基于HRA模型的健康体检人群脑卒中风险评估

发布时间：2018-08-21 11:48

【摘要】：目的:脑卒中(Stroke)又称脑血管意外或中风,是因脑血管阻塞或破裂引起的脑血流循环障碍和脑组织功能或结构损害为表现的急性脑血管疾病。它是全球第二大、中国第一大致死性病。在中国,脑卒中发病率逐渐攀升,已经成为我国严重的医学和公共卫生问题。为遏制脑卒中高发态势,我国已于2009年启动了“脑卒中筛查和防治工程”(CSSPP),旨在通过项目的实施,提高我国居民脑卒中危险因素知晓率、控制率,降低脑卒中的发生率、复发率、死亡率和致残率,从而减轻脑卒中给社会和家庭带来的经济负担和疾病负担,提高国民健康水平。该工程对年龄在40岁及以上的人群进行八大危险因素的筛查,若具有3项及以上危险因素者可列为脑卒中高危人群。目前该高危人群筛查策略的效力依旧未知,它仅仅通过对危险因素的个数进行计数来判断高危与否,并没有考虑到每个危险因素对于脑卒中发生的影响各不相同。为了更有效地评估个体脑卒中发生概率,本研究旨在在通过Meta分析这八种危险因素是否与脑卒中的发生相关联及其关联强度,探索基于健康风险评价模型(HRA)筛查脑卒中高危人群的策略,并与CSSPP筛查结果进行比较,为优化我国脑卒中高危人群筛查策略提供依据。方法:通过对CNKI知识网络服务平台,万方数据库以及PubMed数据库的检索,收集1990-2015年国内外发表的有关中国汉族人群脑卒中八种发病危险因素(包括高血压,糖尿病,心脏病,高血脂,脑卒中家族史,超重,吸烟及体育锻炼)的文献。本文用Nos量表对符合入选标准的文献进行质量评价,若评分大于5则纳入该文献。采用Reviewer manager 5.3以及Stata 12.0进行分析。健康风险评价模型(HRA)筛查高危人群策略是在对脑卒中8个危险因素进行荟萃分析基础上,获得各因素与脑卒中发生的合并效应值,再结合各年龄组脑卒中发病率,采用数学模型计算出个体未来5年脑卒中发病概率;应用ROC曲线计算高危人群发病概率的界值点,以此筛查出高危人群,并比较HRA和CSSPP两种筛查策略的结果。结果:本文共纳入了 178篇病例对照研究和15篇队列研究。我国筛查策略所纳入的八个危险因素中,高血压是最主要的脑卒中独立危险因素(OR=3.50,95%CI:3.18-3.85;RR=2.68,95%CI=2.20-3.26);糖尿病、心脏病、脑卒中家族史、高血脂、超重以及吸烟为发生脑卒中的中等关联强度的危险因素,其合并比值比介于1.82-2.68之间,合并危险度介于1.27-2.47之间;体育锻炼是防止脑卒中发生的保护因素(OR=0.49,95%CI:0.29-0.83),P值均小于0.05。亚组分析结果显示,高血脂与缺血性脑卒中发作有关,而与出血性脑卒中发作的关联分析无统计学意义;高血压和脑卒中家族史与出血性脑卒中发作的关联强度高于缺血性脑卒中组。应用HRA筛查策略评估了 4196名参加体检的个体。5年脑卒中发病平均概率为1.33‰,男性发病概率高于女性。5年脑卒中发病平均概率随危险因素的个数增多有上升趋势。按照CSSPP项目的筛查策略,可筛查出918名(21.9%)高危个体。按照HRA筛查策略,有219人的脑卒中发病平均概率超过高危界值(2.5%),但因其危险因素的个数不足3个,而被CSSPP项目的筛查策略判定为低危个体。但是,这些被CSSPP项目的筛查策略判定为低危者中有10.5%的个体有高血压,有9.4%的个体有糖尿病。结论:Meta结果分析显示不同危险因素对于脑卒中发作影响各不相同,我国目前仅计数危险因素的个数而不考虑其关联强度的脑卒中高危人群筛查策略可能会导致其筛查的效力有所降低。基于HRA模型的筛查策略可以定量评估个体脑卒中发病风险,综合考虑了各因素的影响。结合CSSPP项目筛查策略,HRA模型可能会改善脑卒中的筛查效果。值得注意的是,由于高血压和糖尿病是脑卒中的独立危险因素,因此应采取更多的措施来控制个体的血压和血糖。期望本研究将有助于提高脑卒中高危人群筛查的成本效果,有助于相关机构采取更为有效的干预措施。
[Abstract]:Objective: Stroke, also known as cerebrovascular accident or apoplexy, is an acute cerebrovascular disease characterized by cerebral blood flow disturbance caused by cerebral vascular obstruction or rupture and impairment of brain tissue function or structure. In order to curb the high incidence of stroke, China has launched the Stroke Screening and Prevention Project (CSSPP) in 2009, aiming to improve the awareness rate of stroke risk factors, control rate, reduce the incidence of stroke, recurrence rate, mortality and disability rate, thereby reducing the death rate of stroke in Chinese residents through the implementation of the project. The project screens people aged 40 years and over for eight major risk factors. Those with three or more risk factors can be classified as high-risk groups for stroke. The effectiveness of the screening strategy for high-risk groups is still unknown, and it only passes. Counting the number of risk factors does not take into account that each risk factor has a different impact on the incidence of stroke. To explore the strategy of screening high-risk population of stroke based on health risk assessment model (HRA), and to compare the results with the results of CSSPP screening, so as to provide the basis for optimizing the screening strategy of high-risk population of stroke in China. Methods: By searching CNKI knowledge network service platform, Wanfang database and PubMed