NLR、PLR及MLR与2型糖尿病合并冠心病患者的相关性研究

doi:10.3969/j.issn.1004-583X.2023.11.006

摘要/Abstract

摘要：

目的探讨中性粒细胞/淋巴细胞比值(neutrophil-lymphocyte ratio, NLR)、血小板/淋巴细胞比值(platelet-lymphocyte ratio, PLR)及单核细胞/淋巴细胞比值(monocyte-lymphocyte ratio, MLR)与2型糖尿病(diabetes mellitus type2, T2DM)合并冠心病(coronary heart disease, CHD)患者冠状动脉病变严重程度的相关性。方法收集2019年1月至2021年12月于威海市中心医院住院并行冠状动脉造影检查的T2DM患者517例,根据冠状动脉造影结果分为单纯T2DM组161例和T2DM合并CHD组356例,比较两组一般资料及实验室检查指标。依据冠状动脉造影结果,计算出Gensini积分,将T2DM合并CHD组分为低危亚组(Gensini积分<16)151例、中危亚组(16≤Gensini积分<40)97例及高危亚组(Gensini积分≥40)108例,比较各亚组一般资料及实验室检查指标,Spearman相关性分析评估NLR、PLR、MLR与患者Gensini积分的相关性,采用logistic回归分析探讨T2DM合并CHD患者冠状动脉病变严重程度的影响因素。结果 T2DM合并CHD组与单纯T2DM组性别构成比、年龄、低密度脂蛋白、低密度脂蛋白/高密度脂蛋白、糖化血红蛋白、尿素氮、肌酐、胱抑素及NLR、PLR、MLR水平差异均有统计学意义( $P$ <0.05)。高危亚组年龄、胱抑素及NLR、PLR、MLR水平显著高于低危亚组和中危亚组,差异有统计学意义( $P$ <0.05)。Spearman相关性分析显示,NLR、PLR、MLR与患者Gensini积分呈正相关( $r s$ =0.393, $P$ <0.01; $r s$ =0.322, $P$ <0.01; $r s$ =0.360, $P$ <0.01)。有序多分类logistic回归分析提示年龄、性别、舒张压、身体质量指数、肌酐以及NLR、PLR是T2DM合并CHD患者冠状动脉病变严重程度的独立影响因素( $P$ <0.05)。结论 NLR、PLR、MLR与T2DM合并CHD患者的Gensini积分呈正相关,NLR、PLR可作为T2DM合并CHD患者冠脉病变严重程度的独立预测因子。监测NLR、PLR有利于早期识别T2DM合并CHD患者冠脉病变的严重程度,预防急性冠脉综合征事件发生。

关键词: 糖尿病, 2型, 冠心病, Gensini积分, NLR, PLR, MLR

Abstract:

Objective To investigate the correlation of neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR) and monocyte-lymphocyte ratio (MLR) with the severity of coronary artery disease in patients with type 2 diabetes mellitus (T2DM) complicated with coronary heart disease (CHD). Methods A total of 517 T2DM patients who underwent coronary angiography (CAG) in Weihai Central Hospital from January 2019 to December 2021 were divided into T2DM group ( $n$ =161) and T2DM + CHD group ( $n$ =356) according to the CAG findings of CHD or not. The general data and laboratory examination indexes of the two groups were compared. According to the results of CAG, Gensini scores were calculated. Patients in T2DM+CHD group were further divided into low-risk subgroup (Gensini score<16, $n$ =151), medium-risk subgroup (16≤Gensini score <40, $n$ =97) and high-risk subgroup (Gensini score≥40, $n$ =108). The general data and laboratory examination indexes of patients in each subgroup were compared. Spearman correlation analysis was used to evaluate the correlation of NLR, PLR and MLR with the Gensini scores. Logistic regression analysis was used to explore the risk factors for the severity of coronary artery disease in T2DM patients complicated with CHD. Results There were significant differences in sex constituent ratio, age, low density lipoprotein (LDL), LDL/high density lipoprotein (HDL), glycosylated hemoglobin (HbA₁c), urea nitrogen, creatinine, cystatin, NLR, PLR and MLR between T2DM group and T2DM+CHD group. The levels of age, cystatin, NLR, PLR and MLR in the high-risk subgroup were significantly higher in those of the low-risk and medium-risk subgroups ( $P$ <0.05). Spearman correlation analysis showed that NLR, PLR and MLR were positively correlated with the Gensini scores ( $r s$ =0.393, $P$ <0.01; $r s$ =0.322, $P$ <0.01; $r s$ =0.360, $P$ <0.01). Ordered multivariate logistic regression analysis showed that age, sex, diastolic blood pressure, body mass index, creatinine, NLR and PLR were independent factors for the severity of coronary artery disease in T2DM patients complicated with CHD ( $P$ <0.05). Conclusion NLR, PLR and MLR are positively correlated with the Gensini score of T2DM patients complicated with CHD. NLR and PLR can be used as independent predictors of the severity of coronary artery disease in them. Monitoring NLR and PLR is helpful to early identify the severity of coronary artery disease in T2DM patients complicated with CHD and prevent the occurrence of acute coronary syndrome.

