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目的探讨老年累积高血压暴露与颈动脉内膜中层厚度(CIMT)的关系。方法观察对象由完成颈动脉超声检查≥60岁的开滦研究脑卒中队列1505人和老年队列2235人组成,其中两队列重叠人群266人,最终以血压和CIMT资料完整的3151人纳入统计分析。按累积高血压暴露时间(0、2、4、6年)将观察对象分成4组。采用Pearson相关和偏相关分析累积收缩压暴露值(cumSBP)与CIMT的相关性。采用逐步线性回归分析cumSBP与CIMT的线性关系,采用多因素Logistic回归模型分析累积高血压暴露与异常CIMT(CIMT≥1 mm)的关联。结果在纳入统计分析的观察对象3151人中,年龄(68.9±7.2)岁,男性2207人(70.0%)。累积高血压暴露0、2、4、6年组的CIMT值分别为(0.91±0.18)、(0.94±0.17)、(0.96±0.18)、(0.99±0.20)mm,相应的异常CIMT检出率分别为33.1%、40.1%、44.5%、52.8%。相关分析显示,cumSBP与CIMT值呈正相关(r=0.14,P<0.01)。校正混杂因素后的逐步线性回归分析显示,cumSBP与CIMT值呈线性正相关(B=0.017,P<0.001)。在多因素Logistic回归分析中,校正其他混杂因素后,结果发现累积高血压暴露4、6年组与累积高血压暴露0年组比,是异常CIMT的危险因素,OR值(95%CI)分别为1.337(1.013~1.763)、1.633(1.200~2.221)。结论 cumSBP与CIMT呈正相关,累积高血压暴露是异常CIMT的危险因素。
Objective To investigate the relationship between elderly cumulative hypertension and carotid artery intima-media thickness (CIMT). Methods Subjects consisted of 1505 stroke patients and 2235 senile patients who completed carotid ultrasonography ≥60 years of age. Among them, 266 patients overlapped with two cohorts, and 3151 persons with complete blood pressure and CIMT data were included in the statistical analysis. The subjects were divided into 4 groups according to the cumulative exposure time of hypertension (0, 2, 4, 6 years). Correlation between cumulative systolic blood pressure (cumSBP) and CIMT was analyzed using Pearson correlation and partial correlation analysis. The linear relationship between cumSBP and CIMT was analyzed by stepwise linear regression. The relationship between cumulative hypertension and abnormal CIMT (CIMT≥1 mm) was analyzed by multivariate Logistic regression model. Results Among the 3,151 observers enrolled in the statistical analysis, the age was (68.9 ± 7.2) years old and 2207 (70.0%) were male. The CIMT values at 0, 2, 4 and 6 years of cumulative hypertension were (0.91 ± 0.18), (0.94 ± 0.17), (0.96 ± 0.18) and (0.99 ± 0.20) mm, respectively Respectively 33.1%, 40.1%, 44.5% and 52.8%. Correlation analysis showed that there was a positive correlation between cumSBP and CIMT (r = 0.14, P <0.01). A stepwise linear regression analysis after adjusting for confounding factors showed a linear positive correlation between cumSBP and CIMT (B = 0.017, P <0.001). In the multivariate Logistic regression analysis, after adjusting for other confounding factors, it was found that the ratio of cumulative hypertension to 4-6-year cumulative hypertension and 0-year cumulative hypertension were risk factors for abnormal CIMT with OR (95% CI) 1.337 (1.013 to 1.763) and 1.633 (1.200 to 2.221). Conclusions The cumSBP is positively correlated with CIMT. Cumulative hypertension is a risk factor for abnormal CIMT.