heart failure risk
Strand-like muscle fibers in the heart tied to heart failure risk
In humans, the heart is the first functional organ to develop, starting to beat by four weeks after conception. During the development, the heart grows an intricate and complex network of muscle fibers, known as trabeculae, forming geometric patterns in the inner lining of the heart. The muscular band of heart tissue called the moderator band or the septomarginal trabecula is found in the right ventricle of the heart and was first described by Leonardo da Vinci in his exploration of human anatomy. Previously, scientists believe that these strand-like muscle structures have no use beyond the heart's early development. Now, a team of researchers at Imperial College London has found that these structures play a pivotal role in the electrical activity and pumping ability of the heart.
Heart failure risk in diabetics can now be predicted by machine learning derived score
The study was also presented at the Heart Failure Society of America Annual Scientific Meeting in Philadelphia. Type 2 diabetes is a global epidemic that is expected to affect over 592 million people globally by 2035, a dramatic increased from 382 million people with diabetes mellitus in 2013, a prevalence that is likely to be underestimated. Type 2 diabetes patients are at more than double the risk of developing heart failure resulting in disability or death among such patients. Earlier this month, late-breaking trial results revealed that a new class of medications known as SGLT2 inhibitors may be helpful for patients with heart failure. These therapies may also be used in patients with diabetes to prevent heart failure from occurring in the first place.
Machine-learning derived model can help predict risk of heart failure for diabetes patients
Heart failure is an important potential complication of type 2 diabetes that occurs frequently and can lead to death or disability. Earlier this month, late-breaking trial results revealed that a new class of medications known as SGLT2 inhibitors may be helpful for patients with heart failure. These therapies may also be used in patients with diabetes to prevent heart failure from occurring in the first place. However, a way of accurately identifying which diabetes patients are most at risk for heart failure remains elusive. A new study led by investigators from Brigham and Women's Hospital and UT Southwestern Medical Center unveils a new, machine-learning derived model that can predict, with a high degree of accuracy, future heart failure among patients with diabetes.
Predicting risk of heart failure for diabetes patients with help from machine learning
Heart failure is an important potential complication of type 2 diabetes that occurs frequently and can lead to death or disability. Earlier this month, late-breaking trial results revealed that a new class of medications known as SGLT2 inhibitors may be helpful for patients with heart failure. These therapies may also be used in patients with diabetes to prevent heart failure from occurring in the first place. However, a way of accurately identifying which diabetes patients are most at risk for heart failure remains elusive. A new study led by investigators from Brigham and Women's Hospital and UT Southwestern Medical Center unveils a new, machine-learning derived model that can predict, with a high degree of accuracy, future heart failure among patients with diabetes.