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  • Pauline Lavigne

CKD and Cardio-Kidney Trials Seeing the Forest for the Trees

Sunday, December 6th 6:00 – 8:30 pm

Across the broad spectrum of cardiovascular (CV) diseases, chronic kidney disease (CKD) is an impressive and consistent adverse amplifier. By whatever measure: a cardiac catheterization lab registry, heart failure admissions, stroke, acute coronary syndrome, or arrhythmias, those with lower eGFR are more likely to die or have recurrent events, even when adjusting for other known confounders. Conversely, renal patients are more likely to die from CV disorders than to survive to need dialysis. Despite this strong intersection for adverse outcomes, those with CKD are often excluded from major CV outcome trials. This is an obvious deficit (the elephant in the room), which is increasingly being realized and addressed.

This session will be co-chaired by Prof. Carolyn Lam from the Department of Cardiology at the National Heart Centre Singapore (NHCS), and Dr. Marc Pfeffer from Brigham and Women’s Hospital (BWH) and the Harvard Medical School in Boston, MA, USA. It will provide a multi-stakeholder look at past issues, current status, and future directions for cardio-kidney trials, with views from nephrologists (Sankar Navaneethan, Houston, USA), cardiologists (Marc Pfeffer, Boston, USA), diabetologists (Peter Rossing, Copenhagen, DEN), statisticians (Stuart Pocock, London, GBR), industry (Jyothis George, Novonordisk, DEN, Richard Nkulikiyinka, Bayer, GER, and Jerome Rossert, AstraZeneca, SWE), regulatory (Aliza Thompson, FDA, USA, and Peter Mol, EMA, NED), patients (Cynthia Chauhan, Wichita, USA, and Patrick Gee, Chesterfield, USA), and payers. The moderated multi-stakeholder expert panel debate will focus on the approvability, reimbursement, and future implementation into clinical practice of new treatments for cardio-kidney disorders.

Making CV Precision Medicine Become a Reality

Thursday, December 3rd: 7:30 – 9:30 pm Advances in disease stratification tools, such as molecular and imaging technologies, will help to identify more specific patient populations. This will help to


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