Deep phenotyping of COVID-19 patients

Stanford OMOP participates in a network study that ran across 50 sites

Deep phenotyping of 34,128 adult patients hospitalised with COVID-19 in an international network study.

Oct 30, 2020: Our new research CDW, STARR-OMOP, launched an year ago, was used in a COVID-19 characterization study and published in Nature Communications. The study named CHARYBDIS (Characterizing Health Associated Risks, and Your Baseline Disease In SARS-COV-2) - describes the baseline demographic, clinical characteristics, treatments and outcomes of interest among individuals tested for SARS-CoV-2 and/or diagnosed with COVID-19 compared to Influenza patients from 2017-2018.

Abstract: Comorbid conditions appear to be common among individuals hospitalised with coronavirus disease 2019 (COVID-19) but estimates of prevalence vary and little is known about the prior medication use of patients. Here, we describe the characteristics of adults hospitalised with COVID-19 and compare them with influenza patients. We include 34,128 (US: 8362, South Korea: 7341, Spain: 18,425) COVID-19 patients, summarising between 4811 and 11,643 unique aggregate characteristics. COVID-19 patients have been majority male in the US and Spain, but predominantly female in South Korea. Age profiles vary across data sources. Compared to 84,585 individuals hospitalised with influenza in 2014-19, COVID-19 patients have more typically been male, younger, and with fewer comorbidities and lower medication use. While protecting groups vulnerable to influenza is likely a useful starting point in the response to COVID-19, strategies will likely need to be broadened to reflect the particular characteristics of individuals being hospitalised with COVID-19.

Data from some of the sites with low rates of COVID-19 infection at the time of manuscript submission, such as Stanford, are not reported in the paper. But you can look at Stanford summary data on the interactive website. The analytic code is available in OHDSI's github repository