Prediction of adverse outcomes in nonischemic dilated cardiomyopathy: A CMR-based nomogram

狼牙棒 医学 列线图 内科学 扩张型心肌病 心脏病学 磁共振成像 队列 心力衰竭 临床终点 心肌病 心脏再同步化治疗 放射科 临床试验 射血分数 心肌梗塞 传统PCI
作者
Xiaorui Xiang,Kankan Zhao,Xiuyu Chen,Yanyan Song,Kai Yang,Shiqin Yu,Shujuan Yang,Jiaxin Wang,Zhixiang Dong,Minjie Lu,Likun Ma,Shihua Zhao
出处
期刊:International Journal of Cardiology [Elsevier BV]
卷期号:390: 131136-131136 被引量:1
标识
DOI:10.1016/j.ijcard.2023.131136
摘要

To develop and validate a novel nomogram score to predict outcomes in patients with nonischemic dilated cardiomyopathy (NIDCM) over a long follow-up period.A total of 335 consecutive NIDCM patients who underwent cardiac magnetic resonance (CMR) imaging were retrospectively enrolled. Comprehensive clinical evaluation and imaging investigation were obtained, including measurements of late gadolinium enhancement (LGE) and feature tracking (FT) images. All patients were followed up for a composite endpoint of major adverse cardiac events (MACE) including all-cause mortality and heart transplantation. These patients were randomly divided into development and validation cohorts (7:3).MACE occurred in 87 (37.2%) out of 234 patients in the development cohort, and in 31 (30.7%) out of 101 patients in the validation cohort. Five variables including NYHA class III-IV, NT-proBNP, beta-blocker medication, LGE presence, and LV global longitudinal strain (GLS) were found to be significantly associated with MACE and were used for constructing the nomogram. The nomogram achieved good discrimination with C-indexes in development and validation cohorts respectively. The calibration curve for 1-, 3-, and 5-year survival probability also showed high coherence between the predicted and actual probability of MACE. Decision curve analysis identified the model was significantly better net benefit in predicting MACE.A novel nomogram score of a predictive model that incorporates clinical factors and imaging features was constructed, which could be conveniently used to facilitate risk evaluation in patients with NIDCM.
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