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北京大学学报（医学版） ›› 2020, Vol. 52 ›› Issue (3): 514-520. doi: 10.19723/j.issn.1671-167X.2020.03.018

• 论著 • 上一篇    下一篇

血管健康指标对新发心脑血管事件的预测价值:北京血管健康分级标准的初步验证

刘欢1,2,何映东3,刘金波1,2,黄薇1,赵娜1,赵红薇1,周晓华2,3,△(),王宏宇1,2,△()   

  1. 1. 北京大学首钢医院血管医学科,北京 100144
    2. 北京大学医学部血管健康研究中心,北京 100191
    3. 北京大学生物统计系,北京国际数学研究中心,北京 100871
  • 收稿日期:2020-03-03 出版日期:2020-06-18 发布日期:2020-06-30
  • 通讯作者: 周晓华,王宏宇 E-mail:azhou@math.pku.edu.cn;dr.hongyuwang@foxmail.com
  • 基金资助:
    北京中医药科技发展资金(NQ2016-07);北京市卫生与健康科技成果和适宜技术推广项目(TG-2017-66);北京大学首钢医院院内基金(2017-hospital-clinical-01);北京大学首钢医院院内基金(SGYYZ201610);北京大学首钢医院院内基金(SGYYQ201605);北京市卫生局首都卫生发展科研专项(2011-4026-02);石景山科技计划项目

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

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摘要：

目的 探索血管健康指标(包括颈-股动脉脉搏波传导速度、颈-桡动脉脉搏波传导速度、心踝血管指数和踝臂指数)与冠状动脉粥样硬化性心脏病(简称冠心病)和脑梗塞的关系,初步评估北京血管健康分级的预测价值。方法 研究纳入2010—2017年首钢医院血管医学科至少有2次住院记录的受试者,排除基线时血管指标数据缺失且患有冠心病或脑梗塞的患者。建立两个队列,队列1(冠心病)入组467例受试者[平均年龄(63.4±12.3)岁,女性42.2%],队列2(脑梗塞)入组658例受试者[平均年龄(64.3±12.2)岁,女性48.7%],分别应用Cox比例风险回归建立冠心病或脑梗塞的预测模型。结果 队列1和队列2的中位随访时间分别为1.9年和2.1年,随访期间,队列1中有164例首发冠心病事件发生,队列2中有117例首发脑梗塞事件发生。将4种血管健康指标同时作为连续变量进行多变量调整分析,队列1中,4种指标均有统计学意义(P均<0.05);队列2中,仅心踝血管指数有统计学意义(P<0.05)。未调整模型中,北京血管健康分级对于冠心病和脑梗塞的预测价值均有统计学意义(P均<0.05),而在多变量调整模型中,北京血管健康分级仅对冠心病具有预测价值(P<0.05)。结论 不同的血管健康指标对于冠心病和脑梗塞的预测价值不同,其中心踝血管指数可能是一种较为稳定的指标。北京血管健康分级对于冠心病具有预测价值,而对于脑梗塞的预测价值还需进一步研究。

关键词: 心血管疾病, 危险因素, 队列研究, 北京血管健康分级

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

中图分类号: 

  • R541.4

图1

受试者入选流程图"

表1

简化的北京血管健康分级赋值"

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

表2

队列1人群和队列2人群的基线特点"

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

表3

队列1中4种血管健康指标分别对于冠心病风险的预测"

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

表4

队列2中4种血管健康指标分别对于脑梗塞风险的预测"

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

表5

队列1中4种血管健康指标同时对于冠心病风险的预测"

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

表6

队列2中4种血管健康指标同时对于脑梗塞风险的预测"

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

表7

简化的BVHS对于冠心病和脑梗塞的预测价值"

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
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ISSN 1671-167X
CN 11-4691/R
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