Key words: diabetes mellitus, type 2, coronary heart disease, Gensini score, NLR, PLR, MLR

中图分类号:

R587.1

师佩华, 林彦琳, 毕丽妨. NLR、PLR及MLR与2型糖尿病合并冠心病患者的相关性研究[J]. 临床荟萃, 2023, 38(11): 996-1001.

Shi Peihua, Lin Yanlin, Bi Lifang. Study on the correlation of NLR, PLR and MLR with type 2 diabetes mellitus complicated with coronary heart disease[J]. Clinical Focus, 2023, 38(11): 996-1001.

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链接本文: https://huicui.hebmu.edu.cn/CN/10.3969/j.issn.1004-583X.2023.11.006

https://huicui.hebmu.edu.cn/CN/Y2023/V38/I11/996

图/表 6

表1 两组一般资料、生化指标、及NLR、PLR、MLR比较

Tab. 1 Comparison of general data, biochemical indexes, NLR, PLR, MLR between the two groups

指标	单纯T2DM组( $n$ =161)	T2DM合并CHD组( $n$ =356)	χ²/ $Z$ / $t$ 值	$P$ 值
男性[例(%)]	49(21.2)	182(78.8)	18.760	<0.01
年龄(岁)	60.79±8.17	65.35±8.60	5.658	<0.01
SBP(mmHg)	142.67±18.74	145.52±22.03	1.511	0.132
DBP(mmHg)	82.31±11.67	83.67±12.52	1.165	0.245
BMI[kg/m²]	24.56(23.37, 26.57)	25.30(23.85, 26.67)	1.541	0.123
TC(mmol/L)	4.82±1.09	4.97±1.13	1.423	0.155
TG(mmol/L)	1.52(0.96, 2.31)	1.48(1.00, 2.17)	0.244	0.807
HDL-C(mmol/L)	1.15(0.98, 1.32)	1.13(0.92, 1.30)	1.448	0.148
LDL-C(mmol/L)	2.84(2.24, 3.38)	2.99(2.36, 3.70)	1.997	0.046
LDL-C/HDL-C	2.40(1.99, 3.10)	2.72(2.12, 3.45)	2.929	0.003
FBG(mmol/L)	7.46(5.81, 9.25)	7.00(5.83, 9.38)	0.787	0.431
HbA₁c(%)	6.80(6.30, 7.70)	7.30(6.60, 8.38)	3.618	<0.01
BUN(mmol/L)	5.90(5.00, 6.80)	6.20(5.13, 7.40)	2.185	0.029
Cr(μmol/L)	58.00(49.25, 65.00)	64.00(55.00, 77.00)	4.799	<0.01
UA(μmol/L)	328.00(274.25, 389.00)	331.00(284.00, 399.00)	1.082	0.279
CysC(mg/L)	0.88(0.80, 0.98)	0.94(0.86, 1.05)	4.236	<0.01
NLR	1.57(1.17, 1.93)	2.08(1.52, 2.77)	6.550	<0.01
PLR	101.94(84.15, 130.24)	114.34(92.46, 142.73)	3.571	<0.01
MLR	0.17(0.13, 0.21)	0.22(0.17, 0.28)	6.711	<0.01

表1 两组一般资料、生化指标、及NLR、PLR、MLR比较

Tab. 1 Comparison of general data, biochemical indexes, NLR, PLR, MLR between the two groups

