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J Pediatr ; 2021 Sep 25.
Article in English | MEDLINE | ID: covidwho-1527773


OBJECTIVES: To determine the time to reverse transcription-polymerase chain reaction (RT-PCR) negativity after the first positive RT-PCR test, factors associated with longer time to RT-PCR negativity, proportion of children seroconverting after proven severe acute respiratory syndrome coronavirus 2 infection, and factors associated with the lack of seroconversion. STUDY DESIGN: The Epidemiological Study of Coronavirus in Children of the Spanish Society of Pediatrics is a multicenter study conducted in Spanish children to assess the characteristics of coronavirus disease 2019. In a subset of patients, 3 serial RT-PCR tests on nasopharyngeal swab specimens were performed after the first RT-PCR test, and immunoglobulin G serology for severe acute respiratory syndrome coronavirus 2 antibodies was performed in the acute and follow-up (<14 and ≥14 days after diagnosis) phase. RESULTS: In total, 324 patients were included in the study. The median time to RT-PCR negativity was 17 days (IQR, 8-29 days), and 35% of patients remained positive more than 4 weeks after the first RT-PCR test. The probability of RT-PCR negativity did not differ across groups defined by sex, disease severity, immunosuppressive drugs, or clinical phenotype. Globally, 24% of children failed to seroconvert after infection. Seroconversion was associated with hospitalization, persistence of RT-PCR positivity, and days of fever. CONCLUSIONS: Time to RT-PCR negativity was long, regardless of the severity of symptoms or other patient features. This finding should be considered when interpreting RT-PCR results in a child with symptoms, especially those with mild symptoms. Seroprevalence and postimmunization studies should consider that 11 in 4 infected children fail to seroconvert.

Pediatr Infect Dis J ; 40(8): e287-e293, 2021 08 01.
Article in English | MEDLINE | ID: covidwho-1305449


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 (, 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.

COVID-19/diagnosis , Systemic Inflammatory Response Syndrome/diagnosis , Adolescent , Bayes Theorem , COVID-19/epidemiology , Child , Child, Preschool , Comorbidity , Critical Care , Critical Illness , Female , Humans , Infant , Infant, Newborn , Male , Prospective Studies , Risk Factors , SARS-CoV-2/isolation & purification , Severity of Illness Index , Systemic Inflammatory Response Syndrome/epidemiology