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应激性高血糖比值与N末端B型脑钠肽前体预测多支冠状动脉疾病糖尿病患者全因死亡率的相对及联合能力。

The relative and combined ability of stress hyperglycemia ratio and N-terminal pro-B-type natriuretic peptide to predict all-cause mortality in diabetic patients with multivessel coronary artery disease.

作者信息

Wang Le, Wang Chen, Lang Jia-Chun, Xu Rong-di, Cong Hong-Liang, Zhang Jing-Xia, Hu Yue-Cheng, Li Ting-Ting, Liu Chun-Wei, Yang Hua, Li Wen-Yu

机构信息

Department of Cardiology, Tianjin Chest Hospital, Tianjin University, 261 Tai'erzhuang Road, Jinnan District, Tianjin, 300222, China.

Department of Cardiology, Chest Hospital, Tianjin University, 261 Tai'erzhuang Road, Jinnan District, Tianjin, 300222, China.

出版信息

Cardiovasc Diabetol. 2024 Mar 11;23(1):93. doi: 10.1186/s12933-024-02186-2.

DOI:10.1186/s12933-024-02186-2
PMID:38468331
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10926680/
Abstract

BACKGROUND

Stress hyperglycemia ratio (SHR) and N-terminal pro-B-type natriuretic peptide (NT-proBNP) are independently associated with increased mortality risk in diabetic patients with coronary artery disease (CAD). However, the role of these biomarkers in patients with diabetes and multivessel disease (MVD) remains unknown. The present study aimed to assess the relative and combined abilities of these biomarkers to predict all-cause mortality in patients with diabetes and MVD.

METHODS

This study included 1148 diabetic patients with MVD who underwent coronary angiography at Tianjin Chest Hospital between January 2016 and December 2016. The patients were divided into four groups according to their SHR (SHR-L and SHR-H) and NT-proBNP (NT-proBNP-L and NT-proBNP-H) levels. The primary outcome was all-cause mortality. Multivariate Cox regression analyses were performed to evaluate the association of SHR and NT-proBNP levels with all-cause mortality.

RESULTS

During a mean 4.2 year follow-up, 138 patients died. Multivariate analysis showed that SHR and NT-proBNP were strong independent predictors of all-cause mortality in diabetic patients with MVD (SHR: HR hazard ratio [2.171; 95%CI 1.566-3.008; P < 0.001; NT-proBNP: HR: 1.005; 95%CI 1.001-1.009; P = 0.009). Compared to patients in the first (SHR-L and NT-proBNP-L) group, patients in the fourth (SHR-H and NT-proBNP-H) group had the highest mortality risk (HR: 12.244; 95%CI 5.828-25.721; P < 0.001). The areas under the curve were 0.615(SHR) and 0.699(NT-proBNP) for all-cause mortality. Adding either marker to the original models significantly improved the C-statistic and integrated discrimination improvement values (all P < 0.05). Moreover, combining SHR and NT-proBNP levels into the original model provided maximal prognostic information.

CONCLUSIONS

SHR and NT-proBNP independently and jointly predicted all-cause mortality in diabetic patients with MVD, suggesting that strategies to improve risk stratification in these patients should incorporate SHR and NT-porBNP into risk algorithms.

摘要

背景

应激性高血糖比率(SHR)和N端前脑钠肽(NT-proBNP)与糖尿病合并冠状动脉疾病(CAD)患者的死亡风险增加独立相关。然而,这些生物标志物在糖尿病合并多支血管病变(MVD)患者中的作用仍不清楚。本研究旨在评估这些生物标志物预测糖尿病合并MVD患者全因死亡率的相对能力和联合能力。

方法

本研究纳入了2016年1月至2016年12月在天津胸科医院接受冠状动脉造影的1148例糖尿病合并MVD患者。根据患者的SHR(SHR-L和SHR-H)和NT-proBNP(NT-proBNP-L和NT-proBNP-H)水平将患者分为四组。主要结局是全因死亡率。进行多变量Cox回归分析以评估SHR和NT-proBNP水平与全因死亡率的关联。

结果

在平均4.2年的随访期间,138例患者死亡。多变量分析显示,SHR和NT-proBNP是糖尿病合并MVD患者全因死亡率的强有力独立预测因子(SHR:风险比[HR] 2.171;95%置信区间[CI] 1.566 - 3.008;P < 0.001;NT-proBNP:HR:1.005;95%CI 1.001 - 1.009;P = 0.009)。与第一组(SHR-L和NT-proBNP-L)患者相比,第四组(SHR-H和NT-proBNP-H)患者的死亡风险最高(HR:12.244;95%CI 5.828 - 25.721;P < 0.001)。全因死亡率的曲线下面积分别为0.615(SHR)和0.699(NT-proBNP)。在原始模型中添加任何一种标志物均显著改善了C统计量和综合判别改善值(所有P < 0.05)。此外,将SHR和NT-proBNP水平纳入原始模型可提供最大的预后信息。

结论

SHR和NT-proBNP独立且联合预测糖尿病合并MVD患者的全因死亡率,这表明改善这些患者风险分层的策略应将SHR和NT-porBNP纳入风险算法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/730e/10926680/16b1037bfa92/12933_2024_2186_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/730e/10926680/7be50ffdd8f8/12933_2024_2186_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/730e/10926680/16b1037bfa92/12933_2024_2186_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/730e/10926680/7be50ffdd8f8/12933_2024_2186_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/730e/10926680/cd9e0f9f5721/12933_2024_2186_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/730e/10926680/c1a8339c2990/12933_2024_2186_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/730e/10926680/16b1037bfa92/12933_2024_2186_Fig4_HTML.jpg

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