医学
内科学
心脏病学
心外膜脂肪组织
脂肪组织
射血分数
接收机工作特性
冠状动脉疾病
曲线下面积
置信区间
作者
Verena Brandt,Raffi Bekeredjian,U Joseph Schoepf,Akos Varga-Szemes,Tilman Emrich,Gilberto J Aquino,Josua Decker,Richard R Bayer,Lauren Ellis,Ullrich Ebersberger,Christian Tesche
标识
DOI:10.1016/j.ejrad.2022.110157
摘要
The purpose of this study was to determine whether EAT volume in combination with coronary CT angiography (CCTA)-derived plaque quantification and CT-derived fractional flow reserve (CT-FFR) has prognostic implication with major adverse cardiac events (MACE).Patients (n = 117, 58 ± 10 years, 61% male) who had previously undergone invasive coronary angiography (ICA) and CCTA were retrospectively analyzed. Follow-up was performed to record MACE. EAT volume and plaque measures were derived from non-contrast and contrast-enhanced CT images using a semi-automatic software approach, while CT-FFR was calculated using a machine-learning algorithm. The diagnostic performance to identify MACE was evaluated using univariable and multivariable Cox proportional hazards analysis and concordance (C)-indices.During a median follow-up period of 40.4 months, 19 events were registered. EAT volume, CCTA ≥ 50% stenosis, and CT-FFR were significantly different in patients developing MACE (all p < 0.05). The following parameters were predictors of MACE in adjusted multivariable Cox regression analysis (hazard ratio [HR]): EAT volume (HR 2.21, p = 0.023), indexed EAT volume (HR 2.03, p = 0.035), and CCTA ≥ 50% (HR 1.05, p = 0.048). A model including Morise score, CCTA ≥ 50% stenosis, and EAT volume showed significantly improved C-index to Morise score alone (AUC 0.83 vs. 0.66, p = 0.004).Facing limitations in conventional cardiovascular risk scoring models, this observational study demonstrates that the prediction performance of our proposed method achieves a significant improvement in prognostic ability, especially when compared to models such as Morise score alone or its combination with CCTA and CT-FFR.
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