Top in cardiology: Time-restricted eating; atrial fibrillation algorithm

A recent study found that time-restricted eating was associated with a reduced risk for CVD among older women with overweight who received cardiotoxic breast cancer treatment.

The time-restricted eating plan was 8 weeks long, and the women who followed it saw a15% relative CVD risk reduction, according to researchers. It was the top story in cardiology last week.

Another top story was about a study that found an implantable cardioverter defibrillator (ICD) algorithm that detected severe sleep apnea may also detect atrial fibrillation burden. Researchers reported that patients with heart failure and ICD-diagnosed severe sleep apnea were more likely to experience an atrial fibrillation episode.

Read these and more top stories in cardiology below:

Time-restricted eating may reduce CV risk for older breast cancer survivors

Older women with overweight who received cardiotoxic treatment for breast cancer saw a 15% relative CVD risk reduction after following an 8-week time-restricted eating plan, according to research published in JACC: CardioOncology. Read more.

ICD sleep apnea algorithm may also detect AF burden

Patients with heart failure who received an implantable cardioverter defibrillator that detected severe sleep apnea may be two- to threefold more likely to experience an atrial fibrillation episode, according to a new analysis of DASAP-HF data. Read more.

Early rhythm control beneficial vs. rate control in AF, but effect may decrease with age

In patients younger than 75 years with atrial fibrillation and concomitant cardiovascular conditions, an early rhythm control strategy was associated with better cardiovascular outcomes compared with a rate control strategy, researchers reported. Read more.

Prediabetes in young adulthood drives risk for MI-related hospitalization

Young adults with prediabetes are nearly twice as likely to be hospitalized for myocardial infarction compared with young adults without impaired glucose tolerance, suggesting more screening and awareness is needed, researchers reported. Read more.

Deep-learning AI algorithm accurately predicts severe aortic stenosis

A machine learning algorithm detected severe aortic stenosis using audio files from a set of patients with accuracy similar to board-certified cardiologists, according to findings from a proof-of-concept study. Read more.