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

Area of Science:

• Neurology and Public Health
• Gerontology and Epidemiology
• Medical Informatics

Background:

• Stroke frequently results in significant cognitive and physical impairments, including dementia.
• Chronic diseases are established risk factors for stroke.
• Limited research has explored the transition from stroke to dementia, particularly concerning chronic diseases and environmental influences.

Purpose of the Study:

• To develop a predictive model for stroke patients transitioning to dementia.
• To investigate the impact of environmental risks on the stroke-to-dementia pathway.
• To identify high-risk populations susceptible to dementia following a stroke.

Main Methods:

• Utilized a large cohort study design with data from Taiwan's National Health Insurance Research Database.
• Employed a Cox regression model and a semi-Markov process to analyze transition behaviors.
• Evaluated the influence of risk factors, medication, and rehabilitation on stroke-to-dementia progression.

Main Results:

• Environmental risks, medication, and rehabilitation significantly influence the transition from stroke to dementia.
• Males under 65 years old were identified as the most sensitive population to environmental risk factors.
• The proposed semi-Markovian model achieved a high R-squared of 90%, outperforming other diagnostic algorithms.

Conclusions:

• The developed semi-Markovian model accurately predicts the transition time from stroke to dementia.
• Environmental risks and rehabilitation are key factors in stroke patients developing dementia.
• The study provides valuable insights for targeted interventions and risk management in stroke survivors.