指标	单纯T2DM组( $n$ =161)	T2DM合并CHD组( $n$ =356)	χ²/ $Z$ / $t$ 值	$P$ 值
男性[例(%)]	49(21.2)	182(78.8)	18.760	<0.01
年龄(岁)	60.79±8.17	65.35±8.60	5.658	<0.01
SBP(mmHg)	142.67±18.74	145.52±22.03	1.511	0.132
DBP(mmHg)	82.31±11.67	83.67±12.52	1.165	0.245
BMI[kg/m²]	24.56(23.37, 26.57)	25.30(23.85, 26.67)	1.541	0.123
TC(mmol/L)	4.82±1.09	4.97±1.13	1.423	0.155
TG(mmol/L)	1.52(0.96, 2.31)	1.48(1.00, 2.17)	0.244	0.807
HDL-C(mmol/L)	1.15(0.98, 1.32)	1.13(0.92, 1.30)	1.448	0.148
LDL-C(mmol/L)	2.84(2.24, 3.38)	2.99(2.36, 3.70)	1.997	0.046
LDL-C/HDL-C	2.40(1.99, 3.10)	2.72(2.12, 3.45)	2.929	0.003
FBG(mmol/L)	7.46(5.81, 9.25)	7.00(5.83, 9.38)	0.787	0.431
HbA₁c(%)	6.80(6.30, 7.70)	7.30(6.60, 8.38)	3.618	<0.01
BUN(mmol/L)	5.90(5.00, 6.80)	6.20(5.13, 7.40)	2.185	0.029
Cr(μmol/L)	58.00(49.25, 65.00)	64.00(55.00, 77.00)	4.799	<0.01
UA(μmol/L)	328.00(274.25, 389.00)	331.00(284.00, 399.00)	1.082	0.279
CysC(mg/L)	0.88(0.80, 0.98)	0.94(0.86, 1.05)	4.236	<0.01
NLR	1.57(1.17, 1.93)	2.08(1.52, 2.77)	6.550	<0.01
PLR	101.94(84.15, 130.24)	114.34(92.46, 142.73)	3.571	<0.01
MLR	0.17(0.13, 0.21)	0.22(0.17, 0.28)	6.711	<0.01

表2 3个亚组间一般资料、生化指标及NLR、PLR、MLR比较

Tab. 2 Comparison of general data, biochemical indexes, NLR, PLR, MLR between groups

指标	低危亚组( $n$ =151)	中危亚组( $n$ =97)	高危亚组( $n$ =108)
男性[例(%)]	63(41.7)	51(52.6)	68(63.0)^*
年龄(岁)	65(61.00, 69.00)	65(60.00, 69.50)	68(61.00, 75.00)^*#
SBP(mmHg)	146.93±18.94	147.94±24.97	141.42±22.83
DBP(mmHg)	85.17±12.38	84.91±13.53	80.49±11.23^*#
BMI(kg/m²)	25.03±2.74	25.27±1.72	25.76±1.96^*
TC(mmol/L)	4.69(3.88,, 5.60)	4.86(4.32, 5.64)	5.03(4.47, 5.82)^*
TG(mmol/L)	1.61(1.02, 2.22)	1.48(1.07, 2.25)	1.43(1.00, 2.02)
HDL-C(mmol/L)	1.11(0.91, 1.29)	1.14(0.98, 1.29)	1.14(0.90, 1.34)
LDL-C(mmol/L)	2.77(2.08, 3.58)	2.96(2.44, 3.71)	3.19(2.63, 3.80)^*
LDL-C/HDL-C	2.56(2.01, 3.38)	2.64(2.06, 3.45)	2.88(2.32, 3.76)^*
FBG(mmol/L)	7.08(5.97, 9.23)	6.46(5.54, 8.14)	7.50(5.70, 10.16)^#
HbA₁c(%)	7.30(6.70, 8.00)	7.30(6.45, 8.50)	7.40(6.53, 8.50)
BUN(mmol/L)	5.90(5.05, 7.10)	6.30(5.00, 7.35)	6.60(5.30, 8.10)
Cr(μmol/L)	59.00(51.00, 68.00)	67.00(58.00, 79.00)^*	69.00(57.00, 86.00)^*
UA(μmol/L)	316.50(275.00, 376.00)	335.00(300.50, 398.50)	349.00(297.50, 414.00)^*
CysC(mg/L)	0.89(0.81, 1.01)	0.94(0.86, 1.04)	0.99(0.93, 1.14)^*#
NLR	1.73(1.34, 2.38)	1.81(1.48, 2.72)	2.70(2.12, 3.72)^*#
PLR	103.21(83.14, 124.78)	111.22(88.52, 144.68)	136.14(109.18, 168.27)^*#
MLR	0.19(0.14, 0.24)	0.20(0.16, 0.29)	0.27(0.22, 0.34)^*#

