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中华临床医师杂志(电子版) ›› 2025, Vol. 19 ›› Issue (09) : 642 -650. doi: 10.3877/cma.j.issn.1674-0785.2025.09.002

临床研究

社区中老年人群心踝血管指数纵向轨迹影响因素及与预后的相关性
温欢1, 苏博2, 刘金波1, 王宏宇1,()   
  1. 1 100144 北京,北京大学首钢医院血管医学中心
    2 100191 北京,北京大学第一医院临床药理研究所
  • 收稿日期:2025-09-27 出版日期:2025-09-30
  • 通信作者: 王宏宇
  • 基金资助:
    首都卫生发展科研专项(自主创新)(首发2020-2-6042); 临床重点项目建设项目(2019-Yuan-LC-01); 北京市石景山区血管医学重点专科项目(2020-2023)

Factors influencing longitudinal trajectory of cardio-ankle vascular index and its correlation with prognosis in middle-aged and elderly community populations

Huan Wen1, Bo Su2, Jinbo Liu1, Hongyu Wang1,()   

  1. 1 Vascular Medicine Center, Peking University Shougang Hospital, Beijing 100144, China
    2 Institute of Clinical Pharmacology, Peking University First Hospital, Beijing 100191, China
  • Received:2025-09-27 Published:2025-09-30
  • Corresponding author: Hongyu Wang
引用本文:

温欢, 苏博, 刘金波, 王宏宇. 社区中老年人群心踝血管指数纵向轨迹影响因素及与预后的相关性[J/OL]. 中华临床医师杂志(电子版), 2025, 19(09): 642-650.

Huan Wen, Bo Su, Jinbo Liu, Hongyu Wang. Factors influencing longitudinal trajectory of cardio-ankle vascular index and its correlation with prognosis in middle-aged and elderly community populations[J/OL]. Chinese Journal of Clinicians(Electronic Edition), 2025, 19(09): 642-650.

目的

探究社区中老年人群心踝血管指数(CAVI)纵向轨迹的影响因素,及其与新发主要不良心血管事件(MACEs)的关联,为动脉血管僵硬早期干预及心血管风险动态管理提供依据。

方法

选取北京市石景山区金顶街社区健康管理中心2020~2023年健康体检纵向数据管理队列中符合标准的受试者为研究对象,应用组轨迹模型(GBTM)构建CAVI变化轨迹模型并分组;采用重复测量方差分析描述模型特征,无序多分类Logistic回归分析不同轨迹组的影响因素,COX回归模型分析不同轨迹组与新发MACEs的关联。

结果

共纳入883名受试者,GBTM将CAVI纵向轨迹分为3组:低水平波动组(17.89%)、中水平波动组(62.85%)、高水平波动组(19.25%)。重复测量方差分析显示,不同时间点、不同组别的CAVI差异均有统计学意义(P<0.05)。无序多分类Logistic回归(以低水平波动组为参照)显示:高龄、高收缩压、高水平同型半胱氨酸(HCY)及血肌酐(Scr)、目前仍饮酒、患高脂血症者更易归入中水平波动组;高龄、男性、高收缩压、高水平空腹血糖(FBG)、HCY、血尿素氮(BUN)、Scr及糖化血红蛋白(HbA1c)、有吸烟史、目前仍饮酒、患高血压、糖尿病及高脂血症者更易归入高水平波动组。COX回归分析显示,与低水平波动组相比,中水平波动组(HR=9.71,95%CI:1.33~70.97,P=0.025)、高水平波动组(HR=18.33,95%CI:2.45~136.94,P=0.005)新发MACEs风险均显著升高。

结论

社区中老年人群CAVI纵向轨迹存在3种不同模式,不同轨迹组人群特征存在差异;CAVI中、高水平波动组均与新发MACEs风险增加相关,需针对高风险人群加强干预。

Objective

To explore the influencing factors of longitudinal trajectory of cardio-ankle vascular index (CAVI) in middle-aged and elderly community populations and its correlation with new-onset major adverse cardiovascular events (MACEs), so as to provide a basis for the early intervention of arterial stiffness and dynamic management of cardiovascular risk.

Methods

Eligible subjects were selected from the longitudinal data management cohort of health check-ups (2020~2023) at Jinding Street Community Health Management Center in Shijingshan District, Beijing. A group-based trajectory model (GBTM) was used to construct and classify CAVI change trajectory models. Repeated-measures analysis of variance was applied to describe the model characteristics; unordered multinomial Logistic regression was used to analyze the influencing factors of different trajectory groups; and Cox regression model was employed to explore the correlation between different trajectory groups and new-onset MACEs.

