Department of Industrial Management, National Taiwan University of Science and Technology, Taipei 106, Taiwan.
Department of Rehabilitation Medicine, Mackay Memorial Hospital, Number 92, Section 2, Zhongshan North Road, Zhongshan District, Taipei City 10449, Taiwan.
Int J Environ Res Public Health. 2020 Mar 16;17(6):1944. doi: 10.3390/ijerph17061944.
Most stroke cases lead to serious mental and physical disabilities, such as dementia and sensory impairment. Chronic diseases are contributory risk factors for stroke. However, few studies considered the transition behaviors of stroke to dementia associated with chronic diseases and environmental risks.
This study aims to develop a prognosis model to address the issue of stroke transitioning to dementia associated with environmental risks.
This cohort study used the data from the National Health Insurance Research Database in Taiwan.
Healthcare data were obtained from more than 25 million enrollees and covered over 99% of Taiwan's entire population.
In this study, 10,627 stroke patients diagnosed from 2000 to 2010 in Taiwan were surveyed.
A Cox regression model and corresponding semi-Markov process were constructed to evaluate the influence of risk factors on stroke, corresponding dementia, and their transition behaviors.
Relative risk and sojourn time were the main outcome measure.
Multivariate analysis showed that certain environmental risks, medication, and rehabilitation factors highly influenced the transition of stroke from a chronic disease to dementia. This study also highlighted the high-risk populations of stroke patients against the environmental risk factors; the males below 65 years old were the most sensitive population.
Experiments showed that the proposed semi-Markovian model outperformed other benchmark diagnosis algorithms (i.e., linear regression, decision tree, random forest, and support vector machine), with a high of 90%. The proposed model also facilitated an accurate prognosis on the transition time of stroke from chronic diseases to dementias against environmental risks and rehabilitation factors.
大多数中风病例会导致严重的身心残疾，如痴呆和感觉障碍。慢性病是中风的促成危险因素。然而，很少有研究考虑与慢性病和环境风险相关的中风向痴呆的转变行为。
本研究旨在开发一种预后模型，以解决与环境风险相关的中风向痴呆转变的问题。
这是一项队列研究，使用了来自中国台湾地区全民健康保险研究数据库的数据。
医疗保健数据来自 2500 多万名参保者，覆盖了中国台湾地区总人口的 99%以上。
本研究调查了中国台湾地区 2000 年至 2010 年间被诊断为中风的 10627 名患者。
构建了 Cox 回归模型和相应的半马尔可夫过程，以评估风险因素对中风、相应痴呆及其转变行为的影响。
相对风险和停留时间是主要观察指标。
多变量分析显示，某些环境风险、药物和康复因素高度影响了从慢性病到痴呆的中风转变。本研究还强调了对环境风险因素具有高敏感性的中风患者高危人群；65 岁以下的男性是最敏感的人群。
实验表明，所提出的半马尔可夫模型优于其他基准诊断算法（即线性回归、决策树、随机森林和支持向量机），准确率高达 90%。该模型还可以根据环境风险和康复因素，准确预测中风从慢性病向痴呆的转变时间。
