Skip to content

COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records

License

Notifications You must be signed in to change notification settings

BHFDSC/CCU013_01_ENG-COVID-19_event_phenotyping

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

59 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation




COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records

Johan H Thygesen, Christopher Tomlinson & Spiros Denaxas

How to cite this work

Now published in Lancet Digital Health:

COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records.
Johan H Thygesen, Christopher Tomlinson, Sam Hollings, Mehrdad A Mizani, Alex Handy, Ashley Akbari, Amitava Banerjee, Jennifer A Cooper, Alvina G Lai, Kezhi Li, Bilal A Mateen, Naveed Sattar, Reecha Sofat, Ana Torralbo, Honghan Wu, Angela Wood, Jonathan AC Sterne, Christina Pagel, William Whiteley, Cathie Sudlow, Harry Hemingway, Spiros Denaxas, on behalf of theLongitudinal Health and Wellbeing COVID-19 National Core Study and the CVD-COVID-UK/COVID-IMPACT Consortium.
Lancet Digital Health. Published online June 8, 2022 https://www.thelancet.com/journals/landig/article/PIIS2589-7500(22)00091-7. DOI: https://doi.org/10.1016/S2589-7500(22)00091-7

Preprint on medRxiv:

Understanding COVID-19 trajectories from a nationwide linked electronic health record cohort of 56 million people: phenotypes, severity, waves & vaccination.
Johan H Thygesen, Christopher R Tomlinson, Sam Hollings, Mehrdad A Mizani, Alex Handy, Ashley Akbari, Amitava Banerjee, Jennifer A Cooper, Alvina G Lai, Kezhi Li, Bilal A Mateen, Naveed Sattar, Reecha Sofat, Ana Torralbo, Honghan Wu, Angela Wood, Jonathan AC Sterne, Christina Pagel, William Whiteley, Cathie Sudlow, Harry Hemingway, Spiros Denaxas, on behalf of the CVD-COVID-UK Consortium and the CONVALESCENCE study.
medRxiv 2021.11.08.21265312; doi: https://doi.org/10.1101/2021.11.08.21265312

Code

Click here to view the analysis code.

Phenotyping algorithms and codelists are available here

Project approval

Data access approval was granted to the CVD-COVID-UK consortium (under project proposal CCU013: High-throughput electronic health record phenotyping approaches) through the NHS Digital online Data Access Request Service (ref. DARS-NIC-381078-Y9C5K). NHS Digital data have been made available for research under the Control of Patient Information (COPI) notice which mandated the sharing of national electronic health records for COVID-19 research. Further details are available within the supplementary section of the manuscript.

License

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this software except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0. Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

About

COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records

Topics

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Contributors 4

  •  
  •  
  •  
  •