Suppr超能文献

急性冠状动脉综合征患者营养不良与冠状动脉斑块特征的关联:一项光学相干断层扫描研究

Association between Malnutrition and Coronary Plaque Characteristics in Patients with Acute Coronary Syndrome: An Optical Coherence Tomography Study.

作者信息

Yan Haihao, Yao Wenjing, Yang Qian, Li Congcong, Wang Zhenyu, Li Tianxing, Li Yanhong, Song Kexin, Zhang Feifei, Dang Yi

机构信息

Department of Internal Medicine, Graduate School of Hebei Medical University, 050017 Shijiazhuang, Hebei, China.

Department of Cardiology Center, Hebei General Hospital, 050051 Shijiazhuang, Hebei, China.

出版信息

Rev Cardiovasc Med. 2023 Oct 23;24(10):303. doi: 10.31083/j.rcm2410303. eCollection 2023 Oct.

Abstract

BACKGROUND

Malnutrition has a negative impact on patients with arteriosclerotic cardiovascular disease (ASCVD); however, only a few studies have confirmed the effect of malnutrition on atherosclerosis. We aimed to investigate the association between malnutrition and vulnerable plaques via optical coherence tomography (OCT).

METHODS

Overall, 142 acute coronary syndrome (ACS) patients were included in this study. Malnutrition was assessed using the Controlled Nutritional Status Score (CONUT), and plaque vulnerability was measured using OCT. Finally, patients were divided into four groups according to their CONUT scores and body mass index (BMI) 25.0 or not, to further compare the effects of both factors on plaque characteristics in patients.

RESULTS

OCT results showed that there were significant differences in plaque rupture, thin cap fibroatheroma (TCFA), minimal fiber cap thickness (FCT), thrombus, and macrophage infiltration between different nutritional states [Absent (0-1) vs Mild (2-4) vs Moderate (5-8), plaque rupture: 34.8% vs 52.5% vs 66.7%, = 0.038; TCFA: 10.1% vs 24.6% vs 33.3%, = 0.039; minimal FCT: 125.0 vs 110.4 vs 96.9, = 0.022; thrombus: 50.7% vs 70.5% vs 83.3%, = 0.019]. Multivariate logistic regression showed that malnutrition was a significant predictor of plaque vulnerability. Plaque rupture: CONUT score (odds ratio [OR]: 1.448, 95% confidence interval [CI]: 1.136-1.845, = 0.003), Mild (OR: 1.981, 95% CI: 0.932-4.210, = 0.075), and Moderate (OR: 4.375, 95% CI: 1.048-18.255, = 0.043); TCFA: CONUT score (OR: 1.334, 95% CI: 1.029-1.730, = 0.030), Mild (OR: 3.518, 95% CI: 1.251-9.897, = 0.017), and Moderate (OR: 4.863, 95% CI: 1.019-23.208, = 0.047); and macrophage: CONUT score (OR: 1.343, 95% CI: 1.060-1.700, = 0.015), Mild (OR: 3.016, 95% CI: 1.305-6.974, = 0.010), and Moderate (OR: 4.637, 95% CI: 1.159-18.552, = 0.030). Combined CONUT score and BMI showed an independent association with macrophages in the malnourished and overweight group (OR: 4.010, 95% CI: 1.188-13.537, = 0.025).

CONCLUSIONS

Malnutrition is a predictor of vulnerable plaques and is associated with inflammatory progression.

摘要

背景

营养不良对动脉粥样硬化性心血管疾病(ASCVD)患者有负面影响;然而,仅有少数研究证实了营养不良对动脉粥样硬化的影响。我们旨在通过光学相干断层扫描(OCT)研究营养不良与易损斑块之间的关联。

方法

本研究共纳入142例急性冠状动脉综合征(ACS)患者。采用控制营养状况评分(CONUT)评估营养不良情况,并用OCT测量斑块易损性。最后,根据CONUT评分和体重指数(BMI)是否≥25.0将患者分为四组,以进一步比较这两个因素对患者斑块特征的影响。

结果

OCT结果显示,不同营养状态下(无营养不良(0 - 1分)vs轻度营养不良(2 - 4分)vs中度营养不良(5 - 8分)),斑块破裂、薄帽纤维粥样瘤(TCFA)、最小纤维帽厚度(FCT)、血栓及巨噬细胞浸润存在显著差异[斑块破裂:34.8% vs 52.5% vs 66.7%,P = 0.038;TCFA:10.1% vs 24.6% vs 33.3%,P = 0.039;最小FCT:125.0 vs 110.4 vs 96.9,P = 0.022;血栓:50.7% vs 70.5% vs 83.3%,P = 0.019]。多因素逻辑回归显示,营养不良是斑块易损性的显著预测因素。斑块破裂:CONUT评分(比值比[OR]:1.448,95%置信区间[CI]:1.136 - 1.845,P = 0.003)、轻度营养不良(OR:1.981,95% CI:0.932 - 4.210,P = 0.075)及中度营养不良(OR:4.375,95% CI:1.048 - 18.255,P = 0.043);TCFA:CONUT评分(OR:1.334,95% CI:1.029 - 1.730,P = 0.030)、轻度营养不良(OR:3.518,95% CI:1.251 - 9.897,P = 0.017)及中度营养不良(OR:4.863,95% CI:1.019 - 23.208,P = 0.047);巨噬细胞:CONUT评分(OR:1.343,95% CI:1.060 - 1.700,P = 0.015)、轻度营养不良(OR:3.016,95% CI:1.305 - 6.974,P = 0.010)及中度营养不良(OR:4.637,95% CI:1.159 - 18.552,P = 0.030)。CONUT评分与BMI联合显示,在营养不良和超重组中与巨噬细胞存在独立关联(OR:4.010,95% CI:1.188 - 13.537,P = 0.025)。

结论

营养不良是易损斑块的预测因素,且与炎症进展相关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ae2/11273137/d7857a2721ca/2153-8174-24-10-303-g1.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