Email Alert | RSS

Journal of Peking University (Health Sciences) ›› 2020, Vol. 52 ›› Issue (3): 514-520. doi: 10.19723/j.issn.1671-167X.2020.03.018

Previous Articles     Next Articles

Predictive value of vascular health indicators on newly cardiovascular events: Preliminary validation of Beijing vascular health stratification system

Huan LIU1,2,Ying-dong HE3,Jin-bo LIU1,2,Wei HUANG1,Na ZHAO1,Hong-wei ZHAO1,Xiao-hua ZHOU2,3,△(),Hong-yu WANG1,2,△()   

  1. 1. Vascular Medicine Center, Peking University Shougang Hospital, Beijing 100144, China
    2. Vascular Health Research Center of Peking University Health Science Center, Beijing 100191, China
    3. Department of Biostatistics, Peking University, Beijing International Center for Mathematical Research, Beijing 100871, China
  • Received:2020-03-03 Online:2020-06-18 Published:2020-06-30
  • Contact: Xiao-hua ZHOU,Hong-yu WANG E-mail:azhou@math.pku.edu.cn;dr.hongyuwang@foxmail.com
  • Supported by:
    Capital Project of Scientific and Technological Development of Traditional Chinese Medicine in Beijing(NQ2016-07);Beijing Health Scientific and Technological Achievements and Appropriate Technology Promotion Project(TG-2017-66);Key Clinical Projects in Peking University Shougang Hospital(2017-hospital-clinical-01);Key Clinical Projects in Peking University Shougang Hospital(SGYYZ201610);Key Clinical Projects in Peking University Shougang Hospital(SGYYQ201605);Capital Funds for Health Improvement and Research(2011-4026-02);Science and Technology Plan Project of Shijingshan District Committee of Science and Technology

RICH HTML

 7   

PDF (PC)

257

Abstract:

Objective: To explore the predictive value of carotid femoral artery pulse wave velocity (CF-PWV), carotid radial artery pulse wave velocity (CR-PWV), cardio-ankle vascular index (CAVI), and ankle brachial index (ABI) on coronary heart disease (CHD) and cerebral infarction (CI), and the preliminary validation of Beijing vascular health stratification (BVHS).Methods: Subjects with at least 2 in-patient records were included into the study between 2010 and 2017 from Vascular Medicine Center of Peking University Shougang Hospital. Subjects with CHD or CI, and without data of vascular function at baseline were excluded. Eventually, 467 subjects free of CHD [cohort 1, mean age: (63.4±12.3) years, female 42.2%] and 658 subjects free of CI [cohort 2, mean age: (64.3±12.2) years, female 48.7%] at baseline were included. The first in-patient records were as the baseline data, the second in-patient records were as a following-up data. Cox proportional hazard regression was used to establish the predictive models of CHD or CI derived from BVHS by multivariable-adjusted analysis.Results: The median follow-up time of cohort 1 and cohort 2 was 1.9 years and 2.1 years, respectively. During the follow-up, 164 first CHD events occurred in cohort 1 and 117 first CI events occurred in cohort 2. Four indicators were assessed as continuous variables simultaneously by multivariable-adjusted analysis. In cohort 1, CF-PWV, CR-PWV, ABI, and CAVI reached statistical significance in the multivariable-adjusted models (P<0.05). In cohort 2, only CAVI (P<0.05) was of statistical significance. In addition, the higher CF-PWV became a protector of CHD or CI (P<0.05). The prediction value of BVHS reached the statistical significance for CHD and CI in the unadjusted models (all P<0.05), however, BVHS could only predict the incidence of CHD (P<0.05), but not the incidence of CI (P>0.05) in the multivariable-adjusted models. CF-PWV, CR-PWV, ABI, and CAVI were associated factors of CHD independent of each other (P<0.05), only CAVI (P<0.05) was the risk factor of CI independent of the other three.Conclusion: The different vascular indicators might have different effect on CHD or CI. CAVI might be a stable predictor of both CHD and CI. Higher baseline CF-PWV was not necessarily a risk factor of CHD or CI because of proper vascular health management. BVHS was a potential factor for the prediction of CHD, and further research is needed to explore the prediction value for CI.

