1.中山大学公共卫生学院,广东 广州510080
2.中山大学孙逸仙纪念医院心内科, 广东 广州510120
吴育彬,第一作者,研究方向:营养与慢性病防治,E-mail:wuyb25@mail2.sysu.edu.cn
纸质出版日期:2024-01-20,
收稿日期:2023-11-03,
录用日期:2023-12-21
扫 描 看 全 文
吴育彬,陈志腾,吴茂雄等.估计葡萄糖处置率与冠状动脉狭窄严重程度关系的横断面研究[J].中山大学学报(医学科学版),2024,45(01):136-145.
WU Yubin,CHEN Zhiteng,WU Maoxiong,et al.Association of Estimated Glucose Disposal Rate With the Stenosis Severity of Coronary Artery Disease: A Cross-sectional Study[J].Journal of Sun Yat-sen University(Medical Sciences),2024,45(01):136-145.
吴育彬,陈志腾,吴茂雄等.估计葡萄糖处置率与冠状动脉狭窄严重程度关系的横断面研究[J].中山大学学报(医学科学版),2024,45(01):136-145. DOI: 10.13471/j.cnki.j.sun.yat-sen.univ(med.sci).20240004.010.
WU Yubin,CHEN Zhiteng,WU Maoxiong,et al.Association of Estimated Glucose Disposal Rate With the Stenosis Severity of Coronary Artery Disease: A Cross-sectional Study[J].Journal of Sun Yat-sen University(Medical Sciences),2024,45(01):136-145. DOI: 10.13471/j.cnki.j.sun.yat-sen.univ(med.sci).20240004.010.
目的
2
探讨估计葡萄糖处置率(eGDR)与冠心病(CAD)严重程度的关联。
方法
2
采用以医院为基础的横断面研究设计,纳入因疑似冠心病而接受冠状动脉造影检查的患者共1 258人(平均年龄:62(53~68)岁;男性占53.9%)。按照eGDR公式计算胰岛素抵抗水平(IR):eGDR =21.158 - [0.09×腰围(WC, cm)] - [3.407×高血压(hypertension, 是/否)] - [0.551×糖化血红蛋白(HbA1c, %)]。根据eGDR三分位数对研究对象进行分组。冠心病的严重程度由狭窄血管的数量决定: 无明显CAD组(所有冠脉狭窄均
<
50%,
n
=704),单支血管CAD组(只有一条受累的主要冠脉狭窄≥50%,
n
=205),多支血管CAD组 (两条或两条以上受累的主要冠脉存在狭窄≥50%,
n
=349);以无明显CAD作参照,采用多因素logistic回归模型分析eGDR与CAD严重程度之间的关联。采用限制性立方样条分析eGDR和CAD在整个eGDR范围内的线性关联。采用亚组分析评估不同糖尿病状态下eGDR和CAD严重程度之间的关联。受试者工作特征(ROC)曲线分析eGDR对提高CAD筛查模型的价值。
结果
2
eGDR降低与CAD严重程度的风险增加显著相关。(OR:2.79;95%CI:1.72~4.55;
P
<
0.001)。多因素logistic回归模型中,eGDR最低分位(T1)的个体患多支血管CAD的风险是eGDR最高分位(T3)的2.79倍。(OR:2.79;95%CI:1.72~4.55;
P
<
0.001)。限制性立方样条分析显示,eGDR与CAD以及多支血管CAD之间存在负线性关联(
P
-linearity
<
0.05)。在非糖尿病患者中,与参照组(T3)相比,T1组患CAD和多支血管CAD的风险显著增加,OR分别为1.42 (95% CI:1.00~2.01;
P
<
0.05)和1.86 (95%CI:1.21~2.86;
P
<
0.05)。而在糖尿病患者中未发现此关联有统计学意义(
P>
0.05)。ROC曲线分析,eGDR加入到CAD传统筛查模型中时,AUC、IDI、NRI的结果显示,模型对CAD和多支血管CAD的筛查有显著改善。
结论
2
eGDR与CAD及CAD严重程度呈负相关。eGDR作为一种无创且易于获取的非胰岛素测量指标,具有筛查大规模人群中CAD严重程度的潜在价值。
Objective
2
To investigate the association between estimated glucose disposal rate (eGDR) and the severity of coronary heart disease.
