Abstract
Intracardiac thrombosis is a severe complication in patients with non-ischemic dilated cardiomyopathy. This study aims to develop and validate an individualized nomogram to evaluate the risk of intracardiac thrombosis in patients with non-ischemic dilated cardiomyopathy. This retrospective study included patients diagnosed with dilated cardiomyopathy at first admission. Clinical baseline characteristics were acquired from electronic medical record systems. Multiple methods were applied to screen the key variables and generate multiple different variable combinations. Multivariable logistic regression was used to build the models, and the optimal model was chosen by comparing the discrimination. Then we checked the performance of the model in different thrombus subgroups. Finally, the model was presented using a nomogram and evaluated from the perspectives of discrimination, calibration, and clinical usefulness. Internal validation was performed by extracting different proportions of data for Bootstrapping. Ultimately, 564 eligible patients were enrolled, 67 of whom developed an intracardiac thrombosis. Risk factors included d-dimer, white blood cell count, high-sensitivity C-reactive protein, pulse pressure, history of stroke, hematocrit, and NT-proBNP in the optimal model. The model had good discrimination and calibration, and the area under the curve (AUC) was 0.833 (0.782-0.884), and the model's performance in each subgroup was stable. Clinical decision curve analysis showed that the model had clinical application value when the high-risk threshold was between 2% and 78%. The AUC of interval validation (30% and 70% data resampling) was 0.844 (0.765-0.924) and 0.833 (0.775-0.891), respectively. This novel intracardiac thrombosis nomogram could be conveniently applied to facilitate the individual intracardiac thrombosis risk assessment in patients with non-ischemic dilated cardiomyopathy.