ArticleBMC infectious diseases2024
Predictive factors for COVID-19 severity and mortality in hospitalized children.
Article in BMC infectious diseases, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Angiotensin-Converting Enzyme 1 (ACE1) gene polymorphisms in pediatric patients with COVID-19: impact on disease severity and outcomes.BMC medical genomics · 2026Article
- Survey of Attitudes Toward Vaccination Against SARS-COV-2 in Pediatric Patients with Heart Disease.Pediatric cardiology · 2026Article
- Differences in the clinical course of COVID-19 in children and adolescents hospitalized in the 2023/2024 and 2024/2025 seasons - a retrospective real-world study.BMC infectious diseases · 2025Article
- Evaluation of common respiratory viruses other than SARS-CoV-2 in hospitalized children during the COVID-19 pandemic.BMC infectious diseases · 2025Article
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundUnderstanding the factors influencing disease progression and severity in pediatric COVID-19 cases is essential for effective management and intervention strategies. This study aimed to evaluate the discriminative ability of clinical and laboratory parameters to identify predictors of COVID-19 severity and mortality in hospitalized children.
methodsIn this multicenter retrospective cohort study, we included 468 pediatric patients with COVID-19. We developed a predictive model using their demographic, clinical, and laboratory data. The performance of the model was assessed using various metrics including sensitivity, specificity, positive predictive value rates, and receiver operating characteristics (ROC).
resultsOur findings demonstrated strong discriminatory power, with an area under the curve (AUC) of 0.818 for severity and 0.873 for mortality prediction. Key risk factors for severe COVID-19 in children include low albumin levels, elevated C-reactive protein (CRP), lactate dehydrogenase (LDH), and underlying medical conditions. Furthermore, ROC curve analysis highlights the predictive value of CRP, LDH, and albumin, with AUC values of 0.789, 0.752, and 0.758, respectively.
conclusionOur study indicates that laboratory values are valuable in predicting COVID-19 severity in children. Various factors, including CRP, LDH, and albumin levels, demonstrated statistically significant differences between patient groups, suggesting their potential as predictive markers for disease severity. Implementing predictive analyses based on these markers could aid clinicians in making informed decisions regarding patient management.
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