Edouard Fu

Dr Edouard Fu is Assistant professor at LUMC, editor at NDT, and in training to become MD. Furthermore, he is an affiliated researcher at the Department of Medical Epidemiology and Biostatistics, Karolinska Institute. Previously, he completed his postdoc at Harvard and was editorial fellow at the leading kidney journal JASN (2021-2023). He received his PhD in 2021 cum laude, given to top dissertations in the field, for the thesis “Optimal cardiovascular treatment strategies in kidney disease - causal inference from observational data”. He has been awarded several prestigious grants to pursue his research, including a personal Rubicon and VENI grant from the Dutch Research Council and a Junior Kolff Grant from the Dutch Kidney Foundation (total €874.000). His work has informed 8 international clinical practice guidelines and position statements. 

His research focuses on assessing the effectiveness and safety of medications and treatments in patients with kidney and cardiovascular disease by applying state-of-the-art causal inference methods to routinely collected big data. He has investigated the cardiorenal effects of ACEi/ARB, MRA, DOACs, SGLT-2i and GLP1-RA, as well as the effectiveness and timing of dialysis initiation. He pioneered the application of target trial emulation in the field of nephrology to answer clinically pressing questions with observational data (e.g. BMJ 2021, JASN 2020), which has improved the validity of causal observational studies. He is currently involved in several large ongoing pharmacoepidemiologic analyses and has published over 140 peer-reviewed articles and conference proceedings in general medical journals (JAMA, BMJ, Annals of Internal Medicine) and specialty journals in the field of nephrology (JASN, Kidney Int, Nature Reviews Nephrology) and cardiology (European Heart Journal, European Journal of Heart Failure). In addition, he has written several educational articles to make advanced methods more accessible for clinicians (e.g. JASN 2023). 

His work has been awarded with various prizes. He was chosen as one of the 30 talents under 30 of The Netherlands by Elsevier (2022) and received the prestigious Stanley Shaldon Award from the European Renal Association for his scientific contributions to nephrology (2023). Furthermore, he received the prize for best Dutch PhD thesis in nephrology, prize for best paper from the Dutch Epidemiology Society (2022), and several prizes on international conferences, including best abstract of the congress (2021) at the annual ERA congress.

Cardiorenal/pharmacoepidemiology, causal inference, target trial emulation, routinely collected healthcare data, machine learning, personalized medicine