Predictive value of cardiac magnetic resonance parametric nomogram models for adverse cardiovascular events in elderly patients with dilated cardiomyopathy

WANG Ling; LU Guowei; ZHANG Hong; YIN Chengjun; CHEN Feng; TIAN Ronghua

doi:10.12122/j.issn.1674-4500.2024.01.13

Abstract：Objective To investigate the predictive value of cardiac magnetic resonance(CMR)parametric nomogram modeling for major adverse cardiovascular events(MACE)in elderly patients with dilated cardiomyopathy(DCM).Methods A total of 173 elderly patients with DCM who underwent CMR at Xiaogan Hospital of Wuhan University of Science and Technology from July 2017 to July 2020 were retrospectively analyzed,and they were randomly divided into a training set(n=104)and a test set(n=69)in a ratio of 6:4.Potential predictors were screened by Lasso regression and multifactorial Cox regression,and the MACE nomogram prediction model for DCM patients was constructed with these factors.The nomogram model was evaluated and validated by calibration curve,ROC curve,decision curve analysis,and Kaplan-Meier survival analysis.Results The median follow-up was 29.7(16.4,45.4)months.At the end of follow-up,MACE occurred in 59(34.1%)patients.A total of 9 potential predictors were screened by LASSO regression and cross-validation.The results of multifactorial Cox regression analysis showed that NYHA class III-IV,N-terminal-brain natriuretic peptide precursor,beta-blocker,CMR late gadolinium enhancement,and overall longitudinal strain of the left ventricle were risk factors for the development of MACE in patients with DCM,and a nomogram prediction model was constructed with these indicators.In the training and test sets,the calibration plots showed that the nomogram predicted 1-year and 3-year survival in good agreement with the actual survival.The area under the ROC curve for 1-year and 3-year survival prediction in the training set was 0.850(95%CI:0.748-0.953)and 0.853(95%CI:0.797-0.909),respectively,and that for 1-year and 3-year survival prediction in the test set was 0.858(95%CI:0.758-0.959)and 0.887(95%CI:0.816-0.958),respectively.The results of the decision curve analysis showed that the nomogram model had a higher net clinical benefit rate.The results of Kaplan-Meier survival analysis showed that patients in the high-risk group of the predictive model had a reduced probability of survival compared with the low-risk group(P<0.05).Conclusion In this study,we constructed a nomogram prediction model for the occurrence of MACE in elderly patients with DCM by clinical and CMR characteristic parameters,which has good calibration,differentiation and clinical application value.