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利用一种包含急性冠脉综合征患者生物标志物的新型判别模型识别斑块破裂。

Identification of plaque ruptures using a novel discriminative model comprising biomarkers in patients with acute coronary syndrome.

机构信息

Division of Cardiology, Department of Internal Medicine, Korea University Anam Hospital, Korea University School of Medicine, #73, Inchon-ro, Seongbuk-gu, Seoul, 02841, Korea.

Department of Cardiovascular Medicine, Regional Cardiocerebrovascular Center, Wonkwang University Medical Center, Iksan, Korea.

出版信息

Sci Rep. 2020 Nov 19;10(1):20228. doi: 10.1038/s41598-020-77413-3.

DOI:10.1038/s41598-020-77413-3
PMID:33214686
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7677551/
Abstract

Soluble lectin-like oxidized low-density lipoprotein receptor-1 (sLOX-1), neutrophil gelatinase-associated lipocalin (NGAL), and matrix metalloproteinase-9 (MMP-9) are inflammatory biomarkers involved in plaque destabilization resulting in acute coronary syndrome (ACS). This study aimed to investigate the diagnostic value of a combination of biomarkers to discriminate plaque ruptures in the setting of ACS. Eighty-five ACS patients with optical coherence tomography (OCT) images of the culprit plaque were included and categorized into two groups: ACS with plaque rupture (Rupture group, n = 42) or without plaque rupture (Non-rupture group, n = 43) verified by OCT. A discriminative model of plaque rupture using several biomarkers was developed and validated. The Rupture group had higher white blood cell (WBC) counts and peak creatine kinase-myocardial band (CK-MB) levels (13.39 vs. 2.69 ng/mL, p = 0.0016). sLOX-1 (227.9 vs. 51.7 pg/mL, p < 0.0001) and MMP-9 (13.4 vs. 6.45 ng/mL, p = 0.0313) levels were significantly higher in the Rupture group, whereas NGAL showed a trend without statistical significance (59.03 vs. 53.80 ng/mL, p = 0.093). Receiver operating characteristic curves to differentiate Rupture group from Non-rupture group calculated the area under the curve for sLOX-1 (p < 0.001), MMP-9 (p = 0.0274), and NGAL (p = 0.0874) as 0.763, 0.645, and 0.609, respectively. A new combinatorial discriminative model including sLOX-1, MMP-9, WBC count, and the peak CK-MB level showed an area under the curve of 0.8431 (p < 0.001). With a cut-off point of 0.614, the sensitivity and specificity of plaque rupture were 62.2% and 97.6%, respectively. The new discriminative model using sLOX-1, MMP-9, WBC count, and peak CK-MB levels could better identify plaque rupture than each individual biomarker in ACS patients.

摘要

可溶性凝集素样氧化低密度脂蛋白受体-1(sLOX-1)、中性粒细胞明胶酶相关脂质运载蛋白(NGAL)和基质金属蛋白酶-9(MMP-9)是参与斑块不稳定导致急性冠脉综合征(ACS)的炎症生物标志物。本研究旨在探讨联合生物标志物诊断 ACS 患者斑块破裂的价值。共纳入 85 例接受光学相干断层扫描(OCT)检查的 ACS 患者,根据 OCT 结果将其分为斑块破裂组(破裂组,n=42)和非破裂组(非破裂组,n=43)。建立并验证了一种基于多种生物标志物的斑块破裂判别模型。破裂组的白细胞(WBC)计数和肌酸激酶同工酶-MB 峰值(CK-MB)水平更高(13.39 vs. 2.69ng/mL,p=0.0016)。sLOX-1(227.9 vs. 51.7pg/mL,p<0.0001)和 MMP-9(13.4 vs. 6.45ng/mL,p=0.0313)水平在破裂组中明显升高,而 NGAL 则无显著差异(59.03 vs. 53.80ng/mL,p=0.093)。计算区分破裂组和非破裂组的受试者工作特征曲线,sLOX-1(p<0.001)、MMP-9(p=0.0274)和 NGAL(p=0.0874)的曲线下面积分别为 0.763、0.645 和 0.609。包括 sLOX-1、MMP-9、WBC 计数和 CK-MB 峰值的新型组合判别模型的曲线下面积为 0.8431(p<0.001)。以 0.614 为截断点,斑块破裂的敏感性和特异性分别为 62.2%和 97.6%。与单一生物标志物相比,使用 sLOX-1、MMP-9、WBC 计数和 CK-MB 峰值的新型判别模型能更好地识别 ACS 患者的斑块破裂。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2994/7677551/156bb7050aa2/41598_2020_77413_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2994/7677551/b320c8489b39/41598_2020_77413_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2994/7677551/2f23d3854a97/41598_2020_77413_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2994/7677551/a28c6046b2a1/41598_2020_77413_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2994/7677551/f5b96e52c83c/41598_2020_77413_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2994/7677551/156bb7050aa2/41598_2020_77413_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2994/7677551/b320c8489b39/41598_2020_77413_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2994/7677551/2f23d3854a97/41598_2020_77413_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2994/7677551/a28c6046b2a1/41598_2020_77413_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2994/7677551/f5b96e52c83c/41598_2020_77413_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2994/7677551/156bb7050aa2/41598_2020_77413_Fig5_HTML.jpg

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