表2 3个亚组间一般资料、生化指标及NLR、PLR、MLR比较

Tab. 2 Comparison of general data, biochemical indexes, NLR, PLR, MLR between groups

指标	低危亚组( $n$ =151)	中危亚组( $n$ =97)	高危亚组( $n$ =108)
男性[例(%)]	63(41.7)	51(52.6)	68(63.0)^*
年龄(岁)	65(61.00, 69.00)	65(60.00, 69.50)	68(61.00, 75.00)^*#
SBP(mmHg)	146.93±18.94	147.94±24.97	141.42±22.83
DBP(mmHg)	85.17±12.38	84.91±13.53	80.49±11.23^*#
BMI(kg/m²)	25.03±2.74	25.27±1.72	25.76±1.96^*
TC(mmol/L)	4.69(3.88,, 5.60)	4.86(4.32, 5.64)	5.03(4.47, 5.82)^*
TG(mmol/L)	1.61(1.02, 2.22)	1.48(1.07, 2.25)	1.43(1.00, 2.02)
HDL-C(mmol/L)	1.11(0.91, 1.29)	1.14(0.98, 1.29)	1.14(0.90, 1.34)
LDL-C(mmol/L)	2.77(2.08, 3.58)	2.96(2.44, 3.71)	3.19(2.63, 3.80)^*
LDL-C/HDL-C	2.56(2.01, 3.38)	2.64(2.06, 3.45)	2.88(2.32, 3.76)^*
FBG(mmol/L)	7.08(5.97, 9.23)	6.46(5.54, 8.14)	7.50(5.70, 10.16)^#
HbA₁c(%)	7.30(6.70, 8.00)	7.30(6.45, 8.50)	7.40(6.53, 8.50)
BUN(mmol/L)	5.90(5.05, 7.10)	6.30(5.00, 7.35)	6.60(5.30, 8.10)
Cr(μmol/L)	59.00(51.00, 68.00)	67.00(58.00, 79.00)^*	69.00(57.00, 86.00)^*
UA(μmol/L)	316.50(275.00, 376.00)	335.00(300.50, 398.50)	349.00(297.50, 414.00)^*
CysC(mg/L)	0.89(0.81, 1.01)	0.94(0.86, 1.04)	0.99(0.93, 1.14)^*#
NLR	1.73(1.34, 2.38)	1.81(1.48, 2.72)	2.70(2.12, 3.72)^*#
PLR	103.21(83.14, 124.78)	111.22(88.52, 144.68)	136.14(109.18, 168.27)^*#
MLR	0.19(0.14, 0.24)	0.20(0.16, 0.29)	0.27(0.22, 0.34)^*#

图1 NLR与T2DM合并CHD患者Gensini积分相关性散点图

Fig. 1 Scatter plot of correlation between NLR and Gensini scores in patients with T2DM complicated with CHD

图2 PLR与T2DM合并CHD患者Gensini积分相关性散点图

Fig. 2 Scatter plot of correlation between PLR and Gensini scores in patients with T2DM complicated with CHD

图3 MLR与T2DM合并CHD患者Gensini积分相关性散点图

Fig. 3 Scatter plot of correlation between MLR and Gensini scores in patients with T2DM complicated with CHD

表3 T2DM合并CHD患者冠状动脉病变程度影响因素的有序Logistic回归分析

Tab. 3 Ordered Logistic regression analysis of factors affecting the severity of coronary artery disease in patients with T2DM complicated with CHD

变量	B值	SE	Wald χ²值	$P$ 值	$O R$ 值	95% $C I$
变量	B值	SE	Wald χ²值	$P$ 值	$O R$ 值	下限	上限
性别	0.780	0.260	9.019	0.003	2.181	1.311	3.629
年龄	0.033	0.014	5.963	0.015	1.034	1.007	1.062
DBP	-0.023	0.009	6.768	0.009	0.977	0.961	0.994
BMI	0.133	0.049	7.402	0.007	1.142	1.038	1.257
TC	0.223	0.331	0.454	0.501	1.250	0.653	2.392
LDL-C	0.194	0.426	0.207	0.650	1.214	0.526	2.798
LDL-C/HDL-C	-0.096	0.163	0.345	0.557	0.909	0.660	1.251
UA	-0.001	0.001	0.170	0.680	0.999	0.997	1.002
Cr	0.017	0.006	7.037	0.008	1.017	1.004	1.029
NLR	0.286	0.136	4.402	0.036	1.331	1.019	1.739
PLR	0.013	0.004	12.057	0.001	1.013	1.006	1.020
MLR	-0.809	1.527	0.265	0.001	0.445	0.020	9.705