Key words: Cardiovascular disease, Risk factors, Cohort studies, Beijing vascular health stratification

CLC Number: 

  • R541.4

Figure 1

Flow diagram of subject inclusion process CHD, coronary heart disease; CI, cerebral infarction."

Table 1

Simplified BVHS system"

Artery stenosis Arterial stiffness Simplified BVHS
1 0 0
1 1
2 0 2
1 3
3 0 4
1 5
4 0 6
1 7

Table 2

Baseline characteristics of cohort 1 and cohort 2"

Variable Cohort 1
(n=467)		 Cohort 2
(n=658)
Age/years 63.4±12.3 64.3±12.2
Female/% 42.2 48.7
Body mass index/(kg/m2) 25.2±3.8 25.6±6.1
Heart rate/(beats/min) 70.3±11.6 71.7±42.6
Mean artery pressure/mmHg 101.8±11.9 101.6±14.5
Smoking/% 30.0 26.6
Drinking/% 27.0 23.1
Diabetes/% 23.3 29.7
Hypertension/% 62.7 64.6
Hyperlipidemia/% 57.8 64.2
Coronary heart disease
(baseline/endpoint)/%		 52.1/66.1
Cerebral infarction
(baseline/endpoint)/%		 32.8/41.8
CF-PWV/(m/s) 11.6±2.9 11.6±2.7
CR-PWV/(m/s) 9.2±1.7 9.1±1.8
CAVI 8.7±1.9 8.6±1.9
ABI 1.02±0.20 1.01±0.21
Median follow-up time/years 1.9 2.1
Number of events 164 117

Table 3

Risk of coronary heart disease event in cohort 1 in groups classified by four arterial health indicators (high vs. low) and per 1-SD increase in them"

Items Binary (high vs. low) Continuous (per 1-SD increase)
Unadjusted Multivariable-adjusted Unadjusted Multivariable-adjusted
CF-PWV
HR (95%CI) 0.82 (0.60-1.11) 0.68 (0.48-0.96) 0.92 (0.78-1.08) 0.65 (0.54-0.77)
P value 0.198 0.028 0.298 <0.001
CR-PWV
HR (95%CI) 0.64 (0.47-0.87) 0.70 (0.59-0.83) 0.70 (0.59-0.83) 0.64 (0.53-0.76)
P value 0.004 <0.001 <0.001 <0.001
ABI
HR (95%CI) 0.90 (0.66-1.23) 1.01 (0.73-1.41) 0.80 (0.70-0.91) 0.85 (0.73-1.00)
P value 0.526 0.946 <0.001 0.044
CAVI
HR (95%CI) 1.33 (0.97-1.81) 1.54 (1.09-2.18) 1.29 (1.12-1.49) 1.19 (0.99-1.43)
P value 0.075 0.014 <0.001 0.062

Table 4

Risk of cerebral infarction event in cohort 2 in groups classified by four arterial health indicators (high vs. low) and per 1-SD increase in them"

Items Binary (high vs. low) Continuous (per 1-SD increase)
Unadjusted Multivariable-adjusted Unadjusted Multivariable-adjusted
CF-PWV
HR (95%CI) 0.79 (0.55-1.14) 0.62 (0.42-0.91) 1.14 (0.95-1.36) 0.80 (0.66-0.97)
P value 0.209 0.016 0.159 0.025
CR-PWV
HR (95%CI) 0.95 (0.66-1.37) 0.75 (0.51-1.12) 0.87 (0.72-1.07) 0.90 (0.73-1.12)
P value 0.784 0.170 0.182 0.344
ABI
HR (95%CI) 0.97 (0.67-1.39) 1.01 (0.69-1.49) 0.86 (0.72-1.01) 1.04 (0.85-1.27)
P value 0.852 0.949 0.076 0.697
CAVI
HR (95%CI) 1.93 (1.32-2.83) 1.86 (1.27-2.80) 1.57 (1.36-1.81) 1.35 (1.12-1.64)
P value <0.001 0.003 <0.001 0.002

Table 5

Risk of coronary heart disease event in cohort 1 per 1-SD increase in four arterial health indicators"