Results

A total of 883 subjects were included. GBTM classified the longitudinal trajectory of CAVI into three groups: low-level fluctuation group (17.89%), medium-level fluctuation group (62.85%), and high-level fluctuation group (19.25%). Repeated-measures analysis of variance showed that there were statistically significant differences in CAVI across different time points and different groups (P<0.05). Taking the low-level fluctuation group as the reference, unordered multinomial Logistic regression revealed that subjects with advanced age, high systolic blood pressure, high levels of homocysteine (HCY) and serum creatinine (Scr), current alcohol consumption, or hyperlipidemia were more likely to be classified into the medium-level fluctuation group, while subjects with advanced age, male gender, high systolic blood pressure, high levels of fasting blood glucose (FBG), HCY, blood urea nitrogen (BUN), Scr and glycated hemoglobin (HbA1c), smoking history, current alcohol consumption, hypertension, diabetes mellitus, or hyperlipidemia were more likely to be classified into the high-level fluctuation group. Cox regression analysis indicated that compared with the low-level fluctuation group, the risk of new-onset MACEs was significantly increased in the medium-level fluctuation group (hazard ratio [HR]=9.71, 95% confidence interval [CI]: 1.33~70.97, P=0.025) and the high-level fluctuation group (HR=18.33, 95%CI: 2.45~136.94, P=0.005).

Conclusion

There are three distinct patterns of CAVI longitudinal trajectory in middle-aged and elderly community populations, and the population characteristics differ among different trajectory groups. Both the medium-level and high-level CAVI fluctuation groups are associated with an increased risk of new-onset MACEs, so targeted intervention for high-risk populations should be strengthened.

