Decreased Clinical Severity of Pediatric Acute COVID-19 and MIS-C and Increase of Incidental Cases during the Omicron Wave in Comparison to the Delta Wave

Kenney, Patrick O.; Chang, Arthur J.; Krabill, Lorna; Hicar, Mark D.

doi:10.3390/v15010180

Cited by 17 publications

(16 citation statements)

References 23 publications

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“…Our results also favor a syndrome occurring in genetically predisposed children because 46% of the patients were of sub-Saharan African origin. This observation agreed with studies in the United States showing African Americans with a risk of MIS-C that was nine times greater than that for Caucasians ( 16 – 18 ).…”

Section: Discussionsupporting

confidence: 91%

Multisystem inflammatory syndrome in children during the COVID-19 waves: data from the Juvenile Inflammatory Rheumatism cohort

et al. 2023

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IntroductionMultisystem inflammatory syndrome in children (MIS-C) is a new condition that first appeared in children and adolescents during the COVID-19 pandemic. We aimed to describe the diagnostic course, clinical and biological manifestations, and treatment of MIS-C during the first three COVID-19 waves.MethodsWe extracted patient data from the Juvenile Inflammatory Rheumatism (JIR) cohort. We analyzed data for patients meeting the World Health Organization diagnostic criteria for MIS-C from the start of the COVID-19 pandemic from March 2020 to June 30, 2021. We then compared data for patients in wave one to those in waves two and three.ResultsWe identified 136 patients with MIS-C. The median age decreased but not significantly during the waves, from 9.9 years to 7.3 years (p = 0.105). Boys represented 52.2% (n = 71) of patients, and 46% (n = 41) of patients originated from sub-Saharan Africa (p < 0.001). Patients presented less diarrhea (p = 0.004), respiratory distress (p < 0.001), and myocarditis (p < 0.001) with progressive waves. Biological inflammation also decreased, namely, C-reactive protein level (p < 0.001), neutrophil count (p = 0.004), and albumin level (p < 0.001). Patients received more corticosteroids (p < 0.001) and required less ventilation support (p < 0.01) and less inotrope treatment (p < 0.001) in the later waves. The duration of hospitalization gradually decreased (p < 0.001), as did critical care unit admissions (p = 0.002).ConclusionOver the three COVID-19 waves, with a change in the management of MIS-C, children in the JIR cohort in France showed a less severe disease course, in particular, a greater use of corticosteroids. This observation may reflect the impact of both improved management and different SARS-CoV-2 variant.

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Section: Discussionsupporting

confidence: 91%

Multisystem inflammatory syndrome in children during the COVID-19 waves: data from the Juvenile Inflammatory Rheumatism cohort

et al. 2023

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“…Variants may present with differences in symptomatology as a result of a number of factors including differences in mutations in spike proteins, receptor binding, and ability to escape host antibodies [20]. As has been previously reported [21][22][23][24][25], we found that fever or chills was the most common COVID-19 symptom across variants. In our cohort, shortness of breath was less common in the Omicron compared to pre-Delta era.…”

Section: Comparison With Prior Worksupporting

confidence: 80%

Moving Biosurveillance Beyond Coded Data: AI for Symptom Detection from Physician Notes

