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AI algorithm can rule out heart attacks with 99.6% accuracy

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Heart attacks could soon be diagnosed faster and more accurately thanks to a new test developed with artificial intelligence.

It’s hoped the UK-led breakthrough could reduce the pressure on accident and emergency departments and help end inequalities in diagnosis, which previous research has shown sees women 50% more likely to get a wrong initial prognosis.

People who are initially misdiagnosed have a 70% higher risk of dying after 30 days, according to statistics from the British Heart Foundation.

But researchers at the University of Edinburgh, who developed the algorithm it’s hoped will soon be used by doctors, say it is an opportunity to end this clinical bias.

A trial of 10,286 patients in six countries found that compared to current testing methods this algorithm, named CoDE-ACS, was able to rule out a heart attack in more than double the number of patients with an accuracy of 99.6%.

Clinical trials are now underway in Scotland with support from Wellcome Leap – which focuses on discovery and innovation to improve human health – to assess whether the tool can help doctors reduce the pressure on overcrowded emergency departments.

Professor Nicholas Mills, professor of cardiology at the Centre for Cardiovascular Science at the University of Edinburgh, who led the research, said: “For patients with acute chest pain due to a heart attack, early diagnosis and treatment saves lives.

“Unfortunately, many conditions cause these common symptoms, and the diagnosis is not always straight forward. Harnessing data and artificial intelligence to support clinical decisions has enormous potential to improve care for patients and efficiency in our busy emergency departments.”

The current gold standard for diagnosing a heart attack is measuring levels of the protein troponin in the blood.

But the same threshold is used for every patient. This means that factors like age, sex and other health problems which affect troponin levels are not considered, affecting how accurate heart attack diagnoses are.

This can lead to inequalities in diagnosis.

CoDE-ACS – which stands for Collaboration for the Diagnosis and Evaluation of Acute Coronary Syndrome – was developed using data from more than 10,000 patients in Scotland who had arrived at hospital with a suspected heart attack.

It uses routinely collected patient information, such as age, sex, ECG findings and medical history, as well as troponin levels, to predict the probability that an individual has had a heart attack.

The result is a probability score from 0 to 100 for each patient.

The AI tool performed well regardless of age, sex, or pre-existing health conditions, showing its potential for reducing misdiagnosis and inequalities across the population.

The researchers say CoDE-ACS has the potential to make emergency care more efficient and effective, by rapidly identifying patients that are safe to go home, and by highlighting to doctors all those that need to stay in hospital for further tests.

The work, funded by the British Heart Foundation and the National Institute for Health and Care Research, has been published in the journal Nature Medicine.

Cardiovascular diseases are the leading cause of death globally with an estimated 17.9 million lives lost. More than four out of five CVD deaths are due to heart attacks and strokes.

The average age of people at the time of their first heart attack is 65.5 years for men and 72 years for women.

According to the British Heart Foundation, as many as 100,000 hospital admissions every year in the UK are due to heart attacks – that’s one every five minutes.

Professor Sir Nilesh Samani, Medical Director of the British Heart Foundation, said: “Chest pain is one of the most common reasons that people present to emergency departments. Every day, doctors around the world face the challenge of separating patients whose pain is due to a heart attack from those whose pain is due to something less serious.

“CoDE-ACS, developed using cutting edge data science and AI, has the potential to rule-in or rule-out a heart attack more accurately than current approaches. It could be transformational for emergency departments, shortening the time needed to make a diagnosis, and much better for patients.”

This new test is the second medical AI-related announcement to be made within a matter of days.

Research led by investigators at Harvard Medical School and the University of Copenhagen in collaboration with VA Boston Healthcare System, Dana-Farber Cancer Institute, and the Harvard TH Chan School of Public Health, demonstrated that AI was able to determine a person’s risk of developing pancreatic cancer with astounding accuracy up to three years prior to their actual diagnoses, based solely on their medical records.

In March this year researchers in Canada announced that artificial intelligence had developed a treatment for the most common type of liver cancer, hepatocellular carcinoma, in just 30 days and could predict a patient’s survival rate.

And AI is already being used to help develop new drugs, in surgery and for personalising treatment.

Of this latest study, Steve Goodacre, professor of emergency medicine at the University of Sheffield, said: “This intriguing study shows how AI can use complex analysis, rather than a simple rule, to improve diagnosis.

This doesn’t (yet) show that we can replace doctors with computers. Experienced clinicians know that diagnosis is a complex business. Indeed, the ‘ground truth’ used to judge whether the AI algorithm was accurate was a judgement made by clinicians.

“It will be interesting to see how clinicians in the emergency department use this algorithm. What will they do if they think the algorithm has got it wrong? The next stage of the research will hopefully answer that question.”

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Tai chi outperforms conventional exercise for seniors

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New findings from 12 studies involving 2,901 participants have demonstrated that tai chi outperforms conventional exercise in improving mobility and balance in seniors.

While tai chi is understood to be beneficial for functional mobility and balance in older adults, such benefits are not well understood due to large variance in research study protocols and observations.

This new review and analysis has now shown that tai chi can induce greater improvement in functional mobility and balance in relatively healthy older adults compared to conventional exercise.

The findings showed the following performance results:

  • The time to complete 50-foot walking was 1.84 seconds faster. 
  • The time to maintain a one-leg stance was 6 seconds longer when eyes were open and 1.65 seconds longer when eyes were closed. 
  • Individuals improved their timed-up-and-go test performance by 0.18 points, indicating quicker standing, walking, and sitting.
  • Individuals taking the functional reach test showed significant improvement with a standardised mean difference of 0.7, suggesting a noteworthy positive impact on the ability to reach and perform daily activities.

