Bayesian network modelling study to identify factors influencing the risk of cardiovascular disease in Canadian adults with hepatitis C virus infection
Bayesian network modelling study to identify factors influencing the risk of cardiovascular disease in Canadian adults with hepatitis C virus infection
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- creativework.keywords - en
- Adult
- Aged
- Bayes Theorem
- Canada / epidemiology
- Cross-Sectional Studies
- Female
- Heart Disease Risk Factors
- Hepatitis C / epidemiology
- Humans
- Male
- Middle Aged
- dc.contributor.author
- Badawi, Alaa
- Di Giuseppe, Giancarlo
- Gupta, Alind
- Poirier, Abbey
- Arora, Paul
- dc.date.accessioned
- 2024-06-13T12:49:12Z
- dc.date.available
- 2024-06-13T12:49:12Z
- dc.date.issued
- 2020-05-05
- dc.description.abstract - en
- OBJECTIVES: The present study evaluates the extent of association between hepatitis C virus (HCV) infection and cardiovascular disease (CVD) risk and identifies factors mediating this relationship using Bayesian network (BN) analysis. DESIGN AND SETTING: A population-based cross-sectional survey in Canada. PARTICIPANTS: Adults from the Canadian Health Measures Survey (n=10 115) aged 30 to 74 years. PRIMARY AND SECONDARY OUTCOME MEASURES: The 10-year risk of CVD was determined using the Framingham Risk Score in HCV-positive and HCV-negative subjects. Using BN analysis, variables were modelled to calculate the probability of CVD risk in HCV infection. RESULTS: When the BN is compiled, and no variable has been instantiated, 73%, 17% and 11% of the subjects had low, moderate and high 10-year CVD risk, respectively. The conditional probability of high CVD risk increased to 13.9%±1.6% (p<2.2×10-16) when the HCV variable is instantiated to 'Present' state and decreased to 8.6%±0.2% when HCV was instantiated to 'Absent' (p<2.2×10-16). HCV cases had 1.6-fold higher prevalence of high-CVD risk compared with non-infected individuals (p=0.038). Analysis of the effect modification of the HCV-CVD relationship (using median Kullback-Leibler divergence; DKL ) showed diabetes as a major effect modifier on the joint probability distribution of HCV infection and CVD risk (DKL =0.27, IQR: 0.26 to 0.27), followed by hypertension (0.24, IQR: 0.23 to 0.25), age (0.21, IQR: 0.10 to 0.38) and injection drug use (0.19, IQR: 0.06 to 0.59). Conclusions: Exploring the relationship between HCV infection and CVD risk using BN modelling analysis revealed that the infection is associated with elevated CVD risk. A number of risk modifiers were identified to play a role in this relationship. Targeting these factors during the course of infection to reduce CVD risk should be studied further.
- dc.identifier.citation
- Badawi A, Di Giuseppe G, Gupta A, et al. Bayesian network modelling study to identify factors influencing the risk of cardiovascular disease in Canadian adults with hepatitis C virus infection. BMJ Open 2020;10:e035867. doi:10.1136/ bmjopen-2019-035867
- dc.identifier.doi
- 10.1136/bmjopen-2019-035867
- dc.identifier.uri
- https://open-science.canada.ca/handle/123456789/2601
- dc.language.iso
- en
- dc.publisher
- BMJ
- dc.rights - en
- Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
- dc.rights - fr
- Creative Commons Attribution-Pas d’Utilisation Commerciale 4.0 International (CC BY-NC 4.0)
- dc.rights.openaccesslevel - en
- Gold
- dc.rights.openaccesslevel - fr
- Or
- dc.rights.uri - en
- https://creativecommons.org/licenses/by-nc/4.0/
- dc.rights.uri - fr
- https://creativecommons.org/licenses/by-nc/4.0/deed.fr
- dc.subject - en
- Health
- dc.subject - fr
- Santé
- dc.subject.en - en
- Health
- dc.subject.fr - fr
- Santé
- dc.title - en
- Bayesian network modelling study to identify factors influencing the risk of cardiovascular disease in Canadian adults with hepatitis C virus infection
- dc.type - en
- Article
- dc.type - fr
- Article
- local.acceptedmanuscript.articlenum
- e035867
- local.article.journalissue
- 5
- local.article.journaltitle
- BMJ Open
- local.article.journalvolume
- 10
- local.peerreview - en
- Yes
- local.peerreview - fr
- Oui
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