The Heart: Heart disease and stroke news and discussions

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Chest e-tattoo boasts major improvements in heart monitoring
https://medicalxpress.com/news/2023-04- ... heart.html
by University of Texas at Austin
A new flexible, wearable medical device could provide a major boost in the fight against heart disease, the leading cause of death in the United States.

A team led by researchers at The University of Texas at Austin has developed an ultrathin, lightweight electronic tattoo, or e-tattoo, that attaches to the chest for continuous, mobile heart monitoring outside of a clinical setting. It includes two sensors that together provide a clear picture of heart health, giving clinicians a better chance to catch red flags for heart disease early.

"Most heart conditions are not very obvious. The damage is being done in the background and we don't even know it," said Nanshu Lu, a professor in the Department of Aerospace and Engineering Mechanics and a lead author of the study. "If we can have continuous, mobile monitoring at home, then we can do early diagnosis and treatment, and if that can be done, 80% of heart disease can be prevented."

The study is published in Advanced Electronic Materials.

As a continuation of an earlier chest e-tattoo project, this new version is wireless and mobile, which is enabled by a series of small active circuits and sensors carefully arranged and linked by stretchable interconnections and conforms to the chest via a medical dressing. The clear devices are far less intrusive than other monitoring systems and more comfortable for patients.

Currently, there isn't a ready solution for long-term, comfortable monitoring outside of the clinical setting. Clinicians can run tests on patients when they visit, but they may not catch some heart issues because signs of disease are not present at that moment.
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Samsung Gets FDA Approval for Galaxy Watch AFib Detection
Soon, Samsung's Galaxy Watches will be able to monitor for dangerous heart activity in the background.
By Ryan Whitwam May 9, 2023

Samsung launched the Galaxy Watch 5 series last year with a suite of health sensors, including everything it needed to detect atrial fibrillation (AFib) like the Apple Watch. However, it wasn't allowed to do that until now. The Food and Drug Administration (FDA) has cleared Samsung to provide AFib monitoring on its current and upcoming wearables.

The way Samsung goes about detecting heart irregularities differs from Apple. The Apple Watch runs occasional heart rhythm checks and will report if anything seems amiss. Samsung's approach is more like Fitbit—the device takes continuous heart rate and rhythm readings and alerts the user after several anomalous measurements. Samsung calls this Irregular Heart Rhythm Notification (IHRN).
https://www.extremetech.com/electronics ... -detection
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Machine learning algorithm a fast, accurate way of diagnosing heart attack
By Paul McClure
May 15, 2023
Heart attack symptoms are sometimes similar to non-heart-related conditions, making diagnosis tricky. UK researchers have turned to machine learning to provide doctors with a fast and accurate way of diagnosing heart attacks that has the potential to shorten the time needed to make a diagnosis and provide more efficient and effective treatment to patients.

Currently, the gold-star method for diagnosing a heart attack is to measure levels of the protein troponin in the blood. Troponin is released when the heart muscle is damaged; levels usually increase sharply within three to 12 hours after a heart attack, peaking after about 24 hours.

Many hospitals worldwide have adopted diagnostic pathways that include assessing troponin levels when someone is admitted with a suspected heart attack. But they have some limitations: they require the fixed-time collection of blood samples which can be a challenge in the emergency department setting; they only categorize patients as being a low, intermediate or high risk of a heart attack without considering other important information such as when the symptoms began or electrocardiogram (ECG) findings; and, they don’t take into account the influence of sex, age and comorbidities.

Now UK researchers have developed an AI-based machine learning algorithm that is fast and accurate. Named the Collaboration for the Diagnosis and Evaluation of Acute Coronary Syndrome (CoDE-ACS), the algorithm was designed to calculate the probability of a heart attack for an individual patient.
https://newatlas.com/health-wellbeing/c ... diagnosis/
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Specially coated titanium reduces risk of clots on prostheses
https://medicalxpress.com/news/2023-05- ... heses.html
by Friedrich-Schiller-Universität Jena
An international research team led by the German University of Jena has now developed a promising approach to significantly reducing blood clotting on the heart valve material titanium.

Around 25,000 artificial heart valves are implanted in Germany per year because the original heart valve is damaged, for example, by an infection. The mechanical heart valves are made of titanium dioxide, among other materials, and last for many years. However, because blood tends to clot on contact with these material surfaces, there is a risk of blood clots forming on the surface of mechanical heart valves. This can become life-threatening if such blood clots break away from the materials. For this reason, most people with mechanical heart valves take medication throughout their lives to reduce blood clotting.
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CT scan best at predicting heart disease risk in middle age
https://medicalxpress.com/news/2023-05- ... iddle.html
by Northwestern University
CT scans are better at predicting a middle-aged person's risk for a heart disease, such as a heart attack, than genetics, reports a new Northwestern Medicine study published May 23 in JAMA.

"Finding the best way to identify who is at risk for developing heart disease can help determine what needs to be done to lower their risk," said lead study author Dr. Sadiya Khan, an assistant professor of medicine and preventive medicine at Northwestern University Feinberg School of Medicine and a Northwestern Medicine cardiologist. "This finding can help doctors and patients in managing risk for heart disease, which is the leading cause of death in the U.S."

Currently, conventional measures of risk-factor levels, such as blood pressure and cholesterol, are used by doctors to determine a person's likelihood of developing coronary heart disease or blockages of the arteries in the heart. But some people may experience a heart attack, or related heart problem, without one of those conventional factors picking it up.

Because the risk for heart disease can be inherited, scientists were optimistic that a person's genetics can inform who is at greatest risk, Khan said. It was posited that polygenic risk scores—a compilation of more than 6 million commonly occurring genetic variants associated with heart disease—could be used as a potential breakthrough for personalized medicine.

