How multisystem inflammatory syndrome in children discriminated from Kawasaki disease: a differentiating score based on an inception cohort study.

Autor: Sobh, Ali, Mosa, Doaa Mosad, Khaled, Nada, Korkor, Mai S., Noureldin, Mohamed Ahmed, Eita, Ahmad M., Elnagdy, Marwa H., El-Bayoumi, Mohammed A.
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Zdroj: Clinical Rheumatology; Apr2023, Vol. 42 Issue 4, p1151-1161, 11p
Abstrakt: Background: About 25–50% of multisystem inflammatory syndrome in children (MIS-C) patients meet the criteria for diagnosis of Kawasaki disease (KD). The differentiation of both conditions is so challenging on clinical practice as the management of both is time dependant and precise diagnosis is fundamental. Method: Data were collected from children < 18 years old hospitalized with MIS-C or KD. Patient demographics, clinical, and laboratory data were compared, and a discrimination score was created to assist in clinical differentiation. Results: 72 patients with MIS-C and 18 with KD were included in the study. Patients with MIS-C had a higher prevalence of abdominal pain (p = 0.02), vomiting (p = 0.03), and cervical lymphadenopathy (p = 0.02) compared with KD cases. MIS-C patients had higher liver enzymes (aspartate aminotransferase (AST) (p = 0.04), alanine aminotransferase (ALT) (p = 0.03), serum creatinine (p = 0.03), and lower platelet count nadir (p = 0.02) than KD. Four variables were detected in the regression analysis model, and the independent predictors were utilized to generate a scoring model that distinguished MIS-C from KD with an area under the curve of 0.70. Conclusion: This study constructed a prediction model for differentiation of MIS-C from KD based on clinical and laboratory profiles. This model will be valuable to guide clinicians in the treatment decisions. Key Points • Children with MIS-C are more likely to have gastrointestinal symptoms, cervical lymphadenopathy, and respiratory involvement than KD patients. • Elevated liver enzymes and lower platelet count are more pronounced laboratory findings in MIS-C than KD. • This study constructed a prediction model for differentiation of MIS-C from KD based on clinical and laboratory profiles. This model will be valuable to guide clinicians in the treatment decisions. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index
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