Deadliest heart disease
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Deadliest Heart Disease: An Overview of Ischemic Heart Disease and Coronary Heart Disease
Introduction to Deadliest Heart Diseases
Cardiovascular diseases (CVDs) are the leading cause of death globally, with ischemic heart disease (IHD) and coronary heart disease (CHD) being the most fatal among them. In 2008, ischemic heart disease alone caused 7.25 million deaths worldwide, highlighting its significant impact on global health. By 2016, coronary heart disease was responsible for 9.4 million deaths, further emphasizing its deadly nature.
Ischemic Heart Disease (IHD)
Definition and Impact
Ischemic heart disease, also known as coronary artery disease, occurs when the blood supply to the heart muscle is reduced due to blockages in the coronary arteries. This condition can lead to severe complications such as heart attacks and heart failure, making it one of the deadliest heart diseases .
Advances in Detection and Prediction
Recent advancements in machine learning and mobile health (mHealth) technologies have shown promise in improving the detection and management of IHD. For instance, mobile apps for heart monitoring and cardiac rehabilitation are being developed to help reduce mortality rates associated with heart diseases. Additionally, machine learning models, such as the K Nearest Neighbor (KNN) algorithm, have demonstrated high accuracy in predicting ischemic heart disease, achieving an accuracy rate of 91.8%.
Coronary Heart Disease (CHD)
Definition and Global Burden
Coronary heart disease is a type of ischemic heart disease characterized by the narrowing or blockage of the coronary arteries. It is the leading cause of death worldwide, with significant mortality rates reported by the World Health Organization (WHO). In Indonesia, for example, CHD, along with other cardiovascular diseases, accounts for 23.1% of deaths, making it the fourth highest cause of death in the ASEAN region.
Predictive Models and Early Detection
To combat the high mortality rates associated with CHD, researchers have developed various predictive models. One such model uses principal component analysis (PCA) combined with binary logistic regression to predict heart disease, achieving an accuracy of 85%. Another study proposed a context-aware clinical decision support model using support vector machines (SVM) for heart failure risk prediction, achieving an average prediction accuracy of 87.9%.
Heart Failure and Other Deadly Heart Conditions
Heart Failure
Heart failure, a condition where the heart cannot pump enough blood to meet the body's needs, is another leading cause of death. Remote monitoring and context-aware clinical decision support systems have been proposed to improve the management and treatment of heart failure, potentially reducing mortality rates.
Infectious Endocarditis
Infectious endocarditis (IE) is a severe heart condition caused by bacterial infections of the heart valves. It remains one of the deadliest heart diseases due to its high mortality rate and complications such as thrombo-embolic events. Current treatments involve surgery and antibiotic therapy, but further research is needed to understand the pathophysiological mechanisms and improve patient outcomes.
Conclusion
Ischemic heart disease and coronary heart disease are the deadliest heart diseases globally, responsible for millions of deaths each year. Advances in mobile health technologies and machine learning models offer promising solutions for early detection and management, potentially reducing mortality rates. Continued research and development in these areas are crucial to combat the global burden of these deadly heart conditions.
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