Treating heart failure is one of the greatest unmet needs in cardiovascular medicine today. Overall survival is poor and 50% of patients die within 5 years of their initial diagnosis. Heart failure is a heterogeneous syndrome and a one-size-fits-all approach is ineffective. Therefore, in my thesis I used biomarkers to 1. Show that patients with heart failure and a preserved ejection fraction are subject to more inflammation, which can be a key treatment target and 2. Identified clinical relevant subgroups with differences in response to treatment using machine learning based approaches.
|Qualification||Doctor of Philosophy|
|Place of Publication||[Groningen]|
|Publication status||Published - 2018|