CHADS Score Predicts Postoperative Atrial Fibrillation in Patients Undergoing Elective Pulmonary Lobectomy.

BACKGROUND

Postoperative atrial fibrillation (PAF) affects 12% to 17% of patients undergoing lobectomy and is associated with increased morbidity. CHADS (congestive heart failure history, hypertension history, age ≥75 years, diabetes mellitus history, and stroke or transient ischemic attack symptoms previously) is used to predict stroke risk in patients with existing AF. It also has been shown also to predict new-onset PAF. Our objective was to determine whether CHADS can predict PAF in patients undergoing lobectomy.

METHODS

A prospective thoracic surgery clinical database was reviewed to identify adult patients, without prior AF, who underwent elective lobectomy between January 1, 2005, and June 30, 2014. Nonelective and combined operations were excluded. Two groups (PAF and no PAF) were analyzed.

RESULTS

PAF developed in 113 of 933 patients with overall incidence of 12% for the entire group. Age (≥75 years) and coronary artery disease were the only significant preoperative characteristics between the two groups. Intensive care unit readmission, new neurologic events, length of stay, 30-day survival, and hospital mortality were significantly higher in the PAF group as were mean CHADS scores (1.4 and 1.1 respectively, p = 0.0014). Incidence of PAF ranged from 7.9% in low-risk groups to 11% in moderate-risk and 17.7% in high-risk groups, which was also significant, p < 0.0002. Similar findings were noted for CHADS-VASc (age in years, sex, history of congestive heart failure, history of hypertension, history of stroke/transient ischemic symptoms/thromboembolic events, history of vascular disease, history of diabetes mellitus).

CONCLUSIONS

Although multiple risk factors for PAF have been described, no easily applicable clinical model exists. Observed rate of PAF was significantly lower then the previously described 12% when CHADS was 0. CHADS can predict PAF in patients undergoing elective lobectomy and can identify patients to selectively institute prophylactic measures in patients at the greatest risk, such as patients with score of 2 or greater. Further validation of this model is warranted in a larger group.