年龄 缺血性卒中史 非阵发性心房颤动以及B型脑钠肽评分对非瓣膜性房颤卒中的预测价值OA北大核心CSTPCD

Objective The study aims to construct a new,easy-to-use model for predicting ischemic stroke risk in patients with nonvalvular atrial fibrillation.Method In this retrospective cohort study,we collected data from 429 patients with atrial fibrillation treated in First Hospital of Jilin University between January 2018 and December 2018.In this study,the subjects were followed up for 4 years by telephone,wechat,outpatient and other means,and ischemic stroke was taken as the endpoint event for observation.The data set is randomly divided 1∶1 into a training set and a validation set.In the training set,univariate and multivariate Logistic regression analysis was used to construct the risk prediction model.The model was visualized through a nomogram,and the value of the model for clinical prediction was evaluated by drawing subject working characteristic curves and calibration curves.Finally,the model is validated internally in the validation set and the whole data set.Result Of 429 patients with nonvalvular atrial fibrillation,91 had ischemic stroke(21.2％).Logistic regression analysis showed that age,history of ischemic stroke,non-paroxysmal atrial fibrillation and BNP were independent risk factors for ischemic stroke in patients with nonvalvular atrial fibrillation.The ABSNp(A:age,B:BNP,S:history of ischemic stroke,Np:nonparoxysmal atrial fibrillation)model constructed based on this result showed good differentiation and accuracy.In the training set,validation set and overall data set,the area under the receiver operating characteristic curve was 0.857(95％ CI 0.795-0.918),0.763(95％ CI 0.692-0.833)and 0.810(95％ CI 0.763-0.857),respectively.In addition,the clinical decision curve shows that ABSNp model has high clinical application value.Conclusion ABSNp model can more accurately predict the risk of ischemic stroke in patients with nonvalvular atrial fibrillation.