It is well-established that patients with the highest proportion of visceral fat area are more likely to experience a heart attack or other cardiovascular event. While abdominal CT scans can provide a more granular look at body composition when routinely performed, ascertaining risk levels based on fat area is rarely done in clinical practice. Manually obtaining measurements can be time intensive and costly, yet a single axial CT slice of the abdomen can visualize the volume of subcutaneous and visceral fat area as well as skeletal muscle area needed to predict the risk of major cardiovascular (CV) events. Used in combination with artificial intelligence (AI), CT imaging has the potential to offer an improved way of predicting adverse CV according to emerging research.
The overlap of the COVID-19 pandemic with persistently rising rates of obesity, diabetes, cardiovascular disease, and other cardiometabolic health conditions has drastically exacerbated the virus death toll. The prevalence of chronic and infectious disease alongside large-scale public health failures have contributed to the adverse outcomes of the unprecedented health crisis, resulting in what The Lancet’s medical journal editor-in-chief, Richard Horton, refers to as a “syndemic.” Defined as the aggregation of two or more concurrent or sequential disease clusters, a syndemic attacks population health on multiple levels of vulnerability, making it extremely difficult to mitigate as evidenced by the current health landscape.