摘要：

目的 分析缺血性卒中相关代谢综合征及其成分，并探讨其对缺血性卒中的影响。 方法 分别记录和测量954 例缺血性卒中患者和768 例其他神经系统疾病患者性别、年龄、体重指数、腹围、血压（收缩压和舒张压）、血清甘油三酯、高密度脂蛋白胆固醇、空腹血糖、口服葡萄糖耐量试验（OGTT）2 h 后血糖和代谢综合征发生率，单因素和多因素后退法Logistic 回归分析探讨代谢综合征及其成分作为缺血性卒中的危险因素。 结果 缺血性卒中组患者年龄（t = 5.766，P = 0.000）、体重指数（t =2.320，P = 0.011）、女性腹围（t = 2.021，P = 0.020）、收缩压（t = 3.790，P = 0.000）、甘油三酯（t = 2.766，P =0.003）、空腹血糖（t = 3.391，P = 0.000）、OGTT 试验2 h 后血糖（t = 2.439，P = 0.008）高于对照组，高密度脂蛋白胆固醇低于对照组（t = 1.967，P = 0.024）；缺血性卒中组患者代谢综合征发生率高于对照组［61.01%（582/954）对21.88%（168/768）；χ2 = 44.168，P = 0.000］，且缺血性卒中组女性患者代谢综合征发生率高于男性［74.68%（354/474）对47.50%（228/480）；χ2 = 74.082，P = 0.000］。Logistic 回归分析显示，代谢综合征（OR = 5.122，95%CI：3.012 ~ 8.718；P = 0.000）以及年龄（OR = 1.040，95%CI：1.011 ~ 1.069；P = 0.007）、体重指数（OR = 2.465，95%CI：1.045 ~ 5.812；P = 0.018）、腹围（OR = 2.825，95%CI：1.359 ~ 5.878；P = 0.005）、血压（OR = 4.988，95%CI：2.416 ~ 10.297；P = 0.000）、甘油三酯（OR = 2.272，95%CI：1.161 ~ 4.449；P =0.017）、高密度脂蛋白胆固醇（OR = 2.510，95%CI：1.160 ~ 5.428；P = 0.019）、OGTT 试验2 h 后血糖（OR =4.040，95%CI：1.923 ~ 8.483；P = 0.000）、空腹血糖（OR = 3.193，95%CI：1.479 ~ 6.894；P = 0.003）是缺血性卒中的独立危险因素。 结论 代谢综合征及其成分均是缺血性卒中的独立危险因素，针对性地干预代谢综合征及其成分是预防和治疗缺血性卒中的重要措施。

关键词: 卒中, 脑缺血, 代谢疾病, 危险因素, 回归分析

Abstract:

Objective  To screen metabolic syndrome (MS) and its components in ischemic stroke, and to explore the effect of MS and its components on ischemic stroke.  Methods  A total of 954 patients with ischemic stroke (ischemic stroke group) and 768 patients with other nervous system diseases (control group) were enrolled in this study. Their sex, age, body mass index (BMI), abdominal girth, blood pressure [systolic blood pressure (SBP) and diastolic blood pressure (DBP), serum triglyceride (TG), high-density lipoprotein cholesterol (HDL?C), fasting blood glucose (FBG), blood glucose 2 h after oral glucose tolerance test (OGTT) and prevalence of MS were measured and recorded. Univariate and multivariate Logistic regression analysis were used to analyze and screen MS and its risk factors in ischemic stroke.  Results  Age (t = 5.766, P = 0.000), BMI (t = 2.320, P = 0.011), abdominal girth of female (t = 2.021, P = 0.020), SBP (t = 3.790, P = 0.000), TG (t = 2.766, P = 0.003), FBG (t = 3.391, P = 0.000), blood glucose 2 h after OGTT (t =2.439, P = 0.008) in ischemic stroke group were significantly higher than those in control group. HDL-C in ischemic stroke group was significantly lower than that in control group (t = 1.967, P = 0.024). Prevalence of MS in ischemic stroke group was significantly higher than that in control group [61.01% (582/954) vs. 21.88% (168/768); χ2 = 44.168, P = 0.000], and MS prevalence of female patients in ischemic stroke group was significantly higher than male [74.68% (354/474) vs. 47.50% (228/480); χ 2 = 74.082, P = 0.000]. Logistic regression analysis revealed that MS (OR = 5.122, 95% CI: 3.012-8.718; P = 0.000), age (OR = 1.040, 95%CI: 1.011-1.069; P = 0.007), BMI (OR = 2.465, 95%CI: 1.045- .812; P = 0.018), abdominal girth (OR = 2.825, 95% CI: 1.359-5.878; P = 0.005), blood pressure (OR = 4.988, 95% CI: 2.416-10.297; P = 0.000), TG (OR = 2.272, 95%CI: 1.161-4.449; P = 0.017), HDL?C (OR = 2.510, 95%CI: 1.160-5.428; P = 0.019), FBG (OR = 3.193, 95%CI: 1.479-6.894; P = 0.003) and blood glucose 2 h after OGTT (OR = 4.040, 95%CI: 1.923-8.483; P = 0.000) were independent risk factors for ischemic stroke.  Conclusions  MS and its components are independent risk factors for ischemic stroke. Targeted intervention for MS and its components is an important solution to prevent and treat ischemic stroke.

Key words: Stroke, Brain ischemia, Metabolic diseases, Risk factors, Regression analysis