Lifeboat Foundation

ROCHESTER, Minn. — A recent study based on real-world community patient data confirms the effectiveness of the Pooled Cohort Equation (PCE), developed by the American Heart Association and the American College of Cardiology in 2013. The PCE is used to estimate a person’s 10-year risk of developing clogged arteries, also known as atherosclerosis, and guide heart attack and stroke prevention efforts. Study findings are published in the Journal of the American College of Cardiology.

The new study highlights to patients and clinicians the continued reliability and effectiveness of the PCE as a tool for assessing cardiovascular risk, regardless of statin use to lower cholesterol.

The PCE serves as a shared decision-making tool for a clinician and patient to evaluate their current status in preventing atherosclerotic cardiovascular disease. The calculator considers input in the categories of gender, age, race, total cholesterol, HDL cholesterol, systolic blood pressure, treatment for high blood pressure, diabetes status, and smoking status.

Advances in imaging technologies are giving physicians unprecedented insights into disease states, but fragmented and siloed information technology systems make it difficult to provide the personalized, coordinated care that patients expect.

In the field of medical imaging, health care providers began replacing radiographic films with digital images stored in a picture and archiving communication system (PACS) in the 1980s. As this wave of digitization progressed, individual departments—ranging from cardiology to pathology to nuclear medicine, orthopedics, and beyond—began acquiring their own, distinct IT solutions.

View questions to ask your health care team, ways to manage your self-care, treatment and support resources, and hear from patients and caregivers with rare brain and spine tumors to guide you through your journey.

The study shows that two liquid biopsy techniques can detect the presence of human papillomavirus in blood.

For more information on liver cancer treatment or #YaleMedicine, visit: https://www.yalemedicine.org/stories/artificial-intelligence-liver-cancer.

With liver cancer on the rise (deaths rose 25% between 2006 and 2015, according to the CDC), doctors and researchers at the Yale Cancer Center are highly focused on finding new and better treatment options. A unique collaboration between Yale Medicine physicians and researchers and biomedical engineers from Yale’s School of Engineering uses artificial intelligence (AI) to pinpoint the specific treatment approach for each patient. First doctors need to understand as much as possible about a particular patient’s cancer. To this end, medical imaging techniques such as computed tomography (CT) and magnetic resonance imaging (MRI) are valuable tools for early detection, accurate diagnosis, and effective treatment of liver cancer. For every patient, physicians need to interpret and analyze these images, along with a multitude of other clinical data points, to make treatment decisions likeliest to lead to a positive outcome. “There’s a lot of data that needs to be considered in terms of making a recommendation on how to manage a patient,” says Jeffrey Pollak, MD, Robert I. White, Jr. Professor of Radiology and Biomedical Imaging. “It can become quite complex.” To help, researchers are developing AI tools to help doctors tackle that vast amount of data. In this video, Julius Chaprio, MD, PhD, explains how collaboration with biomedical engineers like Lawrence Staib, PhD, facilitated the development of specialized AI algorithms that can sift through patient information, recognize important patterns, and streamline the clinical decision-making process. The ultimate goal of this research is to bridge the gap between complex clinical data and patient care. “It’s an advanced tool, just like all the others in the physician’s toolkit,” says Dr. Staib. “But this one is based on algorithms instead of a stethoscope.”

The tumor suppressor p53 has been in the limelight for decades. But its cancer-fighting function may be only a side effect of its role in tissue repair, a Stanford Medicine study finds.

The World Health Organization (WHO) has endorsed a second malaria vaccine to protect children against the deadly disease, which killed 619,000 people in 2021.

Researchers say that the vaccine, known as R21, is easier to make than the first-approved malaria vaccine, called RTS, S, and will be cheaper per dose.

“There’s going to be enough of it to actually give out to children,” says Jackie Cook, a malaria researcher at the London School of Hygiene and Tropical Medicine.

The tool — called the Cryosection Histopathology Assessment and Review Machine, or CHARM — studies images to quickly pick out the genetic profile of a kind of tumor called glioma, a process that currently takes days or weeks.

UMass Amherst researchers have pushed forward the boundaries of biomedical engineering one hundredfold with a new method for DNA detection with unprecedented sensitivity.

“DNA detection is in the center of bioengineering,” says Jinglei Ping, lead author of the paper that appeared in Proceedings of the National Academy of Sciences.

Ping is an assistant professor of mechanical and industrial engineering, an adjunct assistant professor in biomedical engineering and affiliated with the Center for Personalized Health Monitoring of the Institute for Applied Life Sciences. “Everyone wants to detect the DNA at a low concentration with a high sensitivity. And we just developed this method to improve the sensitivity by about 100 times with no cost.”