Model Indicator HR (95%CI) P value
Unadjusted CF-PWV 0.82 (0.69-0.97) 0.023
CR-PWV 0.75 (0.63-0.88) <0.001
ABI 0.78 (0.67-0.90) <0.001
CAVI 1.42 (1.22-1.64) <0.001
Multivariable-adjusted CF-PWV 0.71 (0.59-0.86) <0.001
CR-PWV 0.70 (0.57-0.84) <0.001
ABI 0.84 (0.71-0.99) 0.042
CAVI 1.32 (1.11-1.58) 0.002

Table 6

Risk of cerebral infarction event in cohort 2 per 1-SD increase in four arterial health indicators"

Model Indicator HR (95%CI) P value
Unadjusted CF-PWV 1.04 (0.87-1.25) 0.639
CR-PWV 0.87 (0.72-1.06) 0.177
ABI 0.86 (0.72-1.03) 0.105
CAVI 1.55 (1.35-1.78) <0.001
Multivariable-adjusted CF-PWV 0.83 (0.69-1.00) 0.055
CR-PWV 0.92 (0.74-1.13) 0.417
ABI 0.99 (0.80-1.23) 0.947
CAVI 1.33 (1.11-1.60) 0.002

Table 7

Predictive value of simplified BVHS in prediction of coronary heart disease and cerebral infarction events"

