dbGaP Study Accession: phs002945

NIH Institute/Center: NICHD

RADx Data Program: RADx-rad

DOI: 10.60773/277p-e595

Release Date: 11/07/2022

Study Description: The primary objective of this study was to design and validate a predictive decision support system for the identification, treatment and management of SARS-CoV-2 associated with multisystem inflammatory syndrome in children (MIS-C). To develop this system, the study adapted and retrained machine learning algorithms which have previously trained in patients with Kawasaki Disease, a pediatric inflammatory vasculopathy with clinical overlap with MIS-C but different etiology. This study, performed in collaboration with the International Kawasaki Disease Registry (IKDR) consortium. This dataset contains the development and international validation data for all algorithms developed as part of this study.

Updated Date: 12/09/2022

Principal Investigator: Manlhiot, Cedric

Has Data Files: No

Study Domain: Artificial Intelligence or Machine Learning; Multisystem Inflammatory Syndrome (MIS); Multisystem Inflammatory Syndrome in Children (MIS-C)

Data Collection Method: Disease Registry

Keywords: Kawasaki; Pediatrics

Study Design: Cross-Sectional

Multi-Center Study: Yes

Study Sites: See attached list

Data Types: Clinical; Electronic Medical Records; Environmental; Family History; Individual Phenotype; Questionnaire or Survey

Study Start Date: 01/01/2021

Study End Date: 04/30/2022

Species: Human Data

Estimated Cohort Size: 900

Study Population Focus: Children

Publication URL: https://pubmed.ncbi.nlm.nih.gov/35624313/; https://pubmed.ncbi.nlm.nih.gov/36455760/; https://pubmed.ncbi.nlm.nih.gov/36947454/; https://pubmed.ncbi.nlm.nih.gov/37290536/

Acknowledgement Statement: This study was supported through funding, 4R61HD105591-02, for the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) as part of the RADx-rad program. Data for this study was acquired through the International Kawasaki Disease Registry (IKDR). Approved users should acknowledge the provision of data access by dbGaP for accession phs002945.v1.p1, and the NIH RADx Data Hub. Approved users should also acknowledge the specific version(s) of the dataset(s) obtained from the NIH RADx Data Hub.

Funding Opportunity Announcement (FOA) Number: RFA-OD-20-023

NIH Grant or Contract Number(s): 4R61HD105591-02

Consent/Data Use Limitations: General Research Use; IRB required