Research on the risk factors and predictive model for intracardiac thrombosis in patients with dilated cardiomyopathy / 安徽医科大学学报

ABSTRACT

Objective @#To explore the risk factors for intracardiac thrombosis in dilated cardiomyopathy (DCM) pa- tients and to construct , validate , and evaluate a nomogram prediction model based on these factors .@*Methods @#88 patients diagnosed with DCM and complicated with intracardiac thrombus , and 544 patients without intracardiac thrombus were included . The participants were randomly divided into training and validation sets at a ratio of 7 ∶ 3 . U sing both univariate and multivariate Logistic regression analyses , independent risk factors for intracardiac thrombosis in DCM patients were identified . A nomogram prediction model was constructed using R software . The model ’s validity and performance were assessed using the receiver operating characteristic (ROC) curve , the Hos- mer-Lemeshow goodness-of-fit test , calibration curve , and decision curve . @*Results @#The binary Logistic regression analysis showed that age , atrial fibrillation , left ventricular end-diastolic diameter ( LVEDD) , brain natriuretic peptide ( BNP) , and β-blockers were independently associated with intracardiac thrombosis in DCM patients . Based on these five factors , a nomogram was constructed and validated . The area under the ROC curve for the training set was 0. 823 (95% CI: 0. 760 ~ 0. 887) and 0 . 803 (95% CI: 0 . 705 ~ 0 . 901) for the validation set , in- dicating a good discriminative ability. The Hosmer-Lemeshow test results for the calibration curve were ( χ2 = 6. 679 , P = 0. 572) for the training set and ( χ2 = 2 . 588 , P = 0. 958) for the validation set , indicating a good fit between predicted and ob served outcomes . The decision curve showed a high net clinical benefit in the threshold range of 0. 05 ~ 0. 92 . @*Conclusion @#Based on age , atrial fibrillation , LVEDD , BNP , and β-blockers , the nomo- gram prediction model exhibits good discriminative and calibration abilities , and high clinical benefit. It can effec- tively guide clinicians in early intervention of risk factors , reducing the risk of intracardiac thrombosis in DCM pa- tients .