血浆动脉粥样硬化指数（AIP）和残余样颗粒胆固醇（RLP-C）作为pci后不良心血管事件的预后生物标志物

IF 3.6 3区医学 Q2 PHARMACOLOGY & PHARMACY

Journal of clinical lipidology Pub Date : 2025-05-01 DOI:10.1016/j.jacl.2025.04.031

John Nelson MD, Hamed Rafiee MD, Pegah Bahrami MD, Mohammad Mehdi Zare MD, Davood Semirani-Nezhad MD, Amir Parsa Abhari MD, Sima Shamshiri Khamene MD, Parham Dastjerdi MD, Fatemeh Fathabadi MD, Hamidreza Soleimani MD, Kaveh Hosseini MD

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Several studies have identified AIP and RLP-C as potential predictors of post-percutaneous coronary intervention (PCI) prognosis; however, contradicting results exist.</div></div><div><h3>Objective/Purpose</h3><div>To investigate and compare the predictive capacities of AIP and RLP-C for post-PCI adverse cardiovascular (CV) events.</div></div><div><h3>Methods</h3><div>This was a secondary data analysis on patients undergoing PCI from 2015 to 2021. AIP was calculated as log [TG / HDL-C] and RLP-C as [TC – HDL-C – LDL-C]. The primary outcome was the first episode of MACCE (defined as all-cause mortality, myocardial infarction (MI), stroke, target vessel revascularization, target lesion revascularization, and coronary artery bypass graft). Secondary outcomes were the first incidence of MI, all-cause mortality, and stroke. Parametric survival models with Gompertz and Weibull distributions were used. Model 1 was crude. Model 2 was adjusted for age, gender, smoking, and BMI. 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引用次数: 0

摘要

背景/摘要aip是一种与脂蛋白颗粒大小和动脉粥样硬化性相关的脂质指数。RLP-C是富含甘油三酯的脂蛋白的一个亚群，尽管服用降脂药物，仍与残留的动脉粥样硬化风险相关。一些研究已经确定AIP和RLP-C是经皮冠状动脉介入治疗（PCI）后预后的潜在预测因素；然而，矛盾的结果存在。目的：探讨并比较AIP和RLP-C对pci术后心血管不良事件的预测能力。方法对2015年至2021年接受PCI治疗的患者进行二次数据分析。AIP计算为log [TG / HDL-C]， RLP-C计算为[TC - HDL-C - LDL-C]。主要终点是首次MACCE发作（定义为全因死亡率、心肌梗死（MI）、卒中、靶血管重建术、靶病变重建术和冠状动脉搭桥术）。次要结局是心肌梗死的首次发生率、全因死亡率和卒中。采用Gompertz和Weibull分布的参数生存模型。模型1是粗糙的。模型2对年龄、性别、吸烟和BMI进行了调整。模型3还对高血压、糖尿病、血脂异常、既往ACS、既往PCI和肌酐水平进行调整。进行受试者工作特征（ROC）曲线分析。结果共纳入13392例患者，随访时间中位数为376天。在模型3中，各项指标与MACCE或卒中无显著相关性。在模型3中，RLP-C与MI有显著相关性（HR = 1.36,95% CI: 1.03 ~ 1.80, P = 0.029），但与AIP的相关性不显著（HR = 1.32,95% CI: 0.99 ~ 1.75， P值 = 0.058）。在ROC曲线分析中，AIP对心肌梗死的预测效果最好（AUC: 0.659 vs 0.650）。作为连续变量，AIP和RLP-C均与全因死亡率显著相关(AIP: HR = 1.83,95% CI: 1.02 ~ 3.28, P = 0.043；RLP-C: HR = 1.38,95% CI: 1.11 ~ 1.72, P = 0.003)与分类相反。ROC曲线分析显示RLP-C对死亡率有较高的预测能力（AUC: 0.650 vs 0.641）。据我们所知，这是第一个比较AIP和RLP-C对pci后不良CV事件预测效用的研究。AIP和RLP-C与pci术后死亡率均有显著相关性，RLP-C具有更好的预测能力。RLP-C也与pci后心肌梗死显著相关，但AIP具有更好的预测能力。

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The atherogenic index of plasma (AIP) and remnant-like particle cholesterol (RLP-C) as prognostic biomarkers of post-PCI adverse cardiovascular events

Background/Synopsis

AIP is a lipid index correlating with lipoprotein particle size and atherogenicity. RLP-C is a subset of triglyceride-rich lipoproteins, associated with residual atherogenic risk observed despite taking lipid-lowering medications. Several studies have identified AIP and RLP-C as potential predictors of post-percutaneous coronary intervention (PCI) prognosis; however, contradicting results exist.

Objective/Purpose

To investigate and compare the predictive capacities of AIP and RLP-C for post-PCI adverse cardiovascular (CV) events.

Methods

This was a secondary data analysis on patients undergoing PCI from 2015 to 2021. AIP was calculated as log [TG / HDL-C] and RLP-C as [TC – HDL-C – LDL-C]. The primary outcome was the first episode of MACCE (defined as all-cause mortality, myocardial infarction (MI), stroke, target vessel revascularization, target lesion revascularization, and coronary artery bypass graft). Secondary outcomes were the first incidence of MI, all-cause mortality, and stroke. Parametric survival models with Gompertz and Weibull distributions were used. Model 1 was crude. Model 2 was adjusted for age, gender, smoking, and BMI. Model 3 was additionally adjusted for hypertension, diabetes, dyslipidemia, previous ACS, previous PCI, and creatinine levels. Time-dependent receiver operating characteristic (ROC) curve analysis was performed.

Results

A total of 13,392 patients were included and followed for a median time of 376 days. In model 3, no significant associations were observed between the indices and MACCE or stroke. While RLP-C showed significant association with MI in model 3 (HR = 1.36, 95% CI: 1.03 to 1.80, P = 0.029) the same association for AIP was insignificant by a small margin (HR = 1.32, 95% CI: 0.99 to 1.75, p-value = 0.058). However, MI was best predicted by AIP (AUC: 0.659 vs 0.650) in ROC curve analysis. Both AIP and RLP-C were significantly associated with all-cause mortality as continuous variables (AIP: HR = 1.83, 95% CI: 1.02 to 3.28, P = 0.043; RLP-C: HR = 1.38, 95% CI: 1.11 to 1.72, P = 0.003) as opposed to categorical. RLP-C exhibited higher prediction ability for mortality in ROC curve analysis (AUC: 0.650 vs 0.641).

Conclusions

To the best of our knowledge this is the first study to compare the predictive utility of both AIP and RLP-C for post-PCI adverse CV events. Both AIP and RLP-C had significant associations with post-PCI mortality, and RLP-C showed better predictive ability. RLP-C was also significantly associated with post-PCI MI, however, AIP had superior predictive ability.

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来源期刊

Journal of clinical lipidology 医学-药学

CiteScore

7.00

自引率

6.80%

发文量

209

审稿时长

49 days

期刊介绍： Because the scope of clinical lipidology is broad, the topics addressed by the Journal are equally diverse. Typical articles explore lipidology as it is practiced in the treatment setting, recent developments in pharmacological research, reports of treatment and trials, case studies, the impact of lifestyle modification, and similar academic material of interest to the practitioner. Sections of Journal of clinical lipidology will address pioneering studies and the clinicians who conduct them, case studies, ethical standards and conduct, professional guidance such as ATP and NCEP, editorial commentary, letters from readers, National Lipid Association (NLA) news and upcoming event information, as well as abstracts from the NLA annual scientific sessions and the scientific forums held by its chapters, when appropriate.