Temporal trends and predictors of surgical ablation for atrial fibrillation across a multistate healthcare system.

Document Type


Publication Date


Publication Title

Heart Rhythm O2


oregon; portland; cards; cards publication; washington; spokane; pshmc; swedish; swedish heart; everett; prmc


Background: Multiple class I and class IIa recommendations exist related to surgical ablation (SA) of atrial fibrillation (AF) in patients undergoing cardiac surgery.

Objective: Examine temporal trends and predictors of SA for AF in a large US healthcare system.

Methods: We retrospectively analyzed data from the Society for Thoracic Surgery (STS) Adult Cardiac Surgery Database for 21 hospitals in the Providence St. Joseph Health system. All patients with preoperative AF who underwent isolated coronary artery bypass graft (CABG) surgery, isolated aortic valve replacement (AVR), AVR with CABG surgery (AVR+CABG), isolated mitral valve repair or replacement (MVRr), and MVRr with CABG surgery (MVRr+CABG) from July 1, 2014, to March 31, 2020 were included. Temporal trends in SA were evaluated using the Cochran-Armitage trends test. A multilevel logistic regression model was used to examine patient-, hospital-, and surgeon-level predictors of SA.

Results: Among 3124 patients with preoperative AF, 910 (29.1%) underwent SA. This was performed most often in those undergoing isolated MVRr (n = 324, 44.8%) or MVRr+CABG (n = 75, 35.2%). Rates of SA increased over time and were highly variable between hospitals. Years since graduation from medical school for the primary operator was one of the few predictors of SA: odds ratio (95% confidence interval) = 0.71 (0.56-0.90) for every 10-year increase. Annual surgical (both hospital and operator) and AF catheter ablation volumes were not predictive of SA.

Conclusion: Wide variability in rates of SA for AF exist, underscoring the need for greater preoperative collaboration between cardiologists, electrophysiologists, and cardiac surgeons.

Clinical Institute

Cardiovascular (Heart)




Center for Cardiovascular Analytics, Research + Data Science (CARDS)