Comparison of clinical and para-clinical characteristics between children and adults with the Omicron variant of COVID-19
DOI:
https://doi.org/10.3855/jidc.18812Keywords:
COVID-19, Omicron variant, clinical classifications, children, adultAbstract
Introduction: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant is associated with higher transmissibility, but lower disease severity, compared to some other variants. However, its exact pathogenicity among children is still largely unknown. This study was conducted to determine the differences in clinical characteristics between children and adults infected with this variant.
Methodology: A total of 327 Omicron-infected patients admitted to the First Affiliated Hospital of Nanchang University, between 7 December 2022 and 10 March 2023 were retrospectively evaluated. They were divided into two groups: children (0–18 years, n = 149) and adults (> 18 years, n = 178). Differences in clinical classifications, symptoms, imaging features, biochemical markers, and positive nucleic acid test durations were compared between the groups.
Results: Age had a significant impact on children in terms of clinical classifications (p < 0.05). Fever was the most common symptom among children (123/149), while coughing (151/178) was the most common among adults. The adults also had higher frequencies for pathological imaging features. The children had significantly higher white blood cell counts, and lymphocyte counts, while the adults had higher neutrophil percentages and C-reactive protein. Positive nucleic acid test durations were shorter among the children, compared to the adults. The children also had higher cumulative negative conversion and improvement rates (p < 0.05).
Conclusions: Overall, children with Omicron had milder clinical classifications, significantly different symptoms and biochemical indices, as well as lower occurrence of pathological imaging features and shorter positive nucleic acid test durations, compared to adults.
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Copyright (c) 2024 Yuchen Peng, Yufei Shi, Wentao Zhu, Xiaopeng Li, Jiwei Fu, Xincheng Wu, Pei Shi, Xiaoping Wu
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Funding data
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Natural Science Foundation of Jiangxi Province
Grant numbers 20212ACB206010