Events Model HR (95%CI) P value
Coronary
heart disease		 Unadjusted 1.20 (1.13-1.27) <0.001
Multivariable-adjusted 1.17 (1.10-1.25) <0.001
Cerebral
infarction		 Unadjusted 1.20 (1.00-1.45) 0.048
Multivariable-adjusted 1.07 (0.87-1.32) 0.518
[1] Winsor T. Influence of arterial disease on the systolic blood pressure gradients of the extremity[J]. Am J Med Sci, 1950,220(2):117-126.
[2] Ohkuma T, Ninomiya T, Tomiyama H, et al. Ankle-brachial index measured by oscillometry is predictive for cardiovascular disease and premature death in the Japanese population: An individual participant data meta-analysis[J]. Atherosclerosis, 2018,275:141-148.
pmid: 29902702
[3] Heald CL, Fowkes FG, Murray GD, et al. Risk of mortality and cardiovascular disease associated with the ankle-brachial index: Systematic review[J]. Atherosclerosis, 2006,189(1):61-69.
[4] Zhong Q, Hu MJ, Cui YJ, et al. Carotid-femoral pulse wave velocity in the prediction of cardiovascular events and mortality: an updated systematic review and meta-analysis[J]. Angiology, 2018,69(7):617-629.
[5] Willum-Hansen T, Staessen JA, Torp-Pedersen C, et al. Prognostic value of aortic pulse wave velocity as index of arterial stiffness in the general population[J]. Circulation, 2006,113(5):664-670.
[6] Niiranen TJ, Kalesan B, Larson MG, et al. Aortic-brachial arte-rial stiffness gradient and cardiovascular risk in the community: the Framingham Heart Study[J]. Hypertension, 2017,69(6):1022-1028.
pmid: 28396534
[7] Mitchell GF, Hwang SJ, Vasan RS, et al. Arterial stiffness and cardiovascular events: the Framingham Heart Study[J]. Circulation, 2010,121(4):505-511.
[8] Tillin T, Chambers J, Malik I, et al. Measurement of pulse wave velocity: site matters[J]. J Hypertens, 2007,25(2):383-389.
pmid: 17211245
[9] Shirai K, Utino J, Otsuka K, et al. A novel blood pressure-independent arterial wall stiffness parameter; cardio-ankle vascular index (CAVI)[J]. J Atheroscler Thromb, 2006,13(2):101-107.
[10] Laucevišius A, Ryliškytè L, Balsytè J, et al. Association of cardio-ankle vascular index with cardiovascular risk factors and cardiovascular events in metabolic syndrome patients[J]. Medicina (Kaunas), 2015,51(3):152-158.
[11] Matsushita K, Ding N, Kim ED, et al. Cardio-ankle vascular index and cardiovascular disease: Systematic review and meta-analysis of prospective and cross-sectional studies[J]. J Clin Hypertens (Greenwich), 2019,21(1):16-24.
[12] Sato Y, Nagayama D, Saiki A, et al. Cardio-ankle vascular index is independently associated with future cardiovascular events in outpatients with metabolic disorders[J]. J Atheroscler Thromb, 2016,23(5):596-605.
[13] Satoh-Asahara N, Kotani K, Yamakage H, et al. Cardio-ankle vascular index predicts for the incidence of cardiovascular events in obese patients: a multicenter prospective cohort study (Japan Obesity and Metabolic Syndrome Study: JOMS)[J]. Atherosclerosis, 2015,242(2):461-468.
[14] Vallée A, Petruescu L, Kretz S, et al. Added value of aortic pulse wave velocity index in a predictive diagnosis decision tree of coronary heart disease[J]. Am J Hypertens, 2019,32(4):375-383.
pmid: 30624553
[15] Velescu A, Clara A, Peñafiel J, et al. Adding low ankle brachial index to classical risk factors improves the prediction of major cardiovascular events. The REGICOR study[J]. Atherosclerosis, 2015,241(2):357-363.
pmid: 26071658
[16] Gronewold J, Hermann DM, Lehmann N, et al. Ankle-brachial index predicts stroke in the general population in addition to classical risk factors[J]. Atherosclerosis, 2014,233(2):545-550.
pmid: 24530962
[17] 中国医药教育协会血管医学专业委员会, 中华医学会北京心血管病学分会血管专业学组, 北京大学医学部血管疾病社区防治中心. 中国血管健康评估系统应用指南[J]. 中华医学杂志, 2018,98(37):2955-2967.
[18] 王宏宇, 刘欢. 新的血管健康分级标准与血管医学[J]. 心血管病学进展, 2015,36(4):365-368.
[19] Liu H, Liu J, Zhao H, et al. The design and rationale of the Beijing Vascular Disease Patients Evaluation Study (BEST study)[J]. Contemp Clin Trials Commun, 2017,7:18-22.
[20] Hong JB, Leonards CO, Endres M, et al. Ankle-brachial index and recurrent stroke risk: meta-analysis[J]. Stroke, 2016,47(2):317-322.
doi: 10.1161/STROKEAHA.115.011321 pmid: 26658450
[1] SU Jun-qi,SONG Yang,XIE Shang. Analysis of etiological characteristics and establishment of prediction model of postoperative infections in patients undergoing oral squamous cell carcinoma surgery with free flap reconstruction [J]. Journal of Peking University (Health Sciences), 2022, 54(1): 68-76.
[2] Hao XU,Guo-dong ZHANG,Guang-pu FAN,Yu CHEN. Preoperative plasma predictive factors of new-onset atrial fibrillation after coronary artery bypass graft surgery: A propensity score matching study [J]. Journal of Peking University (Health Sciences), 2021, 53(6): 1139-1143.
