[The Prediction Model of Cardiovascular Events Among the Russian Population: Methodological Aspects].

Area of Science:

• Public Health
• Epidemiology
• Health Economics

Background:

• Disease modeling is crucial for predicting population health and the socio-economic burden of illness.
• Informed healthcare and prevention decisions rely on accurate disease burden predictions.

Purpose of the Study:

• To develop a predictive model for cardiovascular risk.
• To assess the clinical and socio-economic effects of preventive and therapeutic actions at a population level.

Main Methods:

• A Markov model was employed, incorporating risk factors (blood pressure, cholesterol, smoking) and cardiovascular diseases.
• Data was age-standardized for males and females; multivariate sensitivity analysis was performed.
• Literature searches and expert consultations were integral to model development.

Main Results:

• The model compares intervention scenarios (presence/absence) and includes various cardiovascular diseases and risk factors.
• Analysis revealed age-related mortality patterns and the impact of blood pressure and smoking on death risk.
• Data gaps were identified regarding the incidence of risk factors, highlighting the need for prospective studies.

Conclusions:

• The Markov model predicts intervention effectiveness and socio-economic consequences.
• The model is adaptable for future updates with new research findings to enhance accuracy.