Suppr超能文献

脂质组学对经皮冠状动脉介入治疗(PCI)的完全闭塞性冠状动脉病变患者预后的影响。

Prognostic implication of lipidomics in patients with coronary total occlusion undergoing PCI.

机构信息

Department of Cardiology, Shanghai Institute of Cardiovascular Diseases, Zhongshan Hospital, Fudan University; National Clinical Research Center for Interventional Medicine; Shanghai Clinical Research Center for Interventional Medicine, Shanghai, People's Republic of China.

Shanghai Institute of Clinical Bioinformatics, Fudan University Center of Clinical Bioinformatics; Shanghai Respiratory Research Institute, Shanghai, People's Republic of China.

出版信息

Eur J Clin Invest. 2022 Nov;52(11):e13826. doi: 10.1111/eci.13826. Epub 2022 Jun 29.

Abstract

BACKGROUND

Predictors of prognosis in patients with coronary chronic total occlusion (CTO) undergoing elective percutaneous coronary intervention (PCI) have remained lacking. Lipidomic profiling enables researchers to associate lipid species with disease progression and may improve the prediction of cardiovascular events.

METHODS

In the present study, 781 lipids were measured by targeted lipidomic profiling in 350 individuals (50 healthy controls, 50 patients with coronary artery disease and 250 patients with CTO). L1-regularized logistic regression was used to identify lipid species associated with adverse cardiovascular events and create predicting models, which were verified by 10-fold cross-validation (200 repeats). Comparisons were made between a traditional model constructed with clinical characteristics alone and a combined model built with both lipidomic data and traditional factors.

RESULTS

Twenty-four lipid species were dysregulated exclusively in patients with CTO, most of which belonged to sphingomyelin (SM) and triacylglycerol (TAG). Compared with traditional risk factors, new model combining lipids and traditional factors had significantly improved performance in predicting adverse cardiovascular events in CTO patients after PCI (area under the curve, 0.870 vs. 0.726, p < .05; Akaike information criterion, 129 versus 156; net reclassification improvement, 0.312, p < .001; integrated discrimination improvement, 0.244, p < .001). Nomogram was built based on the incorporated model and proved efficient by Kaplan-Meier method.

CONCLUSIONS

Lipidomic profiling revealed lipid species which may participate in the formation of CTO and could contribute to the risk stratification in CTO patients undergoing PCI.

摘要

背景

接受选择性经皮冠状动脉介入治疗(PCI)的冠状动脉慢性完全闭塞(CTO)患者的预后预测因素仍然缺乏。脂质组学分析使研究人员能够将脂质种类与疾病进展相关联,并可能改善心血管事件的预测。

方法

在本研究中,通过靶向脂质组学分析在 350 名个体(50 名健康对照者、50 名冠心病患者和 250 名 CTO 患者)中测量了 781 种脂质。使用 L1-正则化逻辑回归来识别与不良心血管事件相关的脂质种类并创建预测模型,通过 10 倍交叉验证(200 次重复)进行验证。将仅使用临床特征构建的传统模型与同时使用脂质组学数据和传统因素构建的组合模型进行比较。

结果

24 种脂质种类仅在 CTO 患者中失调,其中大多数属于鞘磷脂(SM)和三酰甘油(TAG)。与传统危险因素相比,将脂质与传统因素相结合的新模型在预测 CTO 患者 PCI 后不良心血管事件方面具有显著改善的性能(曲线下面积,0.870 与 0.726,p<.05;Akaike 信息准则,129 与 156;净重新分类改善,0.312,p<.001;综合判别改善,0.244,p<.001)。基于纳入模型构建了列线图,并通过 Kaplan-Meier 方法证明了其效率。

结论

脂质组学分析揭示了可能参与 CTO 形成的脂质种类,并有助于对接受 PCI 的 CTO 患者进行风险分层。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb76/9786902/5c046ab357d8/ECI-52-e13826-g005.jpg

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