Methods
2
We conducted a hospital-based cross-sectional study that included 1258 patients (mean age: 62(53-68) years) who underwent coronary angiography for suspected coronary artery disease (53.9% were male). Insulin resistance level (IR) was calculated according to eGDR formula: eGDR = 21.158 - (0.09 × WC) - (3.407 × hypertension) - (0.551 × HbA1c) [hypertension (yes = 1 / no = 0), HbA1c = HbA1c (%)]. Subjects were grouped according to the eGDR quantile. CAD severity was determined by the number of narrowed vessels: no-obstructive CAD group (all coronary stenosis were
<
50%,
n
=704), Single-vessel CAD group (only one involved major coronary artery stenosis≥50%,
n
=205), Multi-vessel CAD group (two or more involved major coronary arteries stenosis≥50%,
n
=349); Multivariate logistic regression model was used to analyze the association between eGDR and CAD severity. The linear relationship between eGDR and CAD in the whole range of eGDR was analyzed using restricted cubic spline. Subgroup analyses were used to assess the association between eGDR and CAD severity in different diabetic states. Receiver operating characteristic (ROC) curve analysis were used to evaluate the value of eGDR in improving CAD recognition.
Results
2
A decrease in the eGDR index was significantly associated with an increased risk of CAD severity (OR: 2.79; 95%CI: 1.72~4.55;
P
<
0.001). In multivariate logistic regression models, individuals with the lowest quantile of eGDR (T1) were 2.79 times more likely to develop multi-vessel CAD than those with the highest quantile of eGDR (T3) (OR: 2.79; 95%CI: 1.72~4.55;
P
<
0.001). Multivariate restricted cubic spline analysis showed that eGDR was negatively associated with CAD and multi-vessel CAD (
P
-nonlinear
>
0.05). In non-diabetic patients, compared with the reference group (T3), the T1 group had a significantly increased risk of CAD (OR: 1.42; 95% CI: 1.00~2.01;
P
<
0.05) and multi-vessel CAD (OR: 1.86; 95%CI: 1.21~2.86;
P
<
0.05). No statistical association was found between eGDR and CAD in diabetic patients. In ROC curve analysis, when eGDR was added to traditional model for CAD, significant improvements were observed in the model's recognition of CAD and multi-vessel CAD.
Conclusion
2
Our study shows eGDR levels are inversely associated with CAD and CAD severity. eGDR, as a non-insulin measure to assess IR, could be a valuable indicator of CAD severity for population.
冠心病葡萄糖处置率冠心病严重程度多支血管病变冠心病冠状动脉狭窄横断面研究
coronary artery diseaseestimated glucose disposal ratestenosis severity of CADmulti-vessel coronary artery diseasecoronary artery stenosiscross-sectional study
The Writing Committee of the Report on Cardiovascular Health and Diseases in China. Report on cardiovascular health and diseases in China 2021: an updated summary [J]. Biomed Environ Sci, 2022, 35(7): 573-603.
Safiri S, Karamzad N, Singh K, et al. Burden of ischemic heart disease and its attributable risk factors in 204 countries and territories, 1990-2019 [J]. Eur J Prev Cardiol, 2022, 29(2): 420-431.
Hong S, Han K, Park CY. The triglyceride glucose index is a simple and low-cost marker associated with atherosclerotic cardiovascular disease: a population-based study [J]. BMC Med, 2020, 18(1): 361.
Thai PV, Tien HA, Van Minh H, et al. Triglyceride glucose index for the detection of asymptomatic coronary artery stenosis in patients with type 2 diabetes [J]. Cardiovasc Diabetol, 2020, 19(1): 137.
Tao LC, Xu JN, Wang TT, et al. Triglyceride-glucose index as a marker in cardiovascular diseases: landscape and limitations [J]. Cardiovasc Diabetol, 2022, 21(1): 68.
Williams KV, Erbey JR, Becker D, et al. Can clinical factors estimate insulin resistance in type 1 diabetes? [J]. Diabetes, 2000, 49(4): 626-632.
Zabala A, Darsalia V, Lind M, et al. Estimated glucose disposal rate and risk of stroke and mortality in type 2 diabetes: a nationwide cohort study [J]. Cardiovasc Diabetol, 2021, 20(1): 202.
O'Donnell MJ, Xavier D, Liu L, et al. Risk factors for ischaemic and intracerebral haemorrhagic stroke in 22 countries (the INTERSTROKE study): a case-control study [J]. Lancet, 2010, 376(9735): 112-123.
Epstein EJ, Osman JL, Cohen HW, et al. Use of the estimated glucose disposal rate as a measure of insulin resistance in an urban multiethnic population with type 1 diabetes [J]. Diabetes Care, 2013, 36(8): 2280-2285.
Komosinska-Vassev K, Gala O, Olczyk K, et al. The usefulness of diagnostic panels based on circulating adipocytokines/regulatory peptides, renal function tests, insulin resistance indicators and lipid-carbohydrate metabolism parameters in diagnosis and prognosis of type 2 diabetes mellitus with obesity [J]. Biomolecules, 2020, 10(9):1304.
