Scientists, at present, are able to detect atherosclerosis and subclinical cardiac disease in high risk patients. Novel technologies are now capable of identifying valvular abnormalities, myocardial inflammation, vascular stenosis, heart failure, and increased tendencies towards arrhythmias in its early stages. The tests include new cardiac MRI machines, CT scanning methods, novel ultrasonographic markers, and advanced ECG analysis algorithms. Many diagnostic commercialized technologies have been reviewed on Medgadget. Nevertheless, these tests are still unavailable in all medical centers and are unknown to most non-cardiologists.
Heart diseases are a leading cause of morbidity and mortality worldwide. According to the American Heart Association (2017 Update) approximately 92.1 million adults living in the United states have been diagnosed with at least one type of cardiovascular disease. It has also been estimated that by 2030, 43.9% of this population will develop some form of cardiovascular disease. The statistics are especially staggering in high-risk patient groups. Cardiac complications are not limited to patients with conventional cardiovascular risk factors, but also include patients subjected to a high inflammatory burden. Notably, the general population is commonly affected by pro-inflammatory states. Specific patient groups, ie patients suffering from arthritis, autoimmune diseases or those who are continuously treated with certain non-steroidal anti-inflammatory drugs (NSAIDs) are at an increased risk for heart diseases. Of note, more than 50 million Americans suffer from some kind of arthritis. Medical therapies, including over-the-counter prescribed medications, may also affect the cardiovascular system.
“The Heart in Rheumatic, Autoimmune and Inflammatory Diseases” (edited by Udi Nussinovitch MD PhD, Rambam Health Care Campus, Haifa, Israel, and a former author at Medgadget) covers these topics. The book is clinically oriented and focuses on emerging diagnostic technologies in specific high risk subsets of patients.