Contributions of Higher Resolution Observational Evidence from Electronic Health Records to Understand the Causal Relevance of Blood Lipids to Heart Failure and Atrial Fibrillation

Abstract

Heart failure (HF) and atrial fibrillation (AF) are increasingly prevalent due to aging populations, and both diseases have a big economic and healthcare burden globally. To date, there is no primary prevention specific to healthy populations. Blood lipids (i.e., LDL-C, HDL-C, and TG), which are involved with pathophysiological mechanisms of HF and AF, might play a role in the origin of both diseases. Therefore, the potential causal relevance of blood lipids to HF and AF should be investigated. Linkage electronic health records (EHRs) provide an opportunity to investigate the association between blood lipids and the incidence of HF and AF, as these records contain large sample sizes (e.g., n>1 million) with a wide range of diseases and biomarkers routinely recorded in clinical practice. Challenges include structuring the data into a research-ready format, accurately defining outcomes, and handling missing data. The data used in this thesis is from the CALIBER platform, which links routinely collected EHRs from general practices, hospital admission, and the death registries of 3 million patients in England from 1997 to 2016. In this thesis, I (1) constructed cohorts from EHRs and ensured the validity of the cohorts and (2) examined the association between blood lipids and the incidence of HF and AF using the EHR population-based cohort design. The observed findings were then compared to the results from meta-regression of trials on lipid-lowering drugs and those from a Mendelian randomisation approach, and then I (3) assessed the predictive value of adding blood lipids in the risk prediction of incident HF and AF. Additionally, I developed the model for the prediction of 10-year risk of newly occurring HF and AF. Taken together, these findings have a valuable implementation. For future research, my findings can be a basis for developing a new drug to fight against HF and AF. For clinical application, my findings can inform clinicians whether blood lipids should be targeted and what levels are needed to protect people from HF and AF. Besides, my results can inform clinicians to monitor their patients for the developing of HF and AF