表3 T2DM合并CHD患者冠状动脉病变程度影响因素的有序Logistic回归分析

Tab. 3 Ordered Logistic regression analysis of factors affecting the severity of coronary artery disease in patients with T2DM complicated with CHD

变量	B值	SE	Wald χ²值	$P$ 值	$O R$ 值	95% $C I$
变量	B值	SE	Wald χ²值	$P$ 值	$O R$ 值	下限	上限
性别	0.780	0.260	9.019	0.003	2.181	1.311	3.629
年龄	0.033	0.014	5.963	0.015	1.034	1.007	1.062
DBP	-0.023	0.009	6.768	0.009	0.977	0.961	0.994
BMI	0.133	0.049	7.402	0.007	1.142	1.038	1.257
TC	0.223	0.331	0.454	0.501	1.250	0.653	2.392
LDL-C	0.194	0.426	0.207	0.650	1.214	0.526	2.798
LDL-C/HDL-C	-0.096	0.163	0.345	0.557	0.909	0.660	1.251
UA	-0.001	0.001	0.170	0.680	0.999	0.997	1.002
Cr	0.017	0.006	7.037	0.008	1.017	1.004	1.029
NLR	0.286	0.136	4.402	0.036	1.331	1.019	1.739
PLR	0.013	0.004	12.057	0.001	1.013	1.006	1.020
MLR	-0.809	1.527	0.265	0.001	0.445	0.020	9.705

