Description

About the Author

Dr. Arjun Baidya (MD(Medicine), DM (Endocrinology), FACE, SCE (Endocrine and Diabetes) (UK)) is a renowned Endocrinologist with over more than 25 years of clinical experience and more than 14 years of teaching experience. He is currently associated with Nil Ratan Sircar Medical college and Hospital (Kolkata) as an Associate Professor at Department of Endocrinology. Dr. Baidya has guide and co-guide for dissertation in DM, MD, MS and MSc Nursing course under The West Bengal University of Health Sciences, Kolkata since 2014. Apart of that he is adjudicator of dissertation in DM Endocrinology under The West Bengal University of Health Sciences, Kolkata. Dr. Baidya has a keen interest in research and had 18 Presentations in National and International conferences (ADA, IDF, AACE, EASD, ICE, ENDO SOCIETY, ESICON, RSSDI, ITS CON) and had 35 indexed publications in national and International journals. Dr. Baidya is also reviewer of JAFES, Diabetes & Metabolic Syndrome: Clinical Research & Reviews, Diabetic Medicine, Military Medical Research Journal, Journal of Diabetes and Metabolism, Biomedical and Pharmacy Journal, Journal of Endocrinology and Metabolism, Journal of Neurosciences in Rural Practice, Indian Journal of Case Reports and Journal of Pharmaceutical Research International.

About the Book

Having diabetes is now considered the equivalent of having two or three major risk factors for coronary atherosclerosis. The presence of diabetes in an individual increases the risk of any procedure and is associated with a proper prognosis compared with those individuals who do not have diabetes. Therefore, today’s clinician needs a full understanding of this disease and its effect on management decisions.

“DIABETES AND CARDIOVASCULAR DISEASE’ deals with the pathophysiology and clinical epidemiology of diabetes and its relationship with other diseases such as heart failure and hypertension The main aims of this book to provide the clinician with the information needed for an intelligent clinical choice based on valid scientific data