Development and Validation of Multivariable Machine‐Learning Models for the Prediction of Multisystemic Inflammatory Syndrome Outcomes in Latin American Children
We developed and validated machine learning models for the prediction of MIS-C related outcomes that can help clinicians risk stratify patients to identify those most likely to have a severe outcome from MIS-C.
Authors
- Dora Estripeaut (ORCID: https://orcid.org/0000-0002-2042-0817)
- Gabriela Ivankovich‐Escoto (ORCID: https://orcid.org/0000-0001-9675-3143)
- Rolando Ulloa‐Gutiérrez (ORCID: https://orcid.org/0000-0002-9157-9227)
- Danilo Buonsenso (ORCID: https://orcid.org/0000-0001-8567-2639)
- Germán Camacho‐Moreno (ORCID: https://orcid.org/0000-0003-0472-798X)
- Iván Felipe Gutiérrez-Tobar (ORCID: https://orcid.org/0000-0002-9614-2040)
- Adriana H. Tremoulet (ORCID: https://orcid.org/0000-0001-9537-175X)
- Luca Mastrantoni (ORCID: https://orcid.org/0000-0003-1853-4927)
- Enrique Faugier Fuentes (ORCID: https://orcid.org/0000-0001-7807-1296)
- Olguita del Águila (ORCID: https://orcid.org/0000-0003-3085-0148)
- Marco Antonio Yamazaki‐Nakashimada (ORCID: https://orcid.org/0000-0002-7609-3923)
- J. García‐Silva
Institutions
- Università Cattolica del Sacro Cuore (IT)
- Universidad de Ciencias Medicas (CR)
- Universidad Autónoma de Nuevo León (MX)
- Agostino Gemelli University Polyclinic (IT)
- Universidad Nacional de Colombia (CO)
- University of California San Diego (US)
- Rady Children's Hospital-San Diego (US)
- Hospital Nacional Cayetano Heredia (PE)
- Hospital Infantil de México Federico Gómez (MX)
- Clínica Santa María (CO)
- Hospital Nacional de Niños (CR)
- Instituto Nacional de Pediatria (MX)
- National Academy of Sciences (CR)
- Hospital del Niño (PA)
- St Martins Hospital (GB)
- Hospital Universitario Nacional de Colombia (CO)
Publication Details
- Journal
- Acta Paediatrica
- Published
- 2025-09-01
- DOI
- https://doi.org/10.1111/apa.70290
- Primary Topic
- Kawasaki Disease and Coronary Complications
- Type
- article
- Field-Weighted Citation Impact
- 0.00