Research
Title: Advancing CVD risk prediction models in younger individuals
Abstract: Cardiovascular disease is still one of the largest killers in the world. Over the past 20 years, risk scores such as the Framingham score have become a helpful tool to identify individuals who are at risk of a future cardiovascular event. By using a handful of risk factors, risk scores help to inform clinical decisions. However, due to the use of set clinical thresholds to determine who is high risk or not, these scores often fail to identify young individuals as high risk, regardless of whether their risk factors, such as cholesterol or blood pressure, are high. Therefore, identifying high risk individuals and intervening earlier before atherosclerosis develops is key. This PhD aims to advance risk prediction in younger individuals by developing a pre-stratification tool to inform these decisions, by utilising the wealth of data available, in particular GP records, genetic data and omics data. In addition, health economics will be investigated and a clinical tool will be built.
Publications
Browne, A., Fisher, S.A., Masconi, K., Smith, G., Doree, C., Chung, R., Rahimzadeh, M., Shah, A., Rodriguez, S.A., Bolton, T. and Kaptoge, S., 2019. Donor Deferral Due to Low Hemoglobin–An Updated Systematic Review. Transfusion Medicine Reviews.
Chung, R.K., Wood, A.M. and Sweeting, M.J., 2019. Biases incurred from nonrandom repeat testing of haemoglobin levels in blood donors: Selective testing and its implications. Biometrical Journal, 61(2), pp.454-466.
