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Discover high-risk factor combinations using Bayesian network from cohort data of National Stoke Screening in China

机译:从中国国家斯托克筛查队列​​中的彼得安网络发现高风险因子组合

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摘要

Abstract Background In recent years, the increasing incidence and prevalence of stroke has brought a heavy economic burden on families and society in China. The Ministry of Health of the Peoples’ Republic of China initiated the national stroke screening and intervention program in 2011 for stroke prevention and control. In the screening, only those who have been classified to “potential high-risk” group in preliminary screening need further examination and physician confirmation to determine the risk level of stroke in rescreening. However, at the beginning of the program, the “potential high-risk” classification method in the preliminary screening are determined by experts based on their experience. The primary aim of this study is to study the causality of stroke and risk factors in middle-aged population using the cohort data, and to explore whether the stroke screening and intervention program should include more precise “potential high-risk” evaluation criteria for this age group in preliminary screening. Method We use the cohort data of screening between 2013 and 2017 in this study. After data cleaning, the cohort consists of 48,007 people aged from 40 to 59 who are free of stroke at baseline. We use Bayesian networks to develop models. Result The results show that the stroke incidence in middle-aged population with certain two risk factors is higher than some of that with three factors, which is in keeping with our previous study results. We can take the ratio of the stroke incidence with combinations of risk factors and incidence without any of the risk factors as a variable threshold. By adjusting the threshold, we can get precise stroke preliminary screening criteria to achieve a balance between economy and efficiency. Conclusion We find that the criteria used in preliminary screening are not reasonable enough. There is a need for national stroke screening and intervention program to further include some more important risk factors or combinations of two risk factors as classification criteria in the preliminary screening. The results of the study can directly guide stroke screening program in China to make the screening more accurate and efficient.
机译:近年来摘要背景,中风的发病率越来越多,在中国家庭和社会带来了沉重的经济负担。中华民国卫生部的卫生部在2011年启动了国家中风筛查和干预计划,用于预防和控制。在筛选中,只有被分类为“潜在高风险”组的人在初步筛查中需要进一步检查和医生确认,以确定重新筛选中风的风险水平。然而,在该计划的开始,初步筛选中的“潜在高风险”分类方法由专家根据其经验确定。本研究的主要目的是使用群组数据研究中年人口中风和危险因素的因果关系,并探讨中风筛查和干预计划是否应包括更精确的“潜在的高风险”评估标准初步筛查年龄组。方法我们在本研究中使用2013年和2017年之间的筛选队列数据。在数据清理后,队列由48,007人组成40至59岁,在基线上没有中风。我们使用贝叶斯网络开发模型。结果结果表明,带有某些两个风险因素的中年人口中的行程发病率高于其中三种因素,这是与我们以前的研究结果保持一致。我们可以将中风发病率的比例与风险因素的组合和发病率没有任何危险因素作为可变阈值。通过调整阈值,我们可以获得精确的笔画初步筛选标准,以实现经济与效率之间的平衡。结论我们发现初步筛查中使用的标准不够合理。需要国家中风筛查和干预计划,进一步包括一些更重要的风险因素或两个危险因素的组合,作为初步筛查中的分类标准。该研究的结果可以直接在中国指导中风筛查计划,使筛查更准确和高效。

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