Coronary artery disease and major depression may be genetically linked via inflammatory pathways to an increased risk for cardiomyopathy, a degenerative heart muscle disease, researchers at Vanderbilt University Medical Center and Massachusetts General Hospital have found.
Their report, published April 5 in the journal Nature Mental Health, suggests that drugs prescribed for coronary artery disease and depression, when used in combination, potentially may reduce inflammation and prevent the development of cardiomyopathy.
"This work suggests that chronic low-level inflammation may be a significant contributor to both depression and cardiovascular disease," said the paper's corresponding author, Lea Davis, Ph.D., associate professor of Medicine in the Division of Genetic Medicine and Vanderbilt Genetics Institute.
The connection between depression and other serious health conditions is well known. As many as 44% of patients with coronary artery disease (CAD), the most common form of cardiovascular disease, also have a diagnosis of major depression. Yet the biological relationship between the two conditions remains poorly understood.
App detects heart failure vibes via a smartphone's existing sensors
By Ben Coxworth
April 09, 2024
Detecting the first stages of heart failure could soon be as simple as placing a smartphone on a patient's chest. That's the conclusion of an ongoing study, which is aimed at developing an app for diagnosing the potentially lethal condition as early as possible.
Heart failure may initially present in the form of fatigue upon exertion, or shortness of breath. These symptoms may of course have other, more innocuous causes. And unfortunately, checking to see if they are caused by heart failure currently requires ultrasound heart scans, blood tests or other special procedures.
Scientists from Finland's University of Turku set out to develop a much simpler diagnostic method, that can be quickly performed in a doctor's office without any special equipment. The result is a machine-learning-based app that uses a smartphone's existing accelerometer and gyroscope to measure tiny telltale cardiac vibrations in the patient's chest.
AI trained on simple heart rate data can predict an episode of the most common heart rhythm disorder, atrial fibrillation, 30 minutes in advance, new research has shown. With plans for it to be incorporated into a smartphone so it can analyze data from a smartwatch, the model would act as an early warning system.
The most common heart rhythm disorder, atrial fibrillation (AF), significantly increases emergency department presentations and the risk of other diseases like stroke and dementia. The condition occurs when the heart’s upper chambers (atria) beat chaotically, out of sync with the lower chambers (ventricles), producing an irregular, often very rapid, heart rhythm.
Reverting a patient from AF back to regular sinus rhythm can require intensive interventions such as cardioversion, delivering a low-energy shock to ‘reset’ the heart’s conduction system. (Yes, it’s the same device used in medical programs, accompanied by a cry of “CLEAR!”) So, being able to detect an episode of AF before it happens would enable early interventions that might improve patient outcomes.
