Although the underlying disease is associated with a severe course in adults and laboratory abnormalities have been widely reported, there are not sufficient data on the clinical course of coronavirus disease 2019 (COVID-19) in children with pre-existing comorbid conditions and on laboratory findings. We aimed to describe the independent risk factors for estimating the severity of the COVID-19 in children. All children between 1 month and 18 years old who were hospitalized during the period of March 11-December 31, 2020, resulting from COVID-19 were included in the study. Patients were categorized into mild (group 1) and moderate + severe/critically (group 2) severity based on the criteria. Demographic characteristics, comorbidities, and laboratory variables between the two groups were compared. A total of 292 children confirmed to have COVID-19 infection were included in the study. The most common associated diseases were obesity (5.1%) and asthma bronchiale (4.1%). We observed that disease progressed more severely in patients with underlying diseases, especially obesity and asthma bronchiale (for patients with obesity odds ratio [OR] 9.1, 95% confidence interval [CI] 1.92-43.28, p = 0.005 and for patients with asthma bronchiale OR 4.1, 95% CI 1.04-16.80, p = 0.044). In group 2 patients, presence of lymphopenia and hypoalbuminemia, and also an elevation in serum levels of C-reactive protein, procalcitonin, and uric acid were detected and these results were statistically significant (p values; p < 0.001, p = 0.046, p = 0.006, p = 0.045, p < 0.001, respectively). The strongest predictor of moderate-severe COVID-19 infections in the children was uric acid, with an odds ratio of 1.6 (95% CI 1.14-2.13, p = 0.005) and lymphocytes with an odds ratio of 0.7 (95% CI 0.55-0.88, p = 0.003). Although children are less susceptible to COVID-19, the pre-existing comorbid condition can predispose to severe disease. In addition, lymphopenia and high uric acid are indicators that COVID-19 infection may progress more severely.
Keywords: coronavirus; epidemiology; immune responses; lymphocyte; pandemics; virus classification.
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