Case-control study assesses ACR algorithm's accuracy for diagnosing MIS-C in children, suggesting effective identification of cases.
Diagnosing Multisystem Inflammatory Syndrome in Children (MIS-C) is challenging, as it shares clinical features with other childhood febrile illnesses. In response to the emergence of this syndrome during the pandemic, the American College of Rheumatology (ACR) developed a screening algorithm for the evaluation of MIS-C. We aimed to determine the accuracy of the ACR algorithm in distinguishing patients with MIS-C from other febrile children. A single-center case-control study was conducted on children with suspected or confirmed MIS-C from March 2020 to March 2022. The cohort was divided into two groups: the MIS-C group, including children with confirmed MIS-C, and febrile controls, consisting of children suspected but ultimately not diagnosed with MIS-C. The ACR MIS-C screening algorithm was retrospectively applied to both groups. The diagnosis obtained was compared with the WHO and CSTE/CDC case definitions. Sensitivity, specificity, and 95% confidence intervals were calculated. 402 children (241 MIS-C, 161 febrile controls) were included. Median age was 4.2 years, and 58.9% were male. The ACR screening algorithm had 74.3% sensitivity, 99.2% specificity, and 87.0% balanced accuracy when the WHO case definition was used as the gold standard; and 86.2% sensitivity, 95.8% specificity, and 91.0% balanced accuracy when the CSTE/CDC case definition was the gold standard. The ACR MIS-C screening algorithm demonstrates high specificity, accuracy, and good sensitivity in identifying children with MIS-C at the onset of the disease. Despite being developed early in the pandemic with limited data available, the ACR algorithm effectively differentiates children with MIS-C from febrile controls.
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Mastrangelo et al. (2025) studied this question.
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