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PLoS One ; 19(5): e0283037, 2024.
Article in English | MEDLINE | ID: mdl-38713667

ABSTRACT

COVID-19 affects children less seriously than adults; however, severe cases and deaths are documented. This study objective is to determine socio-demographic, clinical and laboratory indicators associated with severe pediatric COVID-19 and mortality at hospital entrance. A multicenter, retrospective, cross-sectional study was performed in 13 tertiary hospitals in Bolivia. Clinical records were collected retrospectively from patients less than 18 years of age and positive for SARS-CoV-2 infection. All variables were measured at hospital entrance; outcomes of interest were ICU admission and death. A score for disease severity was developed using a logistic regression model. 209 patients were included in the analysis. By the end of the study, 43 (20.6%) of children were admitted to the Intensive care unit (ICU), and 17 (8.1%) died. Five indicators were independently predictive of COVID-19 severity: age below 10 years OR: 3.3 (CI95%: 1.1-10.4), days with symptoms to medical care OR: 2.8 (CI95%: 1.2-6.5), breathing difficulty OR: 3.4 (CI95%: 1.4-8.2), vomiting OR: 3.3 (CI95%: 1.4-7.4), cutaneous lesions OR: 5.6 (CI95%: 1.9-16.6). Presence of three or more of these risk factors at hospital entrance predicted severe disease in COVID-19 positive children. Age, presence of underlying illness, male sex, breathing difficulty, and dehydration were predictive of death in COVID-19 children. Our study identifies several predictors of severe pediatric COVID-19 and death. Incorporating these predictors, we developed a tool that clinicians can use to identify children at high risk of severe COVID-19 in limited-resource settings.


Subject(s)
COVID-19 , SARS-CoV-2 , Severity of Illness Index , Humans , COVID-19/mortality , COVID-19/epidemiology , COVID-19/diagnosis , Child , Male , Female , Child, Preschool , Adolescent , Retrospective Studies , Cross-Sectional Studies , Infant , SARS-CoV-2/isolation & purification , Bolivia/epidemiology , Hospitalization , Intensive Care Units/statistics & numerical data , Risk Factors , Sociodemographic Factors
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