TY - JOUR
AU - Thygesen, Johan H
AU - Tomlinson, Christopher
AU - Hollings, Sam
AU - Mizani, Mehrdad A.
AU - Handy, Alex
AU - Akbari, Ashley
AU - Banerjee, Amitava
AU - Cooper, Jennifer A.
AU - Lai, Alvina G.
AU - Li, Kezhi
AU - Mateen, Bilal A
AU - Sattar, Naveed
AU - Sofat, Reecha
AU - Torralbo, Ana
AU - Wu, Honghan
AU - Wood, Angela M
AU - Sterne, Jonathan A C
AU - Pagel, Christina
AU - Whiteley, William N
AU - Sudlow, Cathie L M
AU - Hemingway, Harry
AU - Denaxas, Spiros
AU - CVD-COVID-UK Consortium
AU - COVID-19 National Core Study
PY - 2022
DA - June
TI - COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records
JO - The Lancet Digital Health
EP - E557
VL - 4
IS - 7
DO - https://doi.org/10.1016/S2589-7500(22)00091-7
AB - BACKGROUND: Updatable estimates of COVID-19 onset, progression, and trajectories underpin pandemic mitigation efforts. To identify and characterise disease trajectories, we aimed to define and validate ten COVID-19 phenotypes from nationwide linked electronic health records (EHR) using an extensible framework.
PB - Elsevier
UR - https://www.research.ed.ac.uk/en/publications/dacbf2dd-4af4-4e29-8a45-e12b1640a037
KW - Coronavirus (COVID-19)
KW - Digital health and technology
ER