Dataset Information

Risk factors for disease severity among children with Covid-19: a clinical prediction model.

ABSTRACT:

Background

Children account for a significant proportion of COVID-19 hospitalizations, but data on the predictors of disease severity in children are limited. We aimed to identify risk factors associated with moderate/severe COVID-19 and develop a nomogram for predicting children with moderate/severe COVID-19.

Methods

We identified children ≤ 12 years old hospitalized for COVID-19 across five hospitals in Negeri Sembilan, Malaysia, from 1 January 2021 to 31 December 2021 from the state's pediatric COVID-19 case registration system. The primary outcome was the development of moderate/severe COVID-19 during hospitalization. Multivariate logistic regression was performed to identify independent risk factors for moderate/severe COVID-19. A nomogram was constructed to predict moderate/severe disease. The model performance was evaluated using the area under the curve (AUC), sensitivity, specificity, and accuracy.

Results

A total of 1,717 patients were included. After excluding the asymptomatic cases, 1,234 patients (1,023 mild cases and 211 moderate/severe cases) were used to develop the prediction model. Nine independent risk factors were identified, including the presence of at least one comorbidity, shortness of breath, vomiting, diarrhea, rash, seizures, temperature on arrival, chest recessions, and abnormal breath sounds. The nomogram's sensitivity, specificity, accuracy, and AUC for predicting moderate/severe COVID-19 were 58·1%, 80·5%, 76·8%, and 0·86 (95% CI, 0·79 - 0·92) respectively.

Conclusion

Our nomogram, which incorporated readily available clinical parameters, would be useful to facilitate individualized clinical decisions.

SUBMITTER: Ng DC

PROVIDER: S-EPMC10259359 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature

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Publications

Risk factors for disease severity among children with Covid-19: a clinical prediction model.

Ng David Chun-Ern DC Liew Chuin-Hen CH Tan Kah Kee KK Chin Ling L Ting Grace Sieng Sing GSS Fadzilah Nur Fadzreena NF Lim Hui Yi HY Zailanalhuddin Nur Emylia NE Tan Shir Fong SF Affan Muhamad Akmal MA Nasir Fatin Farihah Wan Ahmad FFWA Subramaniam Thayasheri T Ali Marlindawati Mohd MM Rashid Mohammad Faid Abd MFA Ong Song-Quan SQ Ch'ng Chin Chin CC

BMC infectious diseases 20230612 1

<h4>Background</h4>Children account for a significant proportion of COVID-19 hospitalizations, but data on the predictors of disease severity in children are limited. We aimed to identify risk factors associated with moderate/severe COVID-19 and develop a nomogram for predicting children with moderate/severe COVID-19.<h4>Methods</h4>We identified children ≤ 12 years old hospitalized for COVID-19 across five hospitals in Negeri Sembilan, Malaysia, from 1 January 2021 to 31 December 2021 from the ...[more]

PMID: 37308825

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Project description:We aimed to identify the spectrum of disease in children with COVID-19, and the risk factors for admission in paediatric intensive care units (PICUs). We conducted a multicentre, prospective study of children with SARS-CoV-2 infection in 76 Spanish hospitals. We included children with COVID-19 or multi-inflammatory syndrome (MIS-C) younger than 18 years old, attended during the first year of the pandemic. We enrolled 1200 children. A total of 666 (55.5%) were hospitalised, and 123 (18.4%) required admission to PICU. Most frequent major clinical syndromes in the cohort were mild syndrome (including upper respiratory tract infection and flu-like syndrome, skin or mucosae problems and asymptomatic), 44.8%; bronchopulmonary syndrome (including pneumonia, bronchitis and asthma flare), 18.5%; fever without a source, 16.2%; MIS-C, 10.6%; and gastrointestinal syndrome, 10%. In hospitalised children, the proportions were 28.5%, 25.7%, 16.5%, 19.1% and 10.2%, respectively. Risk factors associated with PICU admission were age in months (OR: 1.007; 95% CI 1.004 to 1.01), MIS-C (OR: 14.4, 95% CI 8.9 to 23.8), chronic cardiac disease (OR: 4.8, 95% CI 1.8 to 13), asthma or recurrent wheezing (OR: 2.5, 95% CI 1.2 to 5.2) and after excluding MIS-C patients, moderate/severe liver disease (OR: 8.6, 95% CI 1.6 to 47.6). However, asthmatic children were admitted into the PICU due to MIS-C or pneumonia, not due to asthma flare.Conclusion: Hospitalised children with COVID-19 usually present as one of five major clinical phenotypes of decreasing severity. Risk factors for PICU include MIS-C, elevation of inflammation biomarkers, asthma, moderate or severe liver disease and cardiac disease. What is Known: • All studies suggest that children are less susceptible to serious SARS-CoV-2 infection when compared to adults. Most studies describe symptoms at presentation. However, it remains unclear how these symptoms group together into clinically identifiable syndromes and the severity associated with them. What is New: • We have gathered the primary diagnoses into five major syndromes of decreasing severity: MIS-C, bronchopulmonary syndrome, gastrointestinal syndrome, fever without a source and mild syndrome. Classification of the children in one of the syndromes is unique and helps to assess the risk of critical illness and to define the spectrum of the disease instead of just describing symptoms and signs.

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Dataset Information

Risk factors for disease severity among children with Covid-19: a clinical prediction model.

Background

Methods

Results

Conclusion

Publications

Risk factors for disease severity among children with Covid-19: a clinical prediction model.

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