[3] Zhan-yue NIU,Yan XUE,Jing ZHANG,He-jun ZHANG,Shi-gang DING. Analysis of endoscopic and pathological features of gastric adenomatous polyps and risk factors for canceration [J]. Journal of Peking University (Health Sciences), 2021, 53(6): 1122-1127.
[4] Jing-xian ZHU,Sheng-nan LU,Yan-fang JIANG,Ling JIANG,Jian-quan WANG. Influencing factors of preoperative pulmonary function in elderly patients undergoing rotator cuff surgery [J]. Journal of Peking University (Health Sciences), 2021, 53(5): 902-906.
[5] WANG Jia-wen,LIU Jing-chao,MENG Ling-feng,ZHANG Wei,LIU Xiao-dong,ZHANG Yao-guang. Quality of life and related factors in patients with interstitial cystitis/bladder pain syndrome [J]. Journal of Peking University (Health Sciences), 2021, 53(4): 653-658.
[6] SUN Zheng-hui,HUANG Xiao-juan,DONG Jing-han,LIU Zhuo,YAN Ye,LIU Cheng,MA Lu-lin. Risk factors of renal sinus invasion in clinical T1 renal cell carcinoma patients undergoing nephrectomy [J]. Journal of Peking University (Health Sciences), 2021, 53(4): 659-664.
[7] GUO Zi-ning, LIANG Zhi-sheng, ZHOU Yi, ZHANG Na, HUANG Jie. Genetic study of cardiovascular disease subtypes defined by International Classification of Diseases [J]. Journal of Peking University (Health Sciences), 2021, 53(3): 453-459.
[8] LIU Qiu-ping,CHEN Xi-jin,WANG Jia-min,LIU Xiao-fei,SI Ya-qin,LIANG Jing-yuan,SHEN Peng,LIN Hong-bo,TANG Xun,GAO Pei. Effectiveness of different screening strategies for cardiovascular diseases prevention in a community-based Chinese population: A decision-analytic Markov model [J]. Journal of Peking University (Health Sciences), 2021, 53(3): 460-466.
[9] ZHOU Bo-lin,LI Wei-shi,SUN Chui-guo,QI Qiang,CHEN Zhong-qiang,ZENG Yan. Risk factors for multiple debridements of the patients with deep incisional surgical site infection after spinal surgery [J]. Journal of Peking University (Health Sciences), 2021, 53(2): 286-292.
[10] XIA Fang-fang,LU Fu-ai,LV Hui-min,YANG Guo-an,LIU Yuan. Clinical characteristics and related factors of systemic lupus erythematosus with interstitial pneumonia [J]. Journal of Peking University (Health Sciences), 2021, 53(2): 266-272.
[11] LIU Xiao-qiang,YANG Yang,ZHOU Jian-feng,LIU Jian-zhang,TAN Jian-guo. Blood pressure and heart rate changes of 640 single dental implant surgeries [J]. Journal of Peking University (Health Sciences), 2021, 53(2): 390-395.
[12] HOU Guo-jin,ZHOU Fang,TIAN Yun,JI Hong-quan,ZHANG Zhi-shan,GUO Yan,LV Yang,YANG Zhong-wei,ZHANG Ya-wen. Risk factors of recurrent kyphosis in thoracolumbar burst fracture patients treated by short segmental pedicle screw fixation [J]. Journal of Peking University (Health Sciences), 2021, 53(1): 167-174.
[13] MENG Zhao-ting,MU Dong-liang. Impact of oliguria during lung surgery on postoperative acute kidney injury [J]. Journal of Peking University (Health Sciences), 2021, 53(1): 188-194.
[14] WANG Ying-chun,HUANG Yong-hui,CHANG Hong,YAO Wei,YAN Xiu-e,LI Ke,ZHANG Yao-peng,ZHENG Wei. Characteristics of benign and malignant lesions of ampullary polyps and the accuracy of forceps biopsy [J]. Journal of Peking University (Health Sciences), 2021, 53(1): 204-209.
[15] Jia-li CHEN,Yue-bo JIN,Yi-fan WANG,Xiao-ying ZHANG,Jing LI,Hai-hong YAO,Jing HE,Chun LI. Clinical characteristics and risk factors of cardiovascular disease in patients with elderly-onset rheumatoid arthritis: A large cross-sectional clinical study [J]. Journal of Peking University (Health Sciences), 2020, 52(6): 1040-1047.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
[1] . [J]. Journal of Peking University(Health Sciences), 2009, 41(2): 188 -191 .
[2] . [J]. Journal of Peking University(Health Sciences), 2009, 41(3): 376 -379 .
[3] . [J]. Journal of Peking University(Health Sciences), 2009, 41(4): 459 -462 .
[4] . [J]. Journal of Peking University(Health Sciences), 2010, 42(1): 82 -84 .
[5] . [J]. Journal of Peking University(Health Sciences), 2007, 39(3): 319 -322 .
[6] . [J]. Journal of Peking University(Health Sciences), 2007, 39(3): 333 -336 .
[7] . [J]. Journal of Peking University(Health Sciences), 2007, 39(3): 337 -340 .
[8] . [J]. Journal of Peking University(Health Sciences), 2007, 39(4): 346 -350 .
[9] . [J]. Journal of Peking University(Health Sciences), 2007, 39(4): 361 -364 .
[10] . [J]. Journal of Peking University(Health Sciences), 2007, 39(4): 377 -380 .
Copyright © Journal of Peking University (Health Sciences), All Rights Reserved.
Powered by Beijing Magtech Co. Ltd