Multi-site analysis of COVID-19 and new-onset diabetes reveals need for improved sensitivity of EHR-based COVID-19 phenotypes-a DiCAYA Network analysis.

doi:10.1093/jamia/ocaf229

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Article

Multi-site analysis of COVID-19 and new-onset diabetes reveals need for improved sensitivity of EHR-based COVID-19 phenotypes-a DiCAYA Network analysis.

Journal of the American Medical Informatics Association : JAMIA - 1 Mar 2026

Conderino Sarah, Kirchner H Lester, Thorpe Lorna E, Divers Jasmin, Hirsch Annemarie G, Nordberg Cara M, Schwartz Brian S, Zhang Lu, Cai Bo, Rudisill Caroline, Obeid Jihad S, Liese Angela, Allen Katie S, Dixon Brian E, Crume Tessa, Dabelea Dana, Burgett Shawna, Bellatorre Anna, Shao Hui, Bian Jiang, Guo Yi, Bost Sarah, Lyu Tianchen, Reynolds Kristi, Mefford Matthew T, Zhou Hui, Zhou Matt, Lustigova Eva, Utidjian Levon H, Maltenfort Mitchell, Kamboj Manmohan, Mendonca Eneida A, Hanley Patrick, Zaganjor Ibrahim, Pavkov Meda E, Rosenman Marc, Titus Andrea R

Abstract excerpt

OBJECTIVE: We discuss implications of potential ascertainment biases for studies examining diabetes risk following SARS-CoV-2 infection using electronic health records (EHRs). We quantitatively explore sensitivity of results to misclassification of COVID-19 status using data from the U.S.-based Diabetes in Children, Adolescents and Young Adults (DiCAYA) Network on children (≤17 years) and young adults (18-44...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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PMID: 41442443
DOI: 10.1093/jamia/ocaf229
PMCID: PMC12884381

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