A retrospective chart review analysis in the first 24 hours after hospital admission revealed four predictors that discriminate between children with multisystem inflammatory syndrome and other syndromes: hypotension, abdominal pain, rash, and serum sodium concentration. Identifying affected children early is key to the successful management of this dangerous syndrome.


Multisystem inflammatory syndrome (MIS-C) is a new syndrome associated with SARS-CoV-2 infection that has been reported in children in increasing numbers. MIS-C associated with COVID-19 may rapidly progress to hypotension and shock with cardiac and other end-organ injuries in affected children. “Clinically, we often found it difficult to separate MIS-C from other common childhood illnesses. To solve this problem, we set out to identify features that are distinctive of our patients with MIS-C and to use those for a prediction model,” said Dr. Matthew Clark (Vanderbilt University Medical Center).1

In a retrospective chart review of children admitted to Vanderbilt Children´s Hospital between June 10, 2020 and April 8, 2021 and evaluated for MIS-C, the researchers collected standardized clinical, laboratory, and cardiac features within the first 24 hours of presentation in the hospital. The diagnosis of MIS-C was determined by the treatment team service and retrospectively reviewed and confirmed by both a pediatric rheumatologist and a pediatric infectious disease specialist. Logistic regression with bootstrapped backward selection was used to identify the most important predictors for MIS-C.

During the study period, 127 children were admitted for evaluation for MIS-C. In 45 patients, the MIS-C diagnosis was confirmed. In the final risk prediction model, the researchers identified four predictors for MIS-C: hypotension, abdominal pain, a rash of any kind, and hyponatremia. The model showed excellent discrimination with a C-index of 0.90 (95% CI, 0.85-0.94).

The authors demonstrated that their clinical diagnostic prediction model has excellent discrimination and could assist clinicians in distinguishing patients with MIS-C from those without. “We are planning to test our model with external and prospective validation, and hopefully, it can be of use for clinicians in the future,” Dr. Clark concluded.


  1. Clark M, et al. A prediction model to distinguish patients with multisystem inflammatory syndrome in children. Abstract L09. ACR Convergence 2021, 3– November.

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