https://pubmed.ncbi.nlm.nih.gov/38343837/

Background

Multisystem inflammatory syndrome in children is rare and clinically heterogeneous, with presentations overlapping Kawasaki disease and macrophage activation syndrome. Resolving it into subphenotypes would sharpen recognition and treatment. Latent class analysis is the natural tool, but it estimates many parameters and the smallest contributing hospital in this study identified only 32 cases, far short of what a site-level model would need.

Method

Running latent class analysis separately at each site fails because the number of classes need not agree and, even when it does, the classes are not comparable. The distributed multi-site latent class analysis approach instead learns a single set of latent classes shared across institutions while allowing the class proportions to differ by site. Conditions, laboratory results, and procedure information served as input features. Nine United States children’s hospitals in PEDSnet participated.

Main finding

From 864 identified cases drawn out of roughly 3.5 million patients, three clinically interpretable subphenotypes emerged. The first, covering about 46 percent of cases, presented mildly with minimal cardiac involvement and no intensive care requirement. The second, about 25 percent, carried high risk of shock along with cardiac and renal involvement. The remainder formed a third group with an intermediate profile.