TY - JOUR
KW - Clinical
KW - epidemiology
KW - health informatics
KW - infectious diseases
KW - public health
AU - M. Mizani
AU - A. Dashtban
AU - L. Pasea
AU - A. Lai
AU - J. Thygesen
AU - C. Tomlinson
AU - A. Handy
AU - J. Mamza
AU - T. Morris
AU - S. Khalid
AU - F. Zaccardi
AU - M. Macleod
AU - F. Torabi
AU - D. Canoy
AU - A. Akbari
AU - C. Berry
AU - T. Bolton
AU - J. Nolan
AU - K. Khunti
AU - S. Denaxas
AU - H. Hemingway
AU - C. Sudlow
AU - A. Banerjee
AD - Institute of Health Informatics, University College London, London NW1 2DA, UK.
BHF Data Science Centre, Health Data Research UK, London, NW1 2BE, UK.
Medical and Scientific Affairs, BioPharmaceuticals Medical, AstraZeneca, Cambridge, CB2 0AA, UK.
Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, OX3 7HE, UK.
Leicester Diabetes Centre, University of Leicester, Leicester, LE5 4PW, UK.
School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Aberdeen, AB24 3FX, UK.
Faculty of Medicine, Health and Life Science, Swansea University, Swansea, SA2 8QA, UK.
Nuffield Department of Women's and Reproductive Health, University of Oxford, Oxford, OX3 9DU, UK.
Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, G12 8TA, UK.
AN - 36374585
BT - J R Soc Med
DO - 10.1177/01410768221131897
DP - NLM
ET - 2022/11/15
LA - eng
N1 - 1758-1095
Mizani, Mehrdad A
Dashtban, Ashkan
Pasea, Laura
Lai, Alvina G
Thygesen, Johan
Tomlinson, Chris
Orcid: 0000-0002-0903-5395
Handy, Alex
Mamza, Jil B
Morris, Tamsin
Khalid, Sara
Zaccardi, Francesco
Macleod, Mary Joan
Torabi, Fatemeh
Canoy, Dexter
Akbari, Ashley
Orcid: 0000-0003-0814-0801
Berry, Colin
Bolton, Thomas
Nolan, John
Khunti, Kamlesh
Denaxas, Spiros
Hemingway, Harry
Sudlow, Cathie
Banerjee, Amitava
Orcid: 0000-0001-8741-3411
CVD-COVID-UK Consortium
Journal Article
England
J R Soc Med. 2022 Nov 14:1410768221131897. doi: 10.1177/01410768221131897.
PY - 2022
SN - 0141-0768
EP - 1410768221131897
T2 - J R Soc Med
TI - Using national electronic health records for pandemic preparedness: validation of a parsimonious model for predicting excess deaths among those with COVID-19-a data-driven retrospective cohort study
ER -