Dataset Information

Stroke to Dementia Associated with Environmental Risks-A Semi-Markov Model.

ABSTRACT: BACKGROUND: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. OBJECTIVE:This study aims to develop a prognosis model to address the issue of stroke transitioning to dementia associated with environmental risks. DESIGN:This cohort study used the data from the National Health Insurance Research Database in Taiwan. SETTING:Healthcare data were obtained from more than 25 million enrollees and covered over 99% of Taiwan's entire population. PARTICIPANTS:In this study, 10,627 stroke patients diagnosed from 2000 to 2010 in Taiwan were surveyed. METHODS: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. MAIN OUTCOME MEASURE:Relative risk and sojourn time were the main outcome measure. RESULTS: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. CONCLUSION: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 R2 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.

SUBMITTER: Wang KJ

PROVIDER: S-EPMC7143936 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Stroke to Dementia Associated with Environmental Risks-A Semi-Markov Model.

Wang Kung-Jeng KJ Lee Chia-Min CM Hu Gwo-Chi GC Wang Kung-Min KM

International journal of environmental research and public health 20200316 6

<h4>Background</h4>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.<h4>Objective</h4>This study aims to develop a prognosis model to address the issue of stroke transitioning to dementia associated with environmental risks.<h4>Design</h4>This c ...[more]

PMID: 32188138

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Project description:In the analysis of semi-competing risks data interest lies in estimation and inference with respect to a so-called non-terminal event, the observation of which is subject to a terminal event. Multi-state models are commonly used to analyse such data, with covariate effects on the transition/intensity functions typically specified via the Cox model and dependence between the non-terminal and terminal events specified, in part, by a unit-specific shared frailty term. To ensure identifiability, the frailties are typically assumed to arise from a parametric distribution, specifically a Gamma distribution with mean 1.0 and variance, say, σ2. When the frailty distribution is misspecified, however, the resulting estimator is not guaranteed to be consistent, with the extent of asymptotic bias depending on the discrepancy between the assumed and true frailty distributions. In this paper, we propose a novel class of transformation models for semi-competing risks analysis that permit the non-parametric specification of the frailty distribution. To ensure identifiability, the class restricts to parametric specifications of the transformation and the error distribution; the latter are flexible, however, and cover a broad range of possible specifications. We also derive the semi-parametric efficient score under the complete data setting and propose a non-parametric score imputation method to handle right censoring; consistency and asymptotic normality of the resulting estimators is derived and small-sample operating characteristics evaluated via simulation. Although the proposed semi-parametric transformation model and non-parametric score imputation method are motivated by the analysis of semi-competing risks data, they are broadly applicable to any analysis of multivariate time-to-event outcomes in which a unit-specific shared frailty is used to account for correlation. Finally, the proposed model and estimation procedures are applied to a study of hospital readmission among patients diagnosed with pancreatic cancer.

Project description:BackgroundSemi-competing risks arise when interest lies in the time-to-event for some non-terminal event, the observation of which is subject to some terminal event. One approach to assessing the impact of covariates on semi-competing risks data is through the illness-death model with shared frailty, where hazard regression models are used to model the effect of covariates on the endpoints. The shared frailty term, which can be viewed as an individual-specific random effect, acknowledges dependence between the events that is not accounted for by covariates. Although methods exist for fitting such a model to right-censored semi-competing risks data, there is currently a gap in the literature for fitting such models when a flexible baseline hazard specification is desired and the data are left-truncated, for example when time is on the age scale. We provide a modeling framework and openly available code for implementation.MethodsWe specified the model and the likelihood function that accounts for left-truncated data, and provided an approach to estimation and inference via maximum likelihood. Our model was fully parametric, specifying baseline hazards via Weibull or B-splines. Using simulated data we examined the operating characteristics of the implementation in terms of bias and coverage. We applied our methods to a dataset of 33,117 Kaiser Permanente Northern California members aged 65 or older examining the relationship between educational level (categorized as: high school or less; trade school, some college or college graduate; post-graduate) and incident dementia and death.ResultsA simulation study showed that our implementation provided regression parameter estimates with negligible bias and good coverage. In our data application, we found higher levels of education are associated with a lower risk of incident dementia, after adjusting for sex and race/ethnicity.ConclusionsAs illustrated by our analysis of Kaiser data, our proposed modeling framework allows the analyst to assess the impact of covariates on semi-competing risks data, such as incident dementia and death, while accounting for dependence between the outcomes when data are left-truncated, as is common in studies of aging and dementia.

Project description:BackgroundLeisure activity participation has been shown to lower risks of cognitive decline in non-stroke populations. However, effects of leisure activities participation upon cognitive functions and risk of dementia after stroke are unclear. The purpose of this study is to examine the effects of recent past leisure activities participation upon cognitive functions and risk of incident dementia after stroke.MethodsHospital-based, retrospective cohort study. 88 of 1,013 patients with stroke or TIA having no prestroke dementia were diagnosed to have incident poststroke dementia (PSD) 3-6 months after stroke. Regular participation (?3 times per week) in intellectual, recreational, social and physical activities over the year before the index stroke was retrospectively recorded at 3-6 months after stroke.ResultsLogistic regression analyses showed that regular participation in intellectual (RR 0.36, 95%CI 0.20-0.63) and stretching & toning physical exercise (0.37, 0.21-0.64) was significantly associated with a reduced risk of PSD after controlling for age, education, prestroke cognitive decline, stroke subtype, prior strokes and chronic brain changes including white matter changes, old infarcts and global atrophy. Results were similar in patients with past strokes in unadjusted models. Participation in increased number of activities in general (r = 0.41, p<0.01) and in intellectual (r = 0.40, p<0.01), recreational (r = 0.24, p<0.01), strenuous aerobic (r = 0.23, p<0.01) and mind-body (r = 0.10, p<0.01) activities was associated with higher poststroke Mini-mental State Examination scores in models adjusted for prestroke cognitive decline.ConclusionsRegular participation in intellectual activities and stretching & toning exercise was associated with a significantly reduced short-term risk of PSD in patients with and without recurrent strokes. Participation in greater number of recent past leisure activities was associated with better poststroke cognitive performance. Findings of this retrospective cohort study call for studies of activity intervention for prevention of cognitive decline in individuals at elevated risk of stroke.

Dataset Information

Stroke to Dementia Associated with Environmental Risks-A Semi-Markov Model.

Publications

Stroke to Dementia Associated with Environmental Risks-A Semi-Markov Model.

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