Naimin Jing, Xiaokang Liu, Qiong Wu, Suchitra Rao, Asuncion Mejias, Mitchell Maltenfort, Julia Schuchard, Vitaly Lorman, Hanieh Razzaghi, Ryan Webb, Chuan Zhou, Ravi Jhaveri, Grace M Lee, Nathan M Pajor, Deepika Thacker, L Charles Bailey, Christopher B Forrest, Yong Chen
BACKGROUND: Multisystem inflammatory syndrome in children (MIS-C) is a severe post-acute sequela of SARS-CoV-2 infection. The highly diverse clinical features of MIS-C necessities characterizing its features by subphenotypes for improved recognition and treatment. However, jointly identifying subphenotypes in multi-site settings can be challenging. We propose a distributed multi-site latent class analysis (dMLCA) approach to jointly learn MIS-C subphenotypes using data across multiple institutions...
January 27, 2024: medRxiv