Stroke risk assessment in rural communities is crucial due to several factors contributing to higher risk in these areas. Rural communities often face unique challenges regarding limited access to healthcare services, lower socioeconomic status, higher prevalence of risk factors, and limited awareness of stroke prevention measures.
A comprehensive approach is required to assess stroke risk in rural communities effectively. This involves considering factors such as age, gender, family history of stroke, lifestyle choices (including smoking, alcohol consumption, and physical activity levels), medical history (hypertension, diabetes, and heart disease), and socioeconomic factors. It is essential to recognize that risk factors can vary within rural communities due to differences in lifestyle, occupation, and environmental factors.
Clinical Trial
Limited research has been conducted on stroke risk assessment in rural regions, and artificial intelligence in stroke risk scoring systems still needs improvement. In this clinical trial, researchers developed a simplified and visualized risk score for assessing the risk of stroke in rural areas. The study utilized a machine learning algorithm to create the risk score and evaluate its performance. The study participants were from the Henan Rural Cohort and were randomly divided into training and test groups. The researchers used the machine learning algorithm to select variables and used statistical methods to construct the scoring system.
AI-based Stroke Risk Assessment
The resulting scoring system, the Rural Stroke Risk Score (RSRS), included factors such as age, drinking status, triglyceride levels, type 2 diabetes mellitus, hypertension, waist circumference, and family history of stroke. The RSRS showed higher discrimination than the Framingham stroke risk profile (FSRP) and the self-reported stroke risk function (SRSRF). It outperformed these existing risk assessment tools by 6.02% and 7.34%, respectively.
Conclusion
This study successfully developed a well-performing scoring system for assessing stroke risk in rural residents. By providing a simplified and visualized risk score, this system can assist healthcare professionals in identifying individuals at higher risk of stroke, leading to more effective preventive measures and improved health outcomes in rural communities. The RSRS has the potential to facilitate stroke screening and contribute to the prevention of cardiovascular disease in economically underdeveloped areas.
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