Machine learning method for predicting pacemaker implantation following transcatheter aortic valve replacement.

Background: An accurate assessment of permanent pacemaker implantation (PPI) risk following transcatheter aortic valve replacement (TAVR) is important for clinical decision making. The aims of this study were to investigate the significance and utility of pre- and post-TAVR ECG data and compare machine learning approaches with traditional logistic regression in predicting pacemaker risk following TAVR.

Methods: Five hundred fifity seven patients in sinus rhythm undergoing TAVR for severe aortic stenosis (AS) were included in the analysis.

Heart rate-corrected QT interval in men increases during winter months.

Background: Sudden cardiac death increases during winter months in both men and women. The heart rate-corrected QT (QTc) interval exhibits circadian variation. However, little is known about QTc interval variation with month of year.

Mortality as an endpoint in atrial fibrillation.

The aim of this study was to evaluate the use of mortality as an appropriate endpoint in studies of atrial fibrillation. Almost none of the atrial fibrillation trials has shown a significant difference in mortality among the various treatment arms because the studies are small, and many patient-years are required to show significant differences. Differences can be found when mortality is used as part of a combined endpoint and in meta-analyses of atrial fibrillation trials.