参考文献 27

[1]	Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. Executive summary of the third report of the national cholesterol education program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (adult treatment panel III)[J]. JAMA, 2001, 285: 2486-2497. doi: 10.1001/jama.285.19.2486 URL
[2]	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. doi: 10.1186/s12933-022-01511-x
[3]	Gohari S, Reshadmanesh T, Khodabandehloo H, et al. The effect of empagliflozin on markers of inflammation in patients with concomitant type 2 diabetes mellitus and coronary artery disease: The EMPA-CARD randomized controlled trial[J]. Diabetol Metab Syndr, 2022, 14(1):170. doi: 10.1186/s13098-022-00951-5 pmid: 36397128
[4]	Mertoglu C, Gunay M. Neutrophil-lymphocyte ratio and platelet-lymphocyte ratio as useful predictive markers of prediabetes and diabetes mellitus[J]. Diabetes Metab Syndr, 2017, 11:S127-S131.
[5]	郭倩云, 冯逊逊, 杨佳奇, 等. 老年2型糖尿病中性粒细胞与淋巴细胞比值与冠心病相关性的研究[J]. 心肺血管病杂志, 2022, 41(6):597-601.
[6]	Qiu Z, Jiang Y, Jiang X, et al. Relationship between platelet to lymphocyte ratio and stable coronary artery disease: Meta-analysis of observational studies[J]. Angiology, 2020, 71(10):909-915. doi: 10.1177/0003319720943810 URL
[7]	郭姣姣, 龚开政. 中性粒细胞/淋巴细胞比值、血小板/淋巴细胞比值与2型糖尿病合并冠心病患者动脉粥样硬化程度的相关性[J]. 中华临床医师杂志(电子版), 2021, 15(3):171-176.
[8]	Qiao S, Gao W, Guo S. Neutrophil-lymphocyte ratio (NLR) for predicting clinical outcomes in patients with coronary artery disease and type 2 diabetes mellitus: A propensity score matching analysis[J]. Ther Clin Risk Manag, 2020, 16:437-443. doi: 10.2147/TCRM.S244623 URL
[9]	Urbanowicz T, Olasińska-Wi'sniewska A, Michalak M, et al. The prognostic significance of neutrophil to lymphocyte ratio (NLR), monocyte to lymphocyte ratio (MLR) and platelet to lymphocyte ratio (PLR) on long-term survival in off-pump coronary artery bypass grafting (OPCAB) procedures[J]. Biology (Basel), 2021, 11(1):34.
[10]	冯浠镰, 张伟, 杨柳柳. 单核细胞与淋巴细胞比值对重症患者病死率的预测意义[J]. 中国呼吸与危重监护杂志, 2022, 21(2):96-101.
[11]	Neeland IJ, Patel RS, Eshtehardi P, et al. Coronary angiographic scoring systems: An evaluation of their equivalence and validity[J]. Am Heart J, 2012, 164(4):547-552. doi: 10.1016/j.ahj.2012.07.007 pmid: 23067913
[12]	Rampidis GP, Benetos G, Benz DC, et al. A guide for gensini score calculation[J]. Atherosclerosis, 2019, 287:181-183. doi: S0021-9150(19)30417-4 pmid: 31104809
[13]	Sun H, Saeedi P, Karuranga S, et al. IDF diabetes atlas: Global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045[J]. Diabetes Res Clin Pract, 2022, 183:109119. doi: 10.1016/j.diabres.2021.109119 URL
[14]	Soehnlein O, Libby P. Targeting inflammation in atherosclerosisfrom experimental insights to the clinic[J]. Nat Rev Drug Discov, 2021, 20(8):589-610. doi: 10.1038/s41573-021-00198-1 pmid: 33976384
[15]	Gijsberts CM, Ellenbroek GHJM, Ten Berg MJ, et al. Effect of monocyte-to-lymphocyte ratio on heart failure characteristics and hospitalizations in a coronary angiography cohort[J]. Am J Cardiol, 2017, 120(6):911-916. doi: S0002-9149(17)31028-7 pmid: 28779870
[16]	Zhu Y, Xian X, Wang Z, et al. Research progress on the relationship between atherosclerosis and inflammation[J]. Biomolecules, 2018, 8(3):80. doi: 10.3390/biom8030080 URL
[17]	Zahorec R. Neutrophil-to-lymphocyte ratio, past, present and future perspectives[J]. Bratisl Lek Listy, 2021, 122(7):474-488. doi: 10.4149/BLL_2021_078 pmid: 34161115
[18]	Xiang F, Chen R, Cao X, et al. Monocyte/lymphocyte ratio as a better predictor of cardiovascular and all-cause mortality in hemodialysis patients: A prospective cohort study[J]. Hemodial Int, 2018, 22(1):82-92. doi: 10.1111/hdi.12549 pmid: 28403540
[19]	Li XT, Fang H, Li D, et al. Association of platelet to lymphocyte ratio with in-hospital major adverse cardiovascular events and the severity of coronary artery disease assessed by the Gensini score in patients with acute myocardial infarction[J]. Chin Med J (Engl), 2020, 133(4):415-423.
[20]	He J, Bian X, Song C, et al. High neutrophil to lymphocyte ratio with type 2 diabetes mellitus predicts poor prognosis in patients undergoing percutaneous coronary intervention: A large-scale cohort study[J]. Cardiovasc Diabetol, 2022, 21(1):156. doi: 10.1186/s12933-022-01583-9 pmid: 35964050
[21]	Hudzik B, Szkodzinski J, Gorol J, et al. Platelet-to-lymphocyte ratio is a marker of poor prognosis in patients with diabetes mellitus and ST-elevation myocardial infarction[J]. Biomark Med, 2015, 9(3):199-207. doi: 10.2217/bmm.14.100 pmid: 25731207
[22]	Ji H, Li Y, Fan Z, et al. Monocyte/lymphocyte ratio predicts the severity of coronary artery disease: A syntax score assessment[J]. BMC Cardiovasc Disord, 2017, 17(1):90. doi: 10.1186/s12872-017-0507-4 URL
[23]	刘逸翔, 范文俊, 丁振江, 等. WMR、MLR及两者联合对冠心病及冠状动脉病变严重程度的诊断价值[J]. 天津医药, 2022, 50(8):859-863.
[24]	马丽, 黄从新. 单核细胞/淋巴细胞比率与冠状动脉病变程度相关性的临床研究[J]. 心血管病学进展, 2020, 41(5):542-546.
[25]	Khurana R, Yadav A, Buxi TBS, et al. Correlation of epicardial fat quantification with severity of coronary artery disease: A study in Indian population[J]. Indian Heart J, 2018, 70 Suppl 3(Suppl 3):S140-S145.
[26]	丰庆春, 谭茗月, 李安莹. 冠状动脉粥样硬化病人血脂、尿素氮、血肌酐与冠脉病变的对比分析[J]. 医学临床研究, 2005, 22(5):647-648.
[27]	Bagheri B, Radmard N, Faghani-Makrani A, et al. Serum creatinine and occurrence and severity of coronary artery disease[J]. Med Arch, 2019, 73(3):154-156. doi: 10.5455/medarh.2019.73.154-156 pmid: 31404126