Secondary analyses revealed that the use of tai chi with relatively short duration of less than 20 weeks, low total time of less than 24 total hours, and/or focusing on the Yang-style of this ancient form of Chinese martial arts were particularly beneficial for functional mobility and balance as compared to conventional exercise.

“This systematic literature review and meta-analysis are exciting because they provide strong evidence that tai chi is a more efficient strategy to improve functional mobility and balance in relatively healthy older adults, as compared to conventional exercise,” said Brad Manor, Ph.D., director of the Mobility and Falls Program at Hebrew SeniorLife’s Hinda and Arthur Marcus Institute for Aging Research, and associate professor of medicine, Harvard Medical School and Beth Israel Deaconess Medical Center.

“This research suggests that tai chi should be carefully considered in future studies and routines of rehabilitative programs for balance and mobility in older adults,” said Bao Dapeng, professor at Beijing Sport University.

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New standards for biomarkers of ageing

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A paper has put forward a new framework for standardising the development and validation of biomarkers of ageing to better predict longevity and quality of life.

Led by Harvard researchers, the team has zeroed in on biomarkers of ageing using omic data from population-based studies. 

The team included ageing and longevity expert Alex Zhavoronkov, PhD, founder and CEO of AI-driven drug discovery company Insilico Medicine, and the findings appeared in Nature Medicine

Ageing is associated with a number of biological changes including increased molecular and cellular damage, however, researchers do not yet have a standardised means to evaluate and validate biomarkers related to ageing. 

In order to create those standards as well as actionable clinical tools, the team analysed population-based cohort studies built on omic data (data related to biological molecules which can include proteomics, transcriptomics, genomics, and epigenomics) of blood-based biomarkers of ageing. The researchers then compared the predictive strength of different biomarkers, including study design and data collection approaches, and looked at how these biomarkers presented in different populations. 

In order to better assess the impact of ageing using biomarkers, the researchers found that clinicians needed to expand their focus to consider not only mortality as an outcome, but also how biomarkers of aging are associated with numerous other health outcomes, including functional decline, frailty, chronic disease, and disability. They also call for the standardisation of omic data to improve reliability. 

“Omics and biomarkers harmonisation efforts, such as the Biolearn project, are instrumental in validation of biomarkers of aging” said co-first author Mahdi Moqri, PhD, of the Division of Genetics. 

Biolearn is an open-source project for biomarkers of aging and is helping to harmonise existing ageing biomarkers, unify public datasets, and provide computational methodologies.

The team also emphasised the importance of continued collaborations among research groups on “large-scale, longitudinal studies that can track long-term physiological changes and responses to therapeutics in diverse populations”, and that further work is required to understand how implementation of biomarker evaluation in clinical trials might improve patient quality of life and survival.

“If we hope to have clinical trials for interventions that extend healthy lifespan in humans, we need reliable, validated biomarkers of ageing,” said co-first author Jesse Poganik, PhD, of the Division of Genetics. 

“We hope that our framework will help prioritise the most promising biomarkers and provide health care providers with clinically valuable and actionable tools.”

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Healthy aging research to receive $115 million

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Global non-profit Hevolution Foundation has announced $115 million in funding that makes up 49 new awards under its Geroscience Research Opportunities (HF-GRO) programme.  

As part of Hevolution’s mission to catalyse the healthspan scientific ecosystem and drive transformative breakthroughs in healthy aging, HF-GRO is funding promising pre-clinical research in aging biology and geroscience. 

Through this first wave of HF-GRO awards, Hevolution will invest up to $115 million in this first cohort of 49 selected projects over the next five years. Its second call for proposals under HF-GRO will be announced later this year, offering an additional $115 million to address the significant funding gaps in aging research.  

Dr. Felipe Sierra, Hevolution’s Chief Scientific Officer stated: “These 49 important research projects represent a significant step forward in deepening our understanding of healthy aging. Hevolution’s prime objective is to mobilise greater investment around uncovering the foundational mechanisms behind biological aging. 

“We are steadfast in our belief that by examining the root causes of aging, rather than solely focusing on its associated diseases, we can usher in a brighter future for humanity.” 

HF-GRO awardees include researchers at prestigious institutions across the United States, Canada, and Europe, including the U.S. National Institute on Aging, Brigham and Women’s Hospital, the Buck Institute, the Mayo Clinic, New York University, and the University of California San Francisco, among many others. 

The American Federation for Aging Research is providing programmatic support for the HF-GRO program, with grantees selected through a rigorous two-stage peer-review process involving 100 experts in aging biology and geroscience. 

Dr Berenice Benayoun, an HF-GRO grant recipient at the University of Southern California, stated: “I am extremely honored and excited that Hevolution selected our project for funding. This is a project close to my heart, which aims at understanding why and how the female and male innate immune aging differs. 

“This funding will support us as we start laying the foundation for a lasting improvement of women’s health throughout aging.” 

To date, Hevolution has committed approximately $250 million to transform the healthy aging sector, including the $40 million for specialised research and development in healthspan science recently announced at Hevolution’s Global Healthspan Summit. 

Hevolution is ramping up its investments to enable healthier aging for all and is now the second largest funder of aging biology research worldwide.  

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