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Lookup NU author(s): Dr Dexter CanoyORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2023 Author(s) (or their employer(s)). Objective: In individuals with complex underlying health problems, the association between systolic blood pressure (SBP) and cardiovascular disease is less well recognised. The association between SBP and risk of cardiovascular events in patients with chronic obstructive pulmonary disease (COPD) was investigated. Methods: and analysis In this cohort study, 39 602 individuals with a diagnosis of COPD aged 55-90 years between 1990 and 2009 were identified from validated electronic health records (EHR) in the UK. The association between SBP and risk of cardiovascular end points (composite of ischaemic heart disease, heart failure, stroke and cardiovascular death) was analysed using a deep learning approach. Results: In the selected cohort (46.5% women, median age 69 years), 10 987 cardiovascular events were observed over a median follow-up period of 3.9 years. The association between SBP and risk of cardiovascular end points was found to be monotonic; the lowest SBP exposure group of <120 mm Hg presented nadir of risk. With respect to reference SBP (between 120 and 129 mm Hg), adjusted risk ratios for the primary outcome were 0.99 (95% CI 0.93 to 1.05) for SBP of <120 mm Hg, 1.02 (0.97 to 1.07) for SBP between 130 and 139 mm Hg, 1.07 (1.01 to 1.12) for SBP between 140 and 149 mm Hg, 1.11 (1.05 to 1.17) for SBP between 150 and 159 mm Hg and 1.16 (1.10 to 1.22) for SBP ≥160 mm Hg. Conclusion: Using deep learning for modelling EHR, we identified a monotonic association between SBP and risk of cardiovascular events in patients with COPD.
Author(s): Rao S, Nazarzadeh M, Li Y, Canoy D, Mamouei M, Salimi-Khorshidi G, Rahimi K
Publication type: Article
Publication status: Published
Journal: Heart
Year: 2023
Volume: 109
Issue: 16
Pages: 1216-1222
Print publication date: 01/08/2023
Online publication date: 20/04/2023
Acceptance date: 04/04/2023
Date deposited: 01/03/2024
ISSN (print): 1355-6037
ISSN (electronic): 1468-201X
Publisher: BMJ Publishing Group
URL: https://doi.org/10.1136/heartjnl-2023-322431
DOI: 10.1136/heartjnl-2023-322431
Data Access Statement: Data may be obtained from a third party and are not publicly available. More details of the data and data sharing is found on the CPRD website (https://www.cprd.com). Targeted-BEHRT source code can be found on the Deep Medicine GitHub site (https://github.com/deepmedicine/Targeted-BEHRT). Example code for conducting an observational study on mock data and estimating risk ratio can also be found in this code repository.
PubMed id: 37080767
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