Suppr超能文献

薄帽纤维粥样斑块而非任何脂质斑块增加糖尿病患者心血管事件的风险:来自 COMBINE OCT-FFR 试验的见解。

Thin-Cap Fibroatheroma Rather Than Any Lipid Plaques Increases the Risk of Cardiovascular Events in Diabetic Patients: Insights From the COMBINE OCT-FFR Trial.

机构信息

Cardiovascular Department, University of Trieste, Italy (E.F.).

Heart and Vascular Center, Semmelweis University, Budapest, Hungary (B.B.).

出版信息

Circ Cardiovasc Interv. 2022 May;15(5):e011728. doi: 10.1161/CIRCINTERVENTIONS.121.011728. Epub 2022 Apr 29.

Abstract

BACKGROUND

Autopsy studies have established that thin-cap fibroatheromas (TCFAs) are the most frequent cause of fatal coronary events. In living patients, optical coherence tomography (OCT) has sufficient resolution to accurately differentiate TCFA from thick-cap fibroatheroma (ThCFA) and not lipid rich plaque (non-LRP). However, the impact of OCT-detected plaque phenotype of nonischemic lesions on future adverse events remains unknown. Therefore, we studied the natural history of OCT-detected TCFA, ThCFA, and non-LRP in patients enrolled in the prospective multicenter COMBINE FFR-OCT trial (Combined Optical Coherence Tomography Morphologic and Fractional Flow Reserve Hemodynamic Assessment of Non-Culprit Lesions to Better Predict Adverse Event Outcomes in Diabetes Mellitus Patients).

METHODS

In the COMBINE FFR-OCT trial, patients with diabetes and ≥1 lesion with a fractional flow reserve >0.80 underwent OCT evaluation and were clinically followed for 18 months. A composite primary end point of cardiac death, target vessel-related myocardial infarction, target-lesion revascularization, and hospitalization for unstable angina was evaluated in relation to OCT-based plaque morphology.

RESULTS

A total of 390 patients (age 67.5±9 years; 63% male) with ≥1 nonischemic lesions underwent OCT evaluation: 284 (73%) had ≥1 LRP and 106 (27%) non-LRP lesions. Among LRP patients, 98 (34.5%) had ≥1 TCFA. The primary end point occurred in 7% of LRP patients compared with 1.9% of non-LRP patients (7.0% versus 1.9%; hazard ratio [HR], 3.9 [95% CI, 0.9-16.5]; =0.068; log rank-=0.049). However, within LRP patients, TCFA patients had a much higher risk for primary end point compared with ThCFA (13.3% versus 3.8%; HR, 3.8 [95% CI, 1.5-9.5]; <0.01), and to non-LRP patients (13.3% versus 1.9%; HR, 7.7 [95% CI, 1.7-33.9]; <0.01), whereas ThCFA patients had risk similar to non-LRP patients (3.8% versus 1.9%; HR, 2.0 [95% CI, 0.42-9.7]; =0.38). Multivariable analyses identified TCFA as the strongest independent predictor of primary end point (HR, 6.79 [95% CI, 1.50-30.72]; =0.013).

CONCLUSIONS

Among diabetes patients with fractional flow reserve-negative lesions, patients carrying TCFA lesions represent only one-third of LRP patients and are associated with a high risk of future events while patients carrying LRP-ThCFA and non-LRP lesions portend benign outcomes.

REGISTRATION

URL: https://www.

CLINICALTRIALS

gov; Unique identifier: NCT02989740.

摘要

背景

尸检研究已经证实,薄帽纤维粥样斑块(TCFA)是导致致命性冠状动脉事件的最常见原因。在存活的患者中,光学相干断层扫描(OCT)具有足够的分辨率,可以准确地区分 TCFA 与厚帽纤维粥样斑块(ThCFA)和富含脂质斑块(非-LRP)。然而,OCT 检测到非缺血性病变的斑块表型对未来不良事件的影响尚不清楚。因此,我们研究了前瞻性多中心 COMBINE FFR-OCT 试验(合并光学相干断层扫描形态学和血流储备分数的非罪犯病变评估以更好地预测糖尿病患者不良事件结局)中 OCT 检测到的 TCFA、ThCFA 和非-LRP 的自然史。

方法

在 COMBINE FFR-OCT 试验中,有 ≥1 个血流储备分数>0.80 的糖尿病患者接受了 OCT 评估,并进行了 18 个月的临床随访。复合主要终点为心脏死亡、靶血管相关心肌梗死、靶病变血运重建和不稳定型心绞痛住院治疗,与基于 OCT 的斑块形态学相关。

结果

共有 390 例(年龄 67.5±9 岁;63%为男性)患者有≥1 个非缺血性病变接受了 OCT 评估:284 例(73%)有≥1 个富含脂质斑块,106 例(27%)为非富含脂质斑块。在富含脂质斑块患者中,有 98 例(34.5%)有≥1 个 TCFA。富含脂质斑块患者的主要终点发生率为 7%,而非富含脂质斑块患者为 1.9%(7.0%比 1.9%;危险比[HR],3.9[95%可信区间,0.9-16.5];=0.068;对数秩检验=0.049)。然而,在富含脂质斑块患者中,TCFA 患者的主要终点风险明显高于 ThCFA(13.3%比 3.8%;HR,3.8[95%可信区间,1.5-9.5];<0.01)和非富含脂质斑块患者(13.3%比 1.9%;HR,7.7[95%可信区间,1.7-33.9];<0.01),而 ThCFA 患者的风险与非富含脂质斑块患者相似(3.8%比 1.9%;HR,2.0[95%可信区间,0.42-9.7];=0.38)。多变量分析确定 TCFA 是主要终点的最强独立预测因子(HR,6.79[95%可信区间,1.50-30.72];=0.013)。

结论

在有血流储备分数阴性病变的糖尿病患者中,携带 TCFA 病变的患者仅占富含脂质斑块患者的三分之一,与未来发生事件的风险较高相关,而携带富含脂质斑块-ThCFA 和非富含脂质斑块的患者则预示着良性结局。

注册

网址:https://www.

临床试验

gov;独特标识符:NCT02989740。

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