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The research was conducted in a single academic hospital involving patients undergoing major non-cardiac surgeries.
Dr. Disha Merlyn Mathias
2 min read
The impact of accurate diagnosis of heart failure in adult patients influenced intraoperative practice patterns and postoperative outcomes
Researchers at UT Southwestern Medical Center have created a machine learning model capable of identifying patients with diabetic cardiomyopathy. (Representational image: Unsplash)
MBT Desk
2 min read
Machine learning model predicts high-risk diabetic cardiomyopathy, revealing potential for targeted prevention
New research suggests beta blockers could increase depression risk in heart patients, urging a reevaluation of treatment protocols. (Representational Image-Wikimedia Commons)
Ankur Deka
3 min read
New research from Uppsala university raises concerns about routine use of beta blockers in patients with normal heart function
The model, called the WATCH-DM score, is used to predict the likelihood of heart failure in diabetes patients within five years.
(Unsplash)
MBT Desk
2 min read
A recent study by Case Western Reserve University used national data from U.S. military veterans to predict the risk of heart failure in diabetic patients.
A new study sheds light on how autophagy, the body’s process for removing damaged cell parts, when impaired, can play a role in causing heart failure (Representational image : Unsplash)
MBT Desk
3 min read
UCLA Health researchers say findings may have implications for heart failure treatment
Published in Circulation, an American Heart Association journal, the study found that the new strategy is the best approach for predicting heart failure in patients with diabetes. (Representational Image: Unsplash)
MBT Desk
3 min read
Published in Circulation, an American Heart Association journal, the study found that the new strategy is the best approach for predicting heart failure in patients with diabetes
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