolescents during the social isolation imposed by the COVID-19 pandemic. METHODS: The present study was conducted using an online, anonymous cross-sectional survey with 589 children and 720 adolescents from Brazil during a nationwide social isolation policy. The Mann-Whitney U-test or the Kruskal-Wallis with the Dunn post-hoc method and a radar chart were used to compare the weekly consumption of each food by age group and isolation status. p < 0.05 was considered statistically significant. Analyses were conducted using R statistical software, version 4.0.2 (R Foundation for Statisitical Computing). RESULTS: We found that isolated families showed breakfast eating habits and the consumption of raw salad, vegetables, beans and soft drinks. Lower-class isolated families and those from the Northeast region consumed fruits, juices, vegetables and beans less frequently. Compared to children, adolescents were less isolated (p = 0.016), less active (p < 0.001), exposed to longer screen time (p < 0.001), showed an inadequate sleeping pattern (p = 0.002) and were from lower-class families (p < 0.001). CONCLUSIONS: Social isolation affected the eating habits of children and adolescents. Non-isolated families presented a lower consumption of healthy food, especially those among the lower class, from Northeast Brazil, as well as adolescents.

Risk Factors for Hospitalization and Mortality due to COVID-19 in Espírito Santo State, Brazil.

Brazil is, at the time of writing, the global epicenter of COVID-19, but information on risk factors for hospitalization and mortality in the country is still limited. Demographic and clinical data of COVID-19 patients until June 11th, 2020 were retrieved from the State Health Secretariat of Espírito Santo, Brazil. Potential risk factors for COVID-19 hospitalization and death were analyzed by univariate and multivariable logistic regression models. A total of 10,713 COVID-19 patients were included in this study; 81.0% were younger than 60 years, 55.2% were female, 89.2% were not hospitalized, 32.9% had at least one comorbidity, and 7.7% died. The most common symptoms on admission were cough (67.7%) and fever (62.6%); 7.1% of the patients were asymptomatic. Cardiovascular diseases (23.7%) and diabetes (10.3%) were the two most common chronic diseases. Multivariate logistic regression analysis identified an association of all explanatory variables, except for cough and diarrhea, with hospitalization. Older age (odds ratio [OR] = 3.95, P < 0.001) and shortness of breath (OR = 3.55, P < 0.001) were associated with increase of odds to COVID-19 death in hospitalized patients. Our study provided evidence that older age, male gender, Asian, indigenous or unknown race, comorbidities (smoking, kidney disease, obesity, pulmonary disease, diabetes, and cardiovascular disease), as well as fever and shortness of breath increased the risk of hospitalization. For death outcome in hospitalized patients, only older age and shortness of breath increased the risk.