Multiomics single timepoint measurements to predict severe COVID-19 - Authors' reply.

Garapati, Kishore; Byeon, Seul Kee; Walsh, Jesse R; Jenkinson, Garrett; Cattaneo, Roberto; O'Horo, John C; Badley, Andrew D; Pandey, Akhilesh

Garapati, Kishore; Byeon, Seul Kee; Walsh, Jesse R; Jenkinson, Garrett; Cattaneo, Roberto; O'Horo, John C; Badley, Andrew D; Pandey, Akhilesh.

Garapati K; Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA; Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka, India; Manipal Academy of Higher Education, Manipal, Karnataka, India.
Byeon SK; Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA.
Walsh JR; Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA.
Jenkinson G; Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA.
Cattaneo R; Department of Molecular Medicine, Mayo Clinic, Rochester, MN 55905, USA.
O'Horo JC; Department of Internal Medicine, Mayo Clinic, Rochester, MN 55905, USA.
Badley AD; Department of Internal Medicine, Mayo Clinic, Rochester, MN 55905, USA.
Pandey A; Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA; Center for Individualized Medicine, Mayo Clinic, Rochester, MN 55905, USA. Electronic address: pandey.akhilesh@mayo.edu.

Lancet Digit Health ; 5(2): e57, 2023 02.

Article in English | MEDLINE | ID: covidwho-2211791

Subject(s)

COVID-19; Humans; Multiomics; SARS-CoV-2

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Prognostic study Limits: Humans Language: English Journal: Lancet Digit Health Year: 2023 Document Type: Article Affiliation country: S2589-7500(22)00250-3

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