Using preoperative four-dimensional automated left atrial quantification echocardiography to predict postoperative...

Postoperative atrial fibrillation (POAF) is a common complication after cardiac surgery, and is associated with poor outcomes. Detecting left atrial (LA) subtle structural and functional abnormalities before surgery may help to identify patients at increased risk of POAF. This study aimed to investigate whether LA volume and strain parameters measured by four-dimensional automated LA quantification (4D auto LAQ) echocardiography are independent predictors of POAF in patients undergoing cardiac surgery.

Consecutive patients undergoing cardiac surgery were prospectively enrolled in the study. All the patients underwent conventional and 4D auto LAQ echocardiography before surgery. The occurrence of POAF up to discharge was monitored. Multivariate logistic regression was used to identify the clinical and echocardiographic risk factors of POAF.

In total, 128 patients were enrolled in the study. POAF occurred in 52 patients (40.6%), who formed the POAF group; the remaining 76 patients formed the no-POAF group. There were statistically significant differences between the two groups in terms of age, pro-brain natriuretic peptide (pro-BNP) levels, red blood cell (RBC) transfusion during surgery, surgical approach, and the type of surgery (all P<0.05). The POAF group had a significantly higher left ventricle end-diastolic diameter (LVEDD; P=0.043), E/e' ratio (P<0.001), and LA size (all P<0.001), but had a lower LA ejection fraction (LAEF; P<0.001), and LA strains (all P<0.05). In the multivariate analysis, an age ≥52 years old [odds ratio (OR) =11.628; P<0.001], RBC transfusion during surgery (OR =8.084; P=0.005), valve surgery (OR =4.870; P=0.033), LA pre-systolic volume (LAVpreA) ≥65 mL (OR =3.779; P=0.034), |LA contraction longitudinal strain| (|LASct|) <10% (OR =6.290; P=0.017), and |LA contraction circumferential strain| (|LASct-c|) <8% (OR =6.915; P=0.003) were identified as six independent predictive factors of POAF. The area under the curve (AUC) value for the POAF prediction model that included the above six variables was 0.924 (P<0.001), which was significantly higher than the AUC values of the three commonly used models that only include clinical parameters [i.e., the POAF score, the CHA2DS2-VASc score, and the atrial fibrillation (AF) risk index], which had AUC values of 0.695, 0.568, and 0.508, respectively.

4D auto LAQ echocardiography is a novel, non-invasive tool for the analysis of LA structure and function in the preoperative setting of cardio surgery. The 4D auto LAQ parameters (including LAVpreA, LASct, and LASct-c), age, RBC transfusion, and valve surgery are independent predictors of the occurrence of POAF. The predictive model that includes the 4D auto LAQ parameters is more conducive to the risk stratification of POAF after cardiac surgery than traditional clinical models. However, our study had a small sample size, and lacked a validation group; thus, further studies need to be conducted to verify the efficacy and reliability of our predictive model in the future.