Does radiofrequency ablation procedural data improve the accuracy of identifying atrial fibrillation recurrence?

Radiofrequency ablation (RFA) using the CARTO 3D mapping system is a common approach for pulmonary vein isolation to treat atrial fibrillation (AF). Linkage between CARTO procedural data and patients' electronical health records (EHR) provides an opportunity to identify the ablation-related parameters that would predict AF recurrence. The objective of this study is to assess the incremental accuracy of RFA procedural data to predict post-ablation AF recurrence using machine learning model.

Predictive utility of the impedance drop on AF recurrence using digital intraprocedural data linked to electronic health record data.

Background: Local impedance drop in cardiac tissue during catheter ablation may be a valuable measure to guide atrial fibrillation (AF) ablation procedures for greater effectiveness.

Objective: The study sought to assess whether local impedance drop during catheter ablation to treat AF predicts 1-year AF recurrence and what threshold of impedance drop is most predictive.

Methods: We identified patients with AF undergoing catheter ablation in the Mercy healthcare system.

Assessment of skeletal age at the wrist in children with a new ultrasound device.

Background: Determination of skeletal development in children is important. The most common method of evaluation uses the standards of Greulich and Pyle (G and P) to assess the left hand radiograph. Numerous assessments may be made during follow-up.