Xuan J, Juan D, Yuyu N, et al. Impact of estimated glucose disposal rate for identifying prevalent ischemic heart disease: findings from a cross-sectional study [J]. BMC Cardiovasc Disord, 2022, 22(1): 378.
Ren X, Jiang M, Han L, et al. Estimated glucose disposal rate and risk of cardiovascular disease: evidence from the China Health and Retirement Longitudinal Study [J]. BMC Geriatr, 2022, 22(1): 968.
Liu MM, Peng J, Guo YL, et al. Impact of diabetes on coronary severity and cardiovascular outcomes in patients with heterozygous familial hypercholesterolaemia [J]. Eur J Prev Cardiol, 2022, 28(16): 1807-1816.
Su J, Li Z, Huang M, et al. Triglyceride glucose index for the detection of the severity of coronary artery disease in different glucose metabolic states in patients with coronary heart disease: a RCSCD-TCM study in China [J]. Cardiovasc Diabetol, 2022, 21(1): 96.
Reaven G. Insulin resistance and coronary heart disease in nondiabetic individuals [J]. Arterioscler Thromb Vasc Biol, 2012, 32(8): 1754-1759.
Levey AS, Stevens LA, Schmid CH, et al. A new equation to estimate glomerular filtration rate [J]. Ann Intern Med, 2009, 150(9): 604-612.
Virani SS, Newby LK, Arnold SV, et al. 2023 AHA/ACC/ACCP/ASPC/NLA/PCNA Guideline for the management of patients with chronic coronary disease: a report of the American Heart Association/American College of Cardiology Joint Committee on Clinical Practice Guidelines [J]. Circulation, 2023, 148(9): e9-e119.
Girgis CM, Scalley BD, Park KEJ. Utility of the estimated glucose disposal rate as a marker of microvascular complications in young adults with type 1 diabetes [J]. Diabetes Research and Clinical Practice, 2012, 96(3): e70-e72.
Meng C, Xing Y, Huo L, et al. Relationship Between Estimated Glucose Disposal Rate and Type 2 Diabetic Retinopathy [J]. Diabetes Metab Syndr Obes, 2023, 16: 807-818.
Liu C, Zhao Q, Zhao Z, et al. Correlation between estimated glucose disposal rate and in-stent restenosis following percutaneous coronary intervention in individuals with non-ST-segment elevation acute coronary syndrome [J]. Front Endocrinol (Lausanne), 2022, 13: 1033354.
Sorajja P, Gersh BJ, Cox DA, et al. Impact of multivessel disease on reperfusion success and clinical outcomes in patients undergoing primary percutaneous coronary intervention for acute myocardial infarction [J]. Eur Heart J, 2007, 28(14): 1709-1716.
骆诗韵, 叶咏欣, 陈霓璇, et al. 2018―2019年广东省城市居民慢性病前瞻性队列设计和基线特征 [J]. 中华疾病控制杂志, 2021, 25(9): 1060-1066.
Luo SY, Ye YX, Chen NX, et al. Prospective cohort of chronic diseases among urban residents in Guangdong Province: design and baseline characteristics of subjects from 2018 to 2019[J]. Chin J Dis Control Prev, 2021, 25(9): 1060-1066.
VanderWeele TJ, Ding P. Sensitivity analysis in observational research: introducing the E-value [J]. Ann Intern Med, 2017, 167(4): 268-274.
Sia CH, Ko J, Zheng H, et al. Association between smoking status and outcomes in myocardial infarction patients undergoing percutaneous coronary intervention [J]. Scientific Reports, 2021, 11(1): 6466.
Alloubani A, Nimer R, Samara R. Relationship between hyperlipidemia, cardiovascular disease and stroke: a systematic review [J]. Curr Cardiol Rev, 2021, 17(6): e051121189015.
Pansuria M, Xi H, Li L, et al. Insulin resistance, metabolic stress, and atherosclerosis [J]. Front Biosci (Schol Ed), 2012, 4(3): 916-931.
Cook NR. Use and misuse of the receiver operating characteristic curve in risk prediction [J]. Circulation, 2007, 115(7): 928-935.
Maddox TM, Stanislawski MA, Grunwald GK, et al. Nonobstructive coronary artery disease and risk of myocardial infarction [J]. JAMA, 2014, 312(17): 1754-1763.
Liu C, Liu X, Ma X, et al. Predictive worth of estimated glucose disposal rate: evaluation in patients with non-ST-segment elevation acute coronary syndrome and non-diabetic patients after percutaneous coronary intervention [J]. Diabetol Metab Syndr, 2022, 14(1): 145.
0
浏览量
4
下载量
0
CSCD
关联资源
相关文章
相关作者
相关机构