McMurry,

Zipursky,

Geva

et al. 2023

Preprint

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Background Real-time surveillance of emerging infectious diseases necessitates a dynamically evolving, computable case definition, which frequently incorporates symptom-related criteria. For symptom detection, both population health monitoring platforms and research initiatives primarily depend on structured data extracted from electronic health records. Objective To validate and test an artificial intelligence (AI) based Natural Language Processing (NLP) pipeline for detecting COVID-19 symptoms from physician notes. Methods Subjects in this retrospective cohort study are patients 21 years old and younger, who presented to a pediatric emergency department (ED) at a large academic children's hospital between March 1, 2020 and May 31, 2022. ED notes for all patients were processed with an NLP pipeline tuned to detect the mention of 11 COVID-19 symptoms based on CDC criteria. For a gold standard, 3 subject matter experts labeled 226 ED notes and had strong agreement (F1=98.6; PPV=97.2; Recall=100.0). F1, PPV, and recall were used to compare the performance of both NLP and ICD-10 to the gold standard chart review. As a formative use case, variations in symptom patterns were measured across SARS-Cov2 variant eras. Results There were 85,678 ED encounters during the study period, 4.0% with patients with COVID-19. NLP was more accurate at identifying encounters with patients that had any of the COVID-19 symptoms (F1=79.6) than ICD-10 codes (F1=45.1%). NLP accuracy was higher for positive symptoms (recall=93%) than ICD-10 (recall=30%). However, ICD-10 accuracy was higher for negative symptoms (specificity=99.4%) than NLP (specificity=91.7%). Congestion or runny nose showed the highest accuracy difference: NLP F1=82.8%, ICD-10 F1=4.2%. Prevalence of NLP symptoms among patients with COVID-19 differed across variant eras. And patients with COVID-19 were more likely to have each symptom than patients without this disease. Effect sizes (odds ratios) varied across pandemic eras. Conclusions This study establishes the value of AI based NLP as a highly effective tool for real-time COVID-19 symptom detection in pediatric patients, outperforming traditional ICD-10 methods. It also reveals the evolving nature of symptom prevalence across different virus variants, underscoring the need for dynamic, technology-driven approaches in infectious disease surveillance.

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“…30 , 31 These studies have also found MIS-C to be less severe during Omicron waves, requiring shorter hospital and ICU stays as well as less vasopressor use. 31 , 32 Ongoing monitoring for incidence following infection from future variants will be essential as risk may continue to change.…”

Section: Discussionmentioning

confidence: 99%

Paediatric inflammatory multisystem syndrome in Canada: population-based surveillance and role of SARS-CoV-2 linkage

et al. 2023

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Background Paediatric inflammatory multisystem syndrome (PIMS) is a rare condition temporally associated with SARS-CoV-2 infection. Using national surveillance data, we compare presenting features and outcomes among children hospitalized with PIMS by SARS-CoV-2 linkage, and identify risk factors for intensive care (ICU). Methods Cases were reported to the Canadian Paediatric Surveillance Program by a network of >2800 pediatricians between March 2020 and May 2021. Patients with positive versus negative SARS-CoV-2 linkages were compared, with positive linkage defined as any positive molecular or serologic test or close contact with confirmed COVID-19. ICU risk factors were identified with multivariable modified Poisson regression. Results We identified 406 children hospitalized with PIMS, including 49.8% with positive SARS-CoV-2 linkages, 26.1% with negative linkages, and 24.1% with unknown linkages. The median age was 5.4 years (IQR 2.5–9.8), 60% were male, and 83% had no comorbidities. Compared to cases with negative linkages, children with positive linkages experienced more cardiac involvement (58.8% vs. 37.4%; p < 0.001), gastrointestinal symptoms (88.6% vs. 63.2%; p < 0.001), and shock (60.9% vs. 16.0%; p < 0.001). Children aged ≥6 years and those with positive linkages were more likely to require ICU. Conclusions Although rare, 30% of PIMS hospitalizations required ICU or respiratory/hemodynamic support, particularly those with positive SARS-CoV-2 linkages. Impact We describe 406 children hospitalized with paediatric inflammatory multisystem syndrome (PIMS) using nationwide surveillance data, the largest study of PIMS in Canada to date. Our surveillance case definition of PIMS did not require a history of SARS-CoV-2 exposure, and we therefore describe associations of SARS-CoV-2 linkages on clinical features and outcomes of children with PIMS. Children with positive SARS-CoV-2 linkages were older, had more gastrointestinal and cardiac involvement, and hyperinflammatory laboratory picture. Although PIMS is rare, one-third required admission to intensive care, with the greatest risk amongst those aged ≥6 years and those with a SARS-CoV-2 linkage.

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Decreased Clinical Severity of Pediatric Acute COVID-19 and MIS-C and Increase of Incidental Cases during the Omicron Wave in Comparison to the Delta Wave

Cited by 17 publications

References 23 publications

Multisystem inflammatory syndrome in children during the COVID-19 waves: data from the Juvenile Inflammatory Rheumatism cohort

Multisystem inflammatory syndrome in children during the COVID-19 waves: data from the Juvenile Inflammatory Rheumatism cohort

Moving Biosurveillance Beyond Coded Data: AI for Symptom Detection from Physician Notes

Paediatric inflammatory multisystem syndrome in Canada: population-based surveillance and role of SARS-CoV-2 linkage

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