Smartphone App Predicts Cardiovascular Damage from Vaping
In this study, recently published in the Journal of the American Heart Association (JAHA), Rashid Alavi, PhD, James G. Boswell Postdoctoral Fellow at the California Institute of Technology (Caltech and HMRI), led a team of researchers to predict the long-term risk of cardiovascular damage from e-cigarettes (ECs), particularly those containing nicotine using cardiovascular intrinsic frequency. The novel technique of measuring intrinsic frequency uses the shape of a blood pressure waveform (without having to calibrate the blood pressure) plus machine learning/AI to detect abnormalities in cardiovascular (heart and blood vessels) function that may not be picked up by current routine measures of heart function (e.g., blood pressure alone, or heart function measured by echocardiography). The intrinsic frequency method allowed us to pick up abnormalities in blood-vessel heart function due to vaping (e-cigarettes) as well as traditional cigarettes that standard measures might have otherwise missed. This pioneering approach, validated on preclinical models, has significant potential for human applications, offering a simple yet powerful, non-invasive tool to detect cardiovascular risks early on. The smartphone captures images of the neck skin. The method has the potential for noninvasive human use by simply shining a cell phone flashlight on the surface of the skin that overlies a blood vessel along with a special app.