Philip Binkley MD
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congestive heart failure; automatic mechanisms and vascular responses to CHF
congestive heart failure; nuclear medicine; vasodilator drugs
Philip Binkley, MD, FACC, MPH, is a cardiologist who specializes in internal medicine and cardiovascular disease at The Ohio State University Wexner Medical Center. Dr. Binkley was named one of America’s Best Doctors in 2009.
A professor of cardiovascular medicine and director of cardiovascular research for the Division of Cardiovascular Medicine at Ohio State’s Medical Center, Dr. Binkley earned his medical degree and completed his internship, residency and fellowship in cardiology at Ohio State. He also earned a master’s in public health from Ohio State.
Dr. Binkley’s clinical interests include chronic heart failure, automatic mechanisms and vascular responses to congestive heart failure. Widely recognized for his research expertise, Dr. Binkley currently serves on the National Research Committee of the American College of Cardiology and has served as Ohio State’s principal investigator on a number of studies examining the effects of various prescription drugs on the human heart. His research focuses on congestive heart failure, nuclear medicine and vasodilator drugs. Dr. Binkley is frequently published, and regularly speaks on the topic of managing heart failure and hypertension.
Dr. Binkley’s career has been devoted to both the clinical management and the investigation of congestive heart failure and cardiomyopathies. He has a long record of investigative efforts including those exploring the vascular responses to ventricular systolic failure and the autonomic consequences of congestive heart failure and the mechanisms by which they contribute to the progression of this disease process. These efforts have been supported by the National American Heart Association, the NIH and a variety of industry sponsors. More recently his research has focused on the clinical and genetic predictors of recovery of LV systolic function including the imaging biomarkers that have significant predictive value.