Forewarned Is Forearmed: Machine Learning Algorithms for the Prediction of Catheter-Induced Coronary and Aortic Injuries.

Catheter-induced dissections (CID) of coronary arteries and/or the aorta are among the most dangerous complications of percutaneous coronary procedures, yet the data on their risk factors are anecdotal. Logistic regression and five more advanced machine learning techniques were applied to determine the most significant predictors of dissection. Model performance comparison and feature importance ranking were evaluated.

Catheter-induced coronary artery and aortic dissections. A study of mechanisms, risk factors and propagation causes.

Background: Only the incidence, management, and prognosis of catheter-induced coronary artery and aortic dissections have been systematically studied until now. We sought to evaluate their mechanisms, risk factors, and propagation causes.

Methods: Electronic databases containing 76,104 procedures and complication registries from 2000-2020 were searched and relevant cineangiographic studies adjudicated.

Delayed presentation of left main coronary artery dissection due to catheter ablation in a patient with bicuspid aortic valve. Coincidence or manifestation of inherent vulnerability?

Left main coronary artery (LMCA) injury is an uncommon complication of catheter ablation. Due to the large myocardial area at risk, its presentation is usually acute with a dramatic course and life-threatening sequelae. Increased susceptibility to spontaneous coronary artery dissection has recently been implied in patients with bicuspid aortic valve (BAV).

Analysis of reported cases of left main coronary artery injury during catheter ablation: In search of a pattern.

Introduction: Left main coronary artery (LMCA) injury is a rare but potentially fatal complication of catheter ablation. Due to LMCA large perfusion area, its occlusion is usually a dramatic event.

Methods And Results: Reports of LMCA injury complicating catheter ablations from 1987 to 2018 were searched in electronic databases.