Abstract

Introduction: The prevalence of thromboembolism (VTE) in cardiac amyloidosis (CA) is not well defined. Additionally, there is no risk stratification tool to identify CA subjects at risk for VTE to guide prophylactic treatment. We sought to identify the prevalence of VTE in CA and to develop a model to predict VTE in this population. Methods: A total of 150 subjects from two academic centers with confirmed CA (69±11years, 56% male, 58% AL-CA), and no history of VTE, atrial arrhythmia or anticoagulation use were included. The primary endpoint was DVT, pulmonary embolism or right atrial thrombi (RA). The LASSO technique was used to evaluate nearly 50 potential clinical and echocardiographic covariates in order to develop a multivariable model for predicting VTE. The subjects were randomly divided in a proportion of 70:30 into training and testing dataset. The diagnostic performance of the model was assessed by calculating the AUC of a ROC curve. Results: Thirty-two subjects (21%) developed VTE after CA diagnosis (18 DVT, 3 RA thrombus, 11 in multiple concurrent locations). The majority occurred within one year of the echocardiogram (78%). Multivariable analysis revealed four variables independently predictive of VTE (p<0.05), based on the regularization parameter (lambda=0.08). VTE was more likely in the presence of liver disease or alcohol abuse, end-stage renal disease, increased LA volume and lower TAPSE. The model had excellent discrimination (AUC=0.823) (Panels A-B) and when applied to the test set an accuracy of 84.4%. The nomogram that can be used to predict the probability of VTE in CA using the covariates identified is illustrated on Panel C. Conclusions: High prevalence of VTE was identified in CA. The developed clinical and echocardiographic risk scheme is user-friendly and has the potential to identify patients with CA at high risk for VTE. It remains to be determined if pre-emptive anticoagulation in this higher risk group might be beneficial.

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