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Thesis

Cardiovascular risk scoring for the prevention of cardiovascular disease in low-resource settings

Abstract:

The aim of this thesis was to examine the use of total cardiovascular risk scoring for the prevention of cardiovascular disease (CVD) in low-resource settings. While risk scoring is popular in high-income countries, the overarching hypothesis was that it was sub-optimal for the prevention of CVD in low-resource settings. To achieve its aim, this thesis first synthesised evidence through a systematic review of systematic reviews on the impact of total CVD risk scoring on important patient outcomes. Second, it developed an R package to calculate World Health Organisation/International Society of Hypertension (WHO/ISH) CVD risk scores for all epidemiological subregions of the world. Third, using mixed methods and intensive fieldwork, it evaluated the practical implementation of WHO/ISH CVD risk scores in Médecins Sans Frontières clinics for Syrian refugees in Jordan. Lastly, it explored the potential to simplify CVD risk scores by replacing cholesterol information with body mass index using a contemporary CVD risk cohort from New Zealand. Overall, the findings showed that CVD risk scoring is sub-optimal for low-resource settings due to a lack of evidence of effectiveness, its difficulty to implement and test, and its potential to be simplified. Focus should be shifted towards conducting high quality randomised trials in low-resource settings, using simplified risk scores that can be completed in a single consultation, and further implementation studies in primary health care. With this in mind, cardiovascular risk scoring as a pivotal intervention for the prevention of CVD in low-resource settings should be judiciously compared to other alternatives, and if implemented, closely monitored for its impact on health outcomes.

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Institution:
University of Oxford
Division:
MSD
Department:
Primary Care Health Sciences
Oxford college:
Christ Church
Role:
Author

Contributors

Role:
Supervisor
Role:
Supervisor
Role:
Supervisor


DOI:
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford


Language:
English
UUID:
uuid:839de6e8-6cf6-4482-a352-201f4a595d56
Deposit date:
2018-06-21
ARK identifier:

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