Predictive ability of perioperative atrial fibrillation risk indices in cardiac surgery patients: a retrospective cohort study.

PURPOSE

The Multicenter Study of Perioperative Ischemia (McSPI) AFRisk index predicts postoperative atrial fibrillation (POAF) after cardiac surgery, but requires pre-, intra-, and postoperative data. Other more abbreviated risk indices exist, but there is no consensus on which risk index is optimal. We compared the discriminatory capacity of the McSPI AFRisk index with three indices containing only preoperative data (the CHADSVasc score, POAF score, and Kolek clinical risk prediction model), hypothesizing that the McSPI AFRisk index would have superior predictive capacity.

METHODS

We retrospectively evaluated 783 patients undergoing cardiac surgery using cardiopulmonary bypass. The predictive capacity of each index was assessed by comparing receiver-operating characteristic (ROC) curves, scaled Brier scores, net reclassification indices, and the integrated discrimination indices.

RESULTS

The incidence of POAF was 32.6%. The area under the curve (AUC) of the ROC curve were 0.77, 0.58, 0.66, and 0.66 for the McSPI AFRisk index, CHADSVasc score, POAF score, and Kolek clinical risk prediction model, respectively. The McSPI AFRIsk index had the highest AUC (P < 0.0001). The scaled Brier scores for the McSPI AFRisk index, CHADSVasc score, POAF score, and Kolek clinical risk prediction model were 0.23, 0.02, 0.08, and 0.07, respectively. Both net reclassification indices and integrated discrimination indices showed that the McSPI AFRisk index more appropriately identified patients at high risk of POAF.

CONCLUSIONS

The McSPI AFRisk index showed superior ability to predict POAF after cardiac surgery compared with three other indices. When clinicians and investigators wish to measure the risk of POAF after cardiac surgery, they should consider using the McSPI AFRisk index.