Differentiating multisystem inflammatory syndrome in children: a single-centre retrospective cohort study.

OBJECTIVE

Features of multisystem inflammatory syndrome in children (MIS-C) overlap with other febrile illnesses, hindering prompt and accurate diagnosis. The objectives of this study were to identify clinical and laboratory findings that distinguished MIS-C from febrile illnesses in which MIS-C was considered but ultimately excluded, and to examine the diseases that most often mimicked MIS-C in a tertiary medical centre.

STUDY

DESIGN

We identified all children hospitalised with fever who were evaluated for MIS-C at our centre and compared clinical signs and symptoms, SARS-CoV-2 status and laboratory studies between those with and without MIS-C. Multivariable logistic LASSO (least absolute shrinkage and selection operator) regression was used to identify the most discriminative presenting features of MIS-C.

RESULTS

We identified 50 confirmed MIS-C cases (MIS-C+) and 68 children evaluated for, but ultimately not diagnosed with, MIS-C (MIS-C-). In univariable analysis, conjunctivitis, abdominal pain, fatigue, hypoxaemia, tachypnoea and hypotension at presentation were significantly more common among MIS-C+ patients. MIS-C+ and MIS-C- patients had similar elevations in C-reactive protein (CRP), but were differentiated by thrombocytopenia, lymphopenia, and elevated ferritin, neutrophil/lymphocyte ratio, BNP and troponin. In multivariable analysis, predictors of MIS-C included age, neutrophil/lymphocyte ratio, platelets, conjunctivitis, oral mucosa changes, abdominal pain and hypotension.

CONCLUSIONS

Among hospitalised children undergoing evaluation for MIS-C, children with MIS-C were older, more likely to present with conjunctivitis, oral mucosa changes, abdominal pain and hypotension, and had higher neutrophil/lymphocyte ratios and lower platelet counts. These data may be helpful for discrimination of MIS-C from other febrile illnesses, including bacterial lymphadenitis and acute viral infection, with overlapping features.