Cross-sectional study analyzes mortality factors in children and adolescents with COVID-19, suggesting implications for clinical management.
Children and adolescents with COVID-19 typically present milder symptoms of the infection, with fatal outcomes being rare. This study aimed to analyze the main associated factors for mortality in this population group. A cross-sectional study was performed to analyze reported COVID-19 cases among individuals under 18 years old in Rio de Janeiro state, Brazil, from March 2021 to September 2023. Pearson’s chi-square test was used for categorical variables, and the Wilcoxon test for numerical variables. The significance level was set at 5%. Logistic regression analysis was performed to identify factors associated with COVID-19 mortality in individuals under 18. Infants under 1 year old had a higher mortality chance (OR = 4.70; 95% CI: 2.45–9.60) compared to adolescents aged 15–17 years. Non-white individuals had a lower mortality chance compared to white individuals (OR = 0.64; 95% CI: 0.41–0.99). The presence of fever (OR = 1.83; 95% CI: 1.17–2.89), dyspnea (OR = 11.83; 95% CI: 7.50-18.74), and oxygen saturation below 95% (OR = 11.97; 95% CI: 3.78–33.19) was associated with a higher mortality chance. Patients with heart disease (OR = 7.74; 95% CI: 3.89–14.58) and immunodeficiency/immunosuppression (OR = 17.16; 95% CI: 8.58–32.14) had a higher mortality chance. Infection during the predominance of variants B1_wild (OR = 3.44; CI 1.75–6.81), Gamma (OR = 3.93; CI 2.13–7.44), and Delta (OR = 2.27; CI 1.02–4.84) was associated with a higher mortality chance compared to the Omicron variant. The main associated factors for death were fever, dyspnea, oxygen saturation below 95% on room air, age under one year, cardiac disease comorbidity, immunodeficiency, and infection during the predominance of B1_wild, Gamma, and Delta variants. Understanding the epidemiological profile and associated factors for mortality in this population is essential to inform effective prevention and control measures and guide optimal clinical management.
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Esteves et al. (2026) studied this question.
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