Abstract 515: A Prediction Model For Left Ventricular Thrombus Persistence/recurrence: Based On A Prospective Study And A Retrospective Study

Abstract

Background: This study aimed to develop a prediction model to forecast thrombus persistence or recurrence in patients with left ventricular (LV) thrombus. Methods: We enrolled patients prospectively from 2020 to 2022 and retrospectively from 2013 to 2019 at the National Center of Cardiovascular Diseases of China. The two cohorts were combined to derive predictive thrombus persistence/recurrence models. The primary study comprised patients who had been consistently taking systemic oral anticoagulants and had imaging records available at the end of a three-month follow-up period. The Lasso regression algorithm was performed to select independent predictors and a nomogram risk prediction model was applied as a risk stratification tool. Results: A total of 172 patients were included, with 124 patients in a training set and 48 patients in a validation set. Six predictors were incorporated into the multivariate logistic regression prediction model. The area under the receiving operating characteristic was 0.852 in the training set and 0.631 in the validation set. Patients with protuberant thrombus and higher baseline D-dimer levels had a reduced risk of persistence/recurrence (OR 0.17, 95% CI 0.03-0.69, P = 0.025; OR 0.67, 95% CI 0.43-0.91, P = 0.030, separately), whereas thicker thrombus was linked to an increased rate of persistent thrombus (OR 1.11, 95% CI 1.05-1.20, P = 0.002). Additionally, thrombus persistence/recurrence rate was greater in patients with nonischemic cardiomyopathy and antiplatelet therapy. Conclusions: This prediction model provides tools and allows the identification of characteristics associated with unresolved thrombus.