A Bayesian Model to Predict COVID-19 Severity in Children
| Autor: | Cristina Epalza, M. José Mellado, Serena Villaverde, Antoni Soriano-Arandes, Mercedes de la Torre, Yolanda Ruiz Del Prado, Jose Antonio Alonso-Cadenas, Blanca Herrero, Paula Rodríguez-Molino, Nerea Gallego, Pere Soler-Palacín, David Aguilera-Alonso, Silvia Simó, Sara Domínguez-Rodríguez, Fátima Ara-Montojo, Cristina Calvo, Francisco José Sanz-Santaeufemia, Elena Cobos, Sara Villanueva-Medina, Teresa Del Rosal, Joan Pujol-Morro, Marta Pareja, Cinta Moraleda, M Isabel Iglesias-Bouzas, Victoria Fumadó, Susana Melendo, Marta Illán Ramos, María Urretavizcaya-Martínez, Jesús Saavedra-Lozano, Alfredo Tagarro, Miquel Serna-Pascual, Carlos Grasa |
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| Rok vydání: | 2021 |
| Předmět: |
Microbiology (medical)
Male Pediatrics medicine.medical_specialty Adolescent Critical Care Anemia Infecciones por coronavirus Critical Illness Enfermedad transmisible Disease Comorbidity Severity of Illness Index Risk Factors Severity of illness medicine Humans Prospective Studies Risk factor Prospective cohort study Child business.industry SARS-CoV-2 Organ dysfunction Pediatría Infant Newborn COVID-19 Infant Bayes Theorem medicine.disease Systemic Inflammatory Response Syndrome Systemic inflammatory response syndrome Infectious Diseases Child Preschool Pediatrics Perinatology and Child Health Female medicine.symptom business |
| Zdroj: | PEDIATRIC INFECTIOUS DISEASE JOURNAL r-FSJD. Repositorio Institucional de Producción Científica de la Fundació Sant Joan de Déu instname ABACUS. Repositorio de Producción Científica Universidad Europea (UEM) |
| ISSN: | 0891-3668 |
| Popis: | Background: We aimed to identify risk factors causing critical disease in hospitalized children with COVID-19 and to build a predictive model to anticipate the probability of need for critical care. Methods: We conducted a multicenter, prospective study of children with SARS-CoV-2 infection in 52 Spanish hospitals. The primary outcome was the need for critical care. We used a multivariable Bayesian model to estimate the probability of needing critical care. Results: The study enrolled 350 children from March 12, 2020, to July 1, 2020: 292 (83.4%) and 214 (73.7%) were considered to have relevant COVID-19, of whom 24.2% required critical care. Four major clinical syndromes of decreasing severity were identified: multi-inflammatory syndrome (MIS-C) (17.3%), bronchopulmonary (51.4%), gastrointestinal (11.6%), and mild syndrome (19.6%). Main risk factors were high C-reactive protein and creatinine concentration, lymphopenia, low platelets, anemia, tachycardia, age, neutrophilia, leukocytosis, and low oxygen saturation. These risk factors increased the risk of critical disease depending on the syndrome: the more severe the syndrome, the more risk the factors conferred. Based on our findings, we developed an online risk prediction tool (https://rserver.h12o.es/pediatria/EPICOAPP/, username: user, password: 0000). Conclusions: Risk factors for severe COVID-19 include inflammation, cytopenia, age, comorbidities, and organ dysfunction. The more severe the syndrome, the more the risk factor increases the risk of critical illness. Risk of severe disease can be predicted with a Bayesian model. Sin financiación 2.129 (2020) Q4,143/162 Inmunology 1.104 SJR (2021) Q1, 29/320 Pediatrics, Perinatology and Child Health No data IDR 2020 UEM |
| Databáze: | OpenAIRE |
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