Suppr超能文献

特定于病变的冠状动脉周围脂肪组织 CT 衰减可改善冠心病患者主要不良心血管事件的风险预测。

Lesion-specific pericoronary adipose tissue CT attenuation improves risk prediction of major adverse cardiovascular events in coronary artery disease.

机构信息

Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215006, China.

Department of Cardiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215006, China.

出版信息

Br J Radiol. 2024 Jan 23;97(1153):258-266. doi: 10.1093/bjr/tqad017.

Abstract

OBJECTIVES

To determine whether lesion-specific pericoronary adipose tissue CT attenuation (PCATa) is superior to PCATa around the proximal right coronary artery (PCATa-RCA) and left anterior descending artery (PCATa-LAD) for major adverse cardiovascular events (MACE) prediction in coronary artery disease (CAD).

METHODS

Six hundred and eight CAD patients who underwent coronary CTA from January 2014 to December 2018 were retrospectively included, with clinical risk factors, plaque features, lesion-specific PCATa, PCATa-RCA, and PCATa-LAD collected. MACE was defined as cardiovascular death, non-fatal myocardial infarction, unplanned revascularization, and hospitalization for unstable angina. Four models were established, encapsulating traditional factors (Model A), traditional factors and PCATa-RCA (Model B), traditional factors and PCATa-LAD (Model C), and traditional factors and lesion-specific PCATa (Model D). Prognostic performance was evaluated with C-statistic, area under receiver operator characteristic curve (AUC), and net reclassification index (NRI).

RESULTS

Lesion-specific PCATa was an independent predictor for MACE (adjusted hazard ratio = 1.108, P < .001). The C-statistic increased from 0.750 for model A to 0.762 for model B (P = .078), 0.773 for model C (P = .046), and 0.791 for model D (P = .005). The AUC increased from 0.770 for model A to 0.793 for model B (P = .027), 0.793 for model C (P = .387), and 0.820 for model D (P = .019). Compared with model A, the NRIs for models B, C, and D were 0.243 (-0.323 to 0.792, P = .392), 0.428 (-0.012 to 0.835, P = .048), and 0.708 (0.152-1.016, P = .001), respectively.

CONCLUSIONS

Lesion-specific PCATa improves risk prediction of MACE in CAD, which is better than PCATa-RCA and PCATa-LAD.

ADVANCES IN KNOWLEDGE

Lesion-specific PCATa was superior to PCATa-RCA and PCATa-LAD for MACE prediction.

摘要

目的

确定冠状动脉疾病(CAD)中,特定病变部位的冠状动脉周围脂肪组织 CT 衰减值(PCATa)是否优于右冠状动脉近端(PCATa-RCA)和左前降支(PCATa-LAD)的 PCATa 预测主要不良心血管事件(MACE)。

方法

回顾性纳入 2014 年 1 月至 2018 年 12 月期间接受冠状动脉 CTA 的 608 例 CAD 患者,收集临床危险因素、斑块特征、病变部位特定的 PCATa、PCATa-RCA 和 PCATa-LAD。MACE 定义为心血管死亡、非致死性心肌梗死、非计划血运重建和不稳定型心绞痛住院。建立了 4 个模型,包含传统因素(模型 A)、传统因素和 PCATa-RCA(模型 B)、传统因素和 PCATa-LAD(模型 C)以及传统因素和病变部位特定的 PCATa(模型 D)。通过 C 统计量、接收者操作特征曲线(AUC)下面积和净重新分类指数(NRI)评估预后性能。

结果

病变部位的 PCATa 是 MACE 的独立预测因子(调整后的危险比=1.108,P<0.001)。C 统计量从模型 A 的 0.750 增加到模型 B 的 0.762(P=0.078)、模型 C 的 0.773(P=0.046)和模型 D 的 0.791(P=0.005)。AUC 从模型 A 的 0.770 增加到模型 B 的 0.793(P=0.027)、模型 C 的 0.793(P=0.387)和模型 D 的 0.820(P=0.019)。与模型 A 相比,模型 B、C 和 D 的 NRI 分别为 0.243(-0.323 至 0.792,P=0.392)、0.428(-0.012 至 0.835,P=0.048)和 0.708(0.152-1.016,P=0.001)。

结论

病变部位的 PCATa 提高了 CAD 中 MACE 的风险预测,优于 PCATa-RCA 和 PCATa-LAD。

知识进展

病变部位的 PCATa 优于 PCATa-RCA 和 PCATa-LAD 预测 MACE。

相似文献

3
Prognostic Value of RCA Pericoronary Adipose Tissue CT-Attenuation Beyond High-Risk Plaques, Plaque Volume, and Ischemia.
JACC Cardiovasc Imaging. 2021 Aug;14(8):1598-1610. doi: 10.1016/j.jcmg.2021.02.026. Epub 2021 May 3.
9
Evaluating Pericoronary Adipose Tissue Attenuation to Predict Cardiovascular Events: A Multicenter Study in East Asians.
JACC Asia. 2024 Nov 12;5(1):1-11. doi: 10.1016/j.jacasi.2024.09.009. eCollection 2025 Jan.
10
Association of perivascular fat attenuation on computed tomography and heart failure with preserved ejection fraction.
ESC Heart Fail. 2023 Aug;10(4):2447-2457. doi: 10.1002/ehf2.14419. Epub 2023 May 31.

本文引用的文献

2
Inflammation drives residual risk in chronic kidney disease: a CANTOS substudy.
Eur Heart J. 2022 Dec 7;43(46):4832-4844. doi: 10.1093/eurheartj/ehac444.
4
Prognostic Value of RCA Pericoronary Adipose Tissue CT-Attenuation Beyond High-Risk Plaques, Plaque Volume, and Ischemia.
JACC Cardiovasc Imaging. 2021 Aug;14(8):1598-1610. doi: 10.1016/j.jcmg.2021.02.026. Epub 2021 May 3.
6
Myocardial Infarction Associates With a Distinct Pericoronary Adipose Tissue Radiomic Phenotype: A Prospective Case-Control Study.
JACC Cardiovasc Imaging. 2020 Nov;13(11):2371-2383. doi: 10.1016/j.jcmg.2020.06.033. Epub 2020 Aug 26.
7
Management of multivessel coronary artery disease in patients with non-ST-elevation myocardial infarction: a complex path to precision medicine.
Ther Adv Chronic Dis. 2020 Jul 1;11:2040622320938527. doi: 10.1177/2040622320938527. eCollection 2020.
8
Serial change of perivascular fat attenuation index after statin treatment: Insights from a coronary CT angiography follow-up study.
Int J Cardiol. 2020 Nov 15;319:144-149. doi: 10.1016/j.ijcard.2020.06.008. Epub 2020 Jun 15.
9
Diagnostic performance of deep learning-based vascular extraction and stenosis detection technique for coronary artery disease.
Br J Radiol. 2020 Sep 1;93(1113):20191028. doi: 10.1259/bjr.20191028. Epub 2020 Mar 25.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验