But the new Northwestern study directly compares genetics and CT scans for coronary artery calcium and demonstrates that the CT scan does a better job than genetics at predicting risk for heart disease in middle age.

"These findings support recommendations to consider CT screening to calculate risk for heart disease in middle-aged patients when their degree of risk is uncertain or in the intermediate range," Khan said.
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Five types of heart failure identified using AI tools
https://medicalxpress.com/news/2023-05- ... tools.html
by University College London
Five subtypes of heart failure that could potentially be used to predict future risk for individual patients have been identified in a new study led by UCL researchers.

Heart failure is an umbrella term for when the heart is unable to pump blood around the body properly. Current ways of classifying heart failure do not accurately predict how the disease is likely to progress.

For the study, published in The Lancet Digital Health, researchers looked at detailed anonymized patient data from more than 300,000 people aged 30 years or older who were diagnosed with heart failure in the UK over a span of 20 years.

Using several machine learning methods, they identified five subtypes: early onset, late onset, atrial fibrillation related (atrial fibrillation is a condition causing an irregular heart rhythm), metabolic (linked to obesity but with a low rate of cardiovascular disease), and cardiometabolic (linked to obesity and cardiovascular disease).
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Super low-cost smartphone attachment brings blood pressure monitoring to your fingertips
https://medicalxpress.com/news/2023-05- ... ssure.html
by University of California - San Diego

Engineers at the University of California San Diego have developed a simple, low-cost clip that uses a smartphone's camera and flash to monitor blood pressure at the user's fingertip. The clip works with a custom smartphone app and currently costs about 80 cents to make. The researchers estimate that the cost could be as low as 10 cents apiece when manufactured at scale.

The technology was published May 29 in Scientific Reports.

Researchers say it could help make regular blood pressure monitoring easy, affordable and accessible to people in resource-poor communities. It could benefit older adults and pregnant women, for example, in managing conditions such as hypertension.

"We've created an inexpensive solution to lower the barrier to blood pressure monitoring," said study first author Yinan (Tom) Xuan, an electrical and computer engineering Ph.D. student at UC San Diego.

"Because of their low cost, these clips could be handed out to anyone who needs them but cannot go to a clinic regularly," said study senior author Edward Wang, a professor of electrical and computer engineering at UC San Diego and director of the Digital Health Lab. "A blood pressure monitoring clip could be given to you at your checkup, much like how you get a pack of floss and toothbrush at your dental visit."
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Researchers target proteins, pathways behind congenital heart disease

by University of North Carolina Health Care
https://medicalxpress.com/news/2023-06- ... sease.html
Researchers at the UNC School of Medicine, UNC McAllister Heart Institute, and the UNC Lineberger Comprehensive Cancer Center characterized the expression of thousands of cardiac proteins during eight critical stages of embryonic heart development.

This research, published in Development Cell, will provide scientists with much-needed information to identify biological causes for congenital heart disease, or CHD.

"We now have a foundational data set that shows how protein dynamics change in normal heart development," said first author Whitney Edwards, Ph.D., and assistant professor in the UNC Department of Cell Biology and Physiology. "Researchers can use this as the blueprint to figure out the specific pathways or proteins contributing to congenital heart disease."
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Repurposed drug shows promise for treating cardiac arrhythmias
https://medicalxpress.com/news/2023-06- ... hmias.html
by University of Chicago
Ruxolitinib, a drug that is already approved by the U.S. Food and Drug Administration (FDA) for treating certain cancers and skin conditions, is effective at inhibiting CaMKII, a protein kinase linked to cardiac arrhythmias.

In a new study published June 21, 2023, in Science Translational Medicine, researchers from Johns Hopkins University and the University of Chicago invented a new reporting technique to monitor activity of CaMKII while screening the effects of nearly 5,000 FDA approved drugs on human cells that expressed the enzyme. The screen identified five previously unknown CaMKII inhibitors; ruxolitinib, which is used to treat cancers of the blood and bone marrow, along with skin conditions like atopic dermatitis and vitiligo, was the most effective.

CaMKII, or Calcium and calmodulin-dependent protein kinase II, is critical to cardiomyocytes, the muscle cells of the heart, where it maintains the balance of calcium. Activation of CaMKII helps facilitate rapid changes in heart activity, such as initiating a fight-or-flight response in the body. Overactivation can lead to impaired heart function and cell death, which can in turn lead to poor heart health outcomes like arrhythmia.
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New AI tool beats standard approaches for detecting heart attacks
https://medicalxpress.com/news/2023-06- ... heart.html
by University of Pittsburgh

A new machine learning model uses electrocardiogram (ECG) readings to diagnose and classify heart attacks faster and more accurately than current approaches, according to a study led by University of Pittsburgh researchers that is published in Nature Medicine.

"When a patient comes into the hospital with chest pain, the first question we ask is whether the patient is having a heart attack or not. It seems like that should be straightforward, but when it's not clear from the ECG, it can take up to 24 hours to complete additional tests," said lead author Salah Al-Zaiti, Ph.D., R.N., associate professor in the Pitt School of Nursing and of emergency medicine and cardiology in the School of Medicine. "Our model helps address this major challenge by improving risk assessment so that patients can get appropriate care without delay."

Among the peaks and valleys of an ECG, clinicians can easily recognize a distinct pattern that indicates the worst type of heart attack called STEMI. These severe episodes are caused by total blockage of a coronary artery and require immediate intervention to restore blood flow.

The problem is that almost two-thirds of heart attacks are caused by severe blockage, but do not have the telltale ECG pattern. The new tool helps detect subtle clues in the ECG that are difficult for clinicians to spot and improves classification of patients with chest pain.
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