表1 社区中老年CAVI纵向轨迹拟合过程中的相关参数
表2 社区中老年CAVI纵向轨迹的模型评价
表3 重复测量方差分析结果
图1 社区中老年人群CAVI纵向轨迹图 注:CAVI为心-踝血管指数
表4 社区中老年人群非MACEs组和MACEs组一般临床资料比较[MQ1Q3)]
项目 整体(883例) 非MACEs组(830例) MACEs组(53例) t/χ2/U P
年龄(岁) 61.0(57.0,65.0) 61.0(57.0,64.0) 65.0(60.0,67.0) 17.021 <0.001
性别[例(%)] 8.864 0.003
男性 286(32.4) 259(31.2) 27(50.9)
女性 597(67.6) 571(68.8) 26(49.1)
受教育程度[例(%)] 6.079 0.048
初中及以下学历 225(25.5) 204(24.6) 21(39.6)
高中或同等学历 430(48.7) 408(49.2) 22(41.5)
大学及以上学历 228(25.8) 218(26.3) 10(18.9)
吸烟状况[例(%)] Fisher 0.003
从不吸烟 664(75.2) 634(76.4) 30(56.6)
已戒烟 70(7.9) 62(7.5) 8(15.1)
目前仍吸烟 149(16.9) 134(16.1) 15(28.3)
饮酒状况[例(%)] Fisher 0.222
从不饮酒 633(71.7) 600(72.3) 33(62.3)
已戒酒 21(2.4) 20(2.4) 1(1.9)
目前仍饮酒 229(25.9) 210(25.3) 19(35.8)
BMI(kg/m2 24.6(22.6,7.0) 24.6(22.6,26.8) 26.0(23.1,27.6) 5.830 0.016
收缩压(mmHg) 124.5(114.5,136.0) 124.5(114.0,135.0) 133.5(124.5,142.5) 13.007 <0.001
舒张压(mmHg) 72.0(65.5,79.5) 72.2(65.5,79.5) 71.5(65.5,77.5) 0.221 0.639
TC(mmol/L) 5.2(4.6,5.9) 5.3(4.6,5.9) 4.9(4.1,5.5) 8.239 0.004
TG(mmol/L) 1.4(1.0,1.9) 1.4(1.0,1.9) 1.5(1.1,1.9) 0.063 0.802
FBG(mmol/L) 5.6(5.2,6.2) 5.6(5.2,6.1) 6.4(5.7,7.7) 20.445 <0.001
HDL-C(mmol/L) 1.4(1.2,1.6) 1.4(1.2,1.6) 1.3(1.2,1.4) 6.232 0.013
LDL-C(mmol/L) 2.8(2.3,3.4) 2.8(2.3,3.4) 2.6(2.1,3.1) 3.119 0.077
HbA1c(%) 5.5(5.2,6.1) 5.5(5.2,6.0) 5.9(5.3,6.8) 10.036 0.002
HCY(µmol/L) 10.4(8.7,12.6) 10.3(8.7,12.5) 11.5(9.3,13.3) 1.668 0.197
BUN(mmol/L) 5.0(4.2,5.9) 4.9(4.2,5.9) 5.2(4.3,6.1) 1.065 0.302
Scr(µmol/L) 64.0(56.0,74.0) 64.0(56.0,73.5) 68.9(60.6,78.0) 5.742 0.017
UA(µmol/L) 320.3(270.0,374.5) 319.0(268.0,368.6) 350.0(306.0,410.0) 7.792 0.005
高血压[例(%)] 20.876 <0.001
573(64.9) 554(66.7) 19(35.8)
310(35.1) 276(33.3) 34(64.2)
糖尿病[例(%)] 84.552 <0.001
736(83.4) 716(86.3) 20(37.7)
147(16.6) 114(13.7) 33(62.3)
高脂血症[例(%)] 5.505 0.019
519(58.8) 496(59.8) 23(43.4)
364(41.2) 334(40.2) 30(56.6)
服药状况[例(%)] 15.020 <0.001
624(70.7) 599(72.2) 25(47.2)
259(29.3) 231(27.8) 28(52.8)
CAVI波动状况[例(%)] 16.144 <0.001
低水平波动组 158(17.9) 157(18.9) 1(1.9)
中水平波动组 555(62.9) 522(62.9) 33(62.3)
高水平波动组 170(19.3) 151(18.2) 19(35.8)
表5 社区中老年人群CAVI轨迹与MACEs关联的COX回归分析
图2 社区中老年人群CAVI不同组别生存曲线
表6 社区中老年人群CAVI轨迹不同组别的一般临床资料比较[MQ1Q3)]
项目 低水平波动组(158例) 中水平波动组(555例) 高水平波动组(170例) F/χ2/H P
年龄(岁) 55.0(49.0,59.8) 61.0(58.0,64.0)a 65.0(62.0,66.0)ab 188.128 <0.001
性别[例(%)] 32.524 <0.001
男性 36(22.8) 165(29.7) 85(50.0)
女性 122(77.2) 390(70.3) 85(50.0)ab
受教育程度[例(%)] 19.974 <0.001
初中及以下学历 27(17.1) 143(25.8) 55(32.4)
高中或同等学历 71(44.9) 282(50.8) 77(45.3)
大学及以上学历 60(38.0) 130(23.4)a 38(22.4)a
吸烟状况[例(%)] 12.901 0.012
从不吸烟 129(81.6) 424(76.4) 111(65.3)
已戒烟 9(5.7) 42(7.6) 19(11.2)
目前仍吸烟 20(12.7) 89(16.0) 40(23.5)ab
饮酒状况[例(%)] Fisher 0.041
从不饮酒 127(80.4) 393(70.8) 113(66.5)
已戒酒 4(2.5) 13(2.3) 4(2.4)
目前仍饮酒 27(17.1) 149(26.8)a 53(31.2)a
BMI(kg/m2 25.1(22.9,28.5) 24.6(22.6,26.8)a 24.3(22.5,26.5)a 8.01 0.018
收缩压(mmHg) 119.5(109.5,130.0) 124.5(114.5,134.5)a 130.0(121.1,140.5)ab 35.398 <0.001
舒张压(mmHg) 72.0(65.0,79.4) 72.0(65.5,79.5) 72.5(65.5,78.5) 0.005 0.997
TC(mmol/L) 5.3(4.7,5.8) 5.3(4.6,6.0) 5.1(4.5,5.8) 3.098 0.212
TG(mmol/L) 1.3(0.9,2.0) 1.4(1.0,1.9) 1.4(1.0,2.0) 1.118 0.572
FBG(mmol/L) 5.4(5.1,6.0) 5.6(5.2,6.2) 5.9(5.3,6.8)ab 18.246 <0.001
HDL-C(mmol/L) 1.4(1.2,1.6) 1.4(1.2,1.6) 1.3(1.1,1.5)ab 8.95 0.011
LDL-C(mmol/L) 2.9(2.3,3.3) 2.8(2.3,3.5) 2.7(2.2,3.1)b 5.453 0.065
