COVID-19 indirect impacts on cardiovascular health: rapid analytics using linked electronic health records
Benjamin D Bray, Daniel O’Connell, Danielle E Robinson, Hannah Whittaker, John Nolan, Tom Bolton, Elizabeth I Adesanya, Alison Barnett, Amitava Banerjee, Julia A Critchley, Spiros Denaxas, Kamlesh Khunti, Evan Kontopantelis, Vahe Nafilyan, Tom Porter, Jennifer K Quint, Reecha Sofat, Chris Tomlinson, William Whiteley, Alasdair Wood, Angela Wood, Jonathan Pearson-Stuttard, Cathie Sudlow, on behalf of the CVD-COVID-UK/COVID-IMPACT Consortium
The aim of the study is to explore the hypothesis that higher than expected deaths after the COVID-19 pandemic are at least partly caused by gaps in the diagnosis and management of major cardiovascular risk factors (hypertension and atrial fibrillation).
Citation to follow. The preprint can be viewed here: https://dx.doi.org/10.2139/ssrn.4972808
- View the analysis code used in NHS England's SDE for England
- View the phenotyping algorithms and codelists used in NHS England's SDE for England
This is a sub-project of project CCU003 approved by the CVD-COVID-UK / COVID-IMPACT Approvals & Oversight Board (sub-project: CCU003_05).
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.