Here are the top stories covered by DocWire News this week in the Cardiology section. In this week’s edition of the round-up, see how weekly alcohol consumption is linked to an increased risk of cardiovascular disease, why those diagnosed with coronary heart disease may experience cognitive decline as they age, how an artificial intelligence classifier can detect a specific cardiovascular disease using a wearable wrist sensor, and what researchers have recently used on healthy donor heart tissue to study the genetic components involved in heart failure.
The quantity of alcohol you consume on a weekly basis is directly correlated to risk of cardiovascular diseases (CVD), a new study shows. Previous studies regarding whether consuming less alcohol is associated with a lower risk of CVD have yielded varying results. With this new research published in Current Developments in Nutrition, however, it appears that the consuming minimal alcohol is associated with a much lower risk of CVD. To conduct this study, researchers obtained a sample of 83,732 Chinese adults aged 18 to 96 years. These individuals were members of the Kailuan Study conducted from 2006-2007 and had no history of CVD or cancer. The participants were grouped into six categories based on self-reported alcohol consumption in units of grams of ethanol per week. Those who consumed over 750 grams of ethanol a week were found to have a hazard ratio of 1.13 for chronic disease and 1.51 for cancer, which was found to be statistically significant.
Those who are diagnosed with coronary heart disease (CHD) may be at an increased risk for cognitive decline in later years, according to research recently published in the Journal of the American College of Cardiology. The researchers found that patients’ scores on cognitive tests decreased faster after they had been diagnosed with CHD than they did prior to diagnosis, indicating that the disease could impair mental function. “This study adds to the increasing body of literature that showcases how the heart and brain work together,” said Dr. Neelum T. Aggarwal, director of research for the Rush Heart Center for Women and a cognitive neurologist at its Cardiology Cognitive Clinic. “We are now seeing more issues related to cognitive function from heart disease as more people are living longer, and also undergoing more heart procedures, and placed on medications.”
Researchers have recently developed an artificial intelligence (AI) classifier that can detect a specific cardiovascular disease using a wearable wrist biosensor. The condition, hypertrophic cardiomyopathy, can cause serious complications and is commonly unrecognized in the clinical setting. By proposing a diagnostic approach using a machine learning and a wearable sensor, these researchers have potentially developed a noninvasive and widely available tool to identify the disease. Their work was published in npj Digital Medicine on June 24. The researchers concluded that the use of machine learning and a wearable biosensor was successful in distinguishing between patients with oHCM and their healthy counterparts. With many wearable devices now being equipped with PPG sensors, this AI approach presents as a potential tool for detecting unrecognized oHCM.
Researchers from the Stanford University School of Medicine have recently utilized healthy, but unusable, donor heart tissue to study the genetic components involved in heart failure. This has allowed these scientists and their collaborators to map out genetic activity and connectivity that occurs when the heart shuts down and identify a gene that is potentially at the center of this process. This work was covered today in Nature Communications. “This study has a truly unique angle, which is that we had precious, healthy human tissue and we used it to tell us something new about how a disease manifests,” explained Victoria Parikh, MD, clinical instructor of cardiovascular medicine. “And now someday we might even be able to translate that into a treatment.”