HbA1c(%) 5.4(5.0,5.9) 5.5(5.2,6.0) 5.8(5.3,6.3)ab 20.086 <0.001
HCY(µmol/L) 9.8(8.0,11.5) 10.3(8.8,12.7)a 11.1(9.1,13.4)ab 16.289 <0.001
BUN(mmol/L) 4.8(4.1,5.8) 4.9(4.2,5.8) 5.3(4.3,6.1)ab 12.304 0.002
Scr(µmol/L) 61.0(53.8,68.9) 64.0(56.4,73.5)a 69.0(59.6,81.0)ab 27.448 <0.001
UA(µmol/L) 311.0(266.5,364.5) 319.0(266.6,367.2) 338.0(283.9,384.8)ab 9.596 0.008
高血压[例(%)] 29.219 <0.001
116(73.4) 376(67.7) 81(47.6)
42(26.6) 179(32.3) 89(52.4)ab
糖尿病[例(%)] 23.302 <0.001
140(88.6) 475(85.6) 121(71.2)
18(11.4) 80(14.4) 49(28.8)ab
高脂血症[例(%)] 8.39 0.015
109(69.0) 312(56.2) 98(57.6)
49(31.0) 243(43.8)a 72(42.4)a
服药状况[例(%)] 24.393 <0.001
127(80.4) 401(72.3) 96(56.5)
31(19.6) 154(27.7)a 74(43.5)ab
MACEs[例(%)] 16.144 <0.001
157(99.4) 522(94.1) 151(88.8)
1(0.6) 33(5.9)a 19(11.2)ab
表7 社区中老年人群CAVI轨迹影响因素的多分类Logistic分析
项目 中水平波动组(对照组为低水平波动组) 高水平波动组(对照组为低水平波动组)
OR(95%CI) P OR(95%CI) P
年龄 1.17(1.13,1.21) <0.001 1.39(1.32,1.46) <0.001
性别(对照组=男性)
女性 0.70(0.46,1.06) 0.088 0.30(0.18,0.48) <0.001
BMI 0.93(0.89,0.98) 0.008 0.91(0.85,0.97) 0.003
收缩压 1.02(1.01,1.03) <0.001 1.05(1.03,1.06) <0.001
舒张压 1.00(0.98,1.02) 0.797 1.00(0.98,1.02) 0.879
TC 1.06(0.90,1.25) 0.499 0.89(0.72,1.09) 0.267
TG 1.01(0.84,1.21) 0.930 1.06(0.86,1.32) 0.568
FBG 1.07(0.91,1.26) 0.407 1.35(1.14,1.60) 0.001
HDL-C 0.95(0.54,1.66) 0.855 0.39(0.19,0.80) 0.010
LDL-C 1.18(0.94,1.49) 0.154 0.87(0.65,1.16) 0.331
HCY 1.08(1.02,1.14) 0.006 1.09(1.03,1.15) 0.004
BUN 1.07(0.92,1.23) 0.384 1.39(1.17,1.65) <0.001
Scr 1.02(1.01,1.03) 0.005 1.04(1.03,1.06) <0.001
HbA1c 1.11(0.89,1.39) 0.356 1.63(1.27,2.09) <0.001
吸烟状况(对照组=从不吸烟)
已戒烟 1.42(0.67,3.00) 0.357 2.45(1.07,5.64) 0.035
目前仍吸烟 1.35(0.80,2.29) 0.257 2.32(1.28,4.21) 0.005
饮酒状况(对照组=从不饮酒)
已戒酒 1.05(0.34,3.28) 0.933 1.12(0.27,4.60) 0.871
目前仍饮酒 1.78(1.13,2.81) 0.013 2.21(1.30,3.74) 0.003
高血压(对照组=否)
1.31(0.89,1.95) 0.175 3.03(1.91,4.83) <0.001
糖尿病(对照组=否)
1.31(0.76,2.26) 0.331 3.15(1.74,5.70) <0.001
高脂血症(对照组=否)
1.73(1.19,2.52) 0.004 1.63(1.04,2.57) 0.034
1
Chong B, Jayabaskaran J, Jauhari SM, et al. Global burden of cardiovascular diseases: projections from 2025 to 2050 [J]. Eur J Prev Cardiol, 2025, 32(11): 1001-1015.
2
国家心血管病中心, 中国心血管健康与疾病报告编写组. 中国心血管健康与疾病报告2024概要 [J].中国循环杂志, 2025, 40(6):521-559.
3
Limpijankit T, Vathesatogkit P, Matchariyakul D, et al. Cardio-ankle vascular index as a predictor of major adverse cardiovascular events in metabolic syndrome patients [J]. Clin Cardiol, 2021, 44(11): 1628-1635.
4
Sumin AN, Shcheglova AV, Barbarash OL. Dynamics of the state of arterial stiffness as a possible pathophysiological factor of unfavorable long-term prognosis in patients after coronary artery bypass grafting [J]. Biomedicines, 2024, 12(5):1018.
5
Kato A. Arterial stiffening and clinical outcomes in dialysis patients [J]. Pulse (Basel), 2015, 3(2): 89-97.
6
Liang L, Li C, Liu X, et al. Lifelong smoking status, weight gain, and subsequent risk of major adverse cardiovascular events: Long-term follow-up of a middle-aged Chinese population[J]. Obesity (Silver Spring), 2022, 30(3): 762-769.
7
Wang S, Zhang X, Keerman M, et al. Impact of the baseline insulin resistance surrogates and their longitudinal trajectories on cardiovascular disease (coronary heart disease and stroke): a prospective cohort study in rural China [J]. Front Endocrinol (Lausanne), 2023, 14: 1259062.
