通过了解冠状动脉疾病的剩余风险和预防/治疗的新目标来改善健康:HURRICANE项目的基本原理和研究方案

European heart journal open Pub Date : 2025-01-28 eCollection Date: 2025-01-01 DOI:10.1093/ehjopen/oeaf005
Chiara Caselli, Mariaelena Occhipinti, Katia Pane, Carmelo De Gori, Silvia Rocchiccioli, Nicoletta Botto, Concetta Prontera, Carlo Cavaliere, Rosetta Ragusa, Cecilia Vecoli, Francesco Sansone, Emanuela Passaro, Elisa Ceccherini, Antonio Morlando, Alberto Clemente, Monica Franzese, Erica Maffei, Bruna Punzo, Alessia Gimelli, Filippo Cademartiri, Danilo Neglia
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引用次数: 0

摘要

稳定性冠状动脉疾病(CAD)患者的最佳药物治疗降低了发病率和死亡率,但留下了疾病进展和事件的大量剩余风险(RR)。根据最近的证据,胰岛素抵抗或糖尿病前期,加上甘油三酯水平升高、高密度脂蛋白胆固醇水平低下和功能低下,通常与慢性炎症状态有关,被认为是心血管代谢和血管RR的相关组成部分。在目前的项目中,我们的目标是发现与新出现的心脏代谢和血管风险模式相关的特定个体遗传/分子谱,并与更严重的稳定CAD表型相关。为此,我们将分析561例疑似稳定型冠状动脉疾病患者的临床数据、血液样本和影像学数据,并通过心脏计算机断层扫描对冠状动脉斑块进行定性和定量分析,建立疾病严重程度和程度的综合预测模型。新的预测模型将纳入与更严重的冠状动脉粥样硬化相关的相关临床和遗传/分子变量,将在类似的前瞻性患者人群中进行验证,并扩展到预测冠状动脉疾病表型的进展(随访1年),尽管有最佳的药物治疗。注册临床试验。gov ID: NCT06601153。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Health improvements by understanding residual risk in coronary artery disease and new targets for prevention/treatment: rationale and research protocol of the HURRICANE project.

Optimal medical treatment in patients with stable coronary artery disease (CAD) reduced morbidity and mortality but left a substantial residual risk (RR) of disease progression and events. According to recent evidence, insulin resistance or pre-diabetes together with elevated levels of triglycerides, low levels, and functionality of HDL-cholesterol, often associated with a chronic inflammatory state, are deemed to be relevant components of cardiometabolic and vascular RR. In the present project, we aim at discovering specific individual genetic/molecular profiles subtending emerging cardiometabolic and vascular risk patterns and associated with more severe stable CAD phenotypes. To this end, we will analyse clinical data, blood samples, and imaging data already gathered in a retrospective population of 561 patients with suspected stable coronary disease and will develop integrated predictive models of severity and extent of disease defined by qualitative and quantitative analysis of coronary plaques by cardiac computed tomography. The new predictive models, which will incorporate relevant clinical and genetic/molecular variables associated with more severe coronary atherosclerosis, will be validated in a similar prospective population of patients and extended to the prediction of progression (at 1 year follow-up) of coronary disease phenotypes, occurring despite optimal medical treatment. Registration  ClinicalTrials.gov ID: NCT06601153.

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