A model of increasing predictability of atrial fibrillation related stroke in patients with non-valvular atrial fibrillation

Abstract

Objective: Our aim for this study was to develop a model using clinical, laboratory and echocardiographic factors, in addition to CHA2DS2-VASC score, to increase predictability of AF related stroke in patients with non-valvular atrial fibrillation (NVAF).Methods: We retrospectively analyzed the medical history, clinical characteristics, laboratory and echocardiographic data of 373 patients with NVAF.Results: In multiple logistic regression, CHA2DAS2 VASC score (OR 1.22 (95%CI 1.04-1.43), P=0.016), anion gap (OR 1.19 (95%CI 1.08-1.30), P < 0.001), e-peak deceleration time （EDT） (OR 1.01 (95%CI 1.00-1.01), P=0.001) and the left atrial appendage emptying rate （LAAEV） (OR 0.99 (95%CI 0.97-0.99), P=0.013) were risk factors for predicting stroke in NVAF patients. For patients with low CHA2DAS2 VASC score, anion gap (OR 1.35 (95%CI 1.03-1.77), P=0.028) and EDT (OR 1.01 (95%CI 1.00-1.02), P=0.043) were associated with stroke.Receiver operating characteristic (ROC) curve showed that area under curve (AUC) is 11% higher in the model including anion gap, EDT， LAAEV and CHA2DS2-VASc score, compared to only using CHA2DS2-VASc score as predictor (0.70 (95%CI 0.64-0.75) vs 0.59 (95%CI 0.54-0.65)).Conclusions: Our study showed that incorporating anion gap, EDT and LAAEV into CHA2DS2-VASC score increases the ability to predict atrial fibrillation related stroke.