8
Hitsumoto T. Clinical usefulness of the cardio-Ankle vascular index as a predictor of primary cardiovascular events in patients with chronic kidney disease [J]. J Clin Med Res, 2018, 10(12): 883-890.
9
Kadoglou N, Moulakakis KG, Mantas G, et al. Novel biomarkers and imaging indices for the "Vulnerable Patient" with Carotid Stenosis: A single-center Study [J]. Biomolecules, 2023, 13(9): 1427.
10
Kiuchi S, Hisatake S, Dobashi S, et al. Role of vascular function in the prognosis of heart failure patients[J]. J Clin Med, 2024, 13(9): 2719.
11
Kirigaya J, Iwahashi N, Tahakashi H, et al. Impact of cardio-ankle vascular index on long-term outcome in patients with acute coronary syndrome [J]. J Atheroscler Thromb, 2020, 27(7): 657-668.
12
Okamoto Y, Miyoshi T, Ichikawa K, et al. Cardio-ankle vascular index as an arterial stiffness marker improves the prediction of cardiovascular events in patients without cardiovascular diseases [J]. J Cardiovasc Dev Dis, 2022, 9(11):368.
13
Gómez-Sánchez M, Patino-Alonso MC, Gómez-Sánchez L, et al. Reference values of arterial stiffness parameters and their association with cardiovascular risk factors in the Spanish population. The EVA Study [J]. Rev Esp Cardiol (Engl Ed), 2020, 73(1): 43-52.
14
Elosua-Bayés M, Martí-Lluch R, García-Gil MDM, et al. Association of classic cardiovascular risk factors and lifestyles with the cardio-ankle vascular index in a general mediterranean population [J]. Rev Esp Cardiol (Engl Ed), 2018, 71(6):458-465.
15
Soska V, Frantisova M, Dobsak P, et al. Cardio-ankle vascular index in subjects with dyslipidaemia and other cardiovascular risk factors [J]. J Atheroscler Thromb, 2013, 20(5):443-451.
16
王玲洁, 王瑷萍, 李朝军, 等. 心脏和血管健康技术创新研发策略专家共识(2024第一次报告,上海) [J/OL]. 中华临床医师杂志(电子版), 2025, 19(5): 323-336.
17
Leto G, Tartaglione L, Rotondi S, et al. Diastolic pressure and ACR are modifiable risk factors of arterial stiffness in T2DM without cardiovascular disease [J]. J Clin Endocrinol Metab, 2022, 107(9): e3857-e3865.
18
Ma J, Li Y, Yang X, et al. Signaling pathways in vascular function and hypertension: molecular mechanisms and therapeutic interventions [J]. Signal Transduct Target Ther, 2023, 8(1):168.
19
Zheng D, Liu J, Piao H, et al. ROS-triggered endothelial cell death mechanisms: Focus on pyroptosis, parthanatos, and ferroptosis [J]. Front Immunol, 2022, 13: 1039241.
20
Kim B, Zhao W, Tang SY, et al. Endothelial lipid droplets suppress eNOS to link high fat consumption to blood pressure elevation[J]. J Clin Invest, 2023, 133(24): e173160.
21
Lin Y, Gil CH, Banno K, et al. ABCG2-Expressing clonal repopulating endothelial cells serve to form and maintain blood vessels [J]. Circulation, 2024, 150(6):451-465.
22
Durgin BG, Straub AC. Redox control of vascular smooth muscle cell function and plasticity [J]. Lab Invest, 2018, 98(10): 1254-1262.
23
Lee GL, Wu JY, Tsai CS, et al. TLR4-activated MAPK-IL-6 axis regulates vascular smooth muscle cell function [J]. Int J Mol Sci, 2016, 17(9): 1394.
24
Xing M, Chen W, Ji Y, et al. SLC44A2-mediated phenotypic switch of vascular smooth muscle cells contributes to aortic aneurysm [J]. J Clin Invest, 2024, 134(16): e183527.
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