database, collecting the published data from 1990 to 2015 at home and abroad. Literatures on eight risk factors for stroke in Chinese Han population (including hypertension, diabetes, heart disease, hyperlipidemia, family history of stroke, overweight, smoking and physical exercise) were evaluated by Nos scale. Literatures that met the inclusion criteria were included if the score was greater than 5. Reviewer manager 5.3 and Stata 12.0 analysis. Health Risk Assessment Model (HRA) screening strategy for high-risk population was based on meta-analysis of 8 risk factors for stroke, and combined with the incidence of stroke in each age group, the incidence of stroke in the next five years was calculated by mathematical model. Results: A total of 178 case-control studies and 15 cohort studies were included. Of the eight risk factors included in the screening strategy in China, hypertension was the most important independent risk factor for stroke. Factors (OR = 3.50, 95% CI: 3.18-3.85; RR = 2.68, 95% CI = 2.20-3.26); diabetes mellitus, heart disease, family history of stroke, hyperlipidemia, overweight and smoking were moderate risk factors for stroke. The combined ratio was between 1.82 and 2.68, and the combined risk was between 1.27 and 2.47; physical exercise was the insurance against stroke. Protective factors (OR = 0.49, 95% CI: 0.29-0.83), P values were all lower than 0.05. Subgroup analysis showed that hyperlipidemia was associated with ischemic stroke attack, but there was no significant correlation between hyperlipidemia and hemorrhagic stroke attack. The average 5-year stroke incidence rate in males was higher than that in females. The average 5-year stroke incidence rate increased with the number of risk factors. According to the CSSPP screening strategy, 918 (21.9%) high-risk individuals were screened. According to the HRA screening strategy, 219. The average incidence of stroke in humans exceeded the high-risk threshold (2.5%), but was judged as low-risk individuals by the screening strategy of CSSPP because the number of risk factors was less than three. However, 10.5% of the individuals identified as low-risk by the screening strategy of CSSPP had hypertension and 9.4% had diabetes. The results show that different risk factors have different effects on stroke onset. At present, the screening strategy for high-risk stroke patients who only count the number of risk factors without considering their correlation strength may reduce the effectiveness of screening. Considering the influence of various factors, the HRA model may improve the screening effect of stroke in combination with the CSSPP project screening strategy. It is worth noting that since hypertension and diabetes are independent risk factors for stroke, more measures should be taken to control individual blood pressure and glucose. It is hoped that this study will help to increase the risk of stroke. The cost effectiveness of crowd screening will help relevant institutions to take more effective intervention measures.
【学位授予单位】：天津医科大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：R743.3

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