Published in

Wiley, Developmental Medicine & Child Neurology, 2024

DOI: 10.1111/dmcn.15898

Links

Tools

Export citation

Search in Google Scholar

Common data elements for arthrogryposis multiplex congenita: An international framework

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

Full text: Unavailable

Green circle
Preprint: archiving allowed
Orange circle
Postprint: archiving restricted
Red circle
Published version: archiving forbidden
Data provided by SHERPA/RoMEO

Abstract

AbstractAimTo facilitate multisite studies and international clinical research, this study aimed to identify consensus‐based, standardized common data elements (CDEs) for arthrogryposis multiplex congenita (AMC).MethodA mixed‐methods study comprising of several focus group discussions and three rounds of modified Delphi surveys to achieve consensus using two tiered‐rating scales were conducted.ResultsOverall, 45 clinical experts and adults with lived experience (including 12 members of an AMC consortium) participated in this study from 11 countries in North America, Europe, and Australia. The CDEs include 321 data elements and 19 standardized measures across various domains from fetal development to adulthood. Data elements pertaining to AMC phenotypic traits were mapped according to the Human Phenotype Ontology. A universal governance structure, local operating protocols, and sustainability plans were identified as the main facilitators, whereas limited capacity for data sharing and the need for a federated informatics infrastructure were the main barriers.InterpretationCollection of systematic data on AMC using CDEs will allow investigations on etiological pathways, describe epidemiological profile, and establish genotype–phenotype correlations in a standardized manner. The proposed CDEs will facilitate international multidisciplinary collaborations by improving large‐scale studies and opportunities for data sharing, knowledge translation, and dissemination.