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Deep learning can make reliable coma outcome prediction
After cardiac arrest and resuscitation, part of the patients will be in a coma and treated at an intensive care unit. Their prospects are uncertain. What is needed to get an outcome prediction that is reliable? Researchers of the University of Twente and the ‘Medisch Spectrum Twente’ hospital, both in Enschede, The Netherlands, developed a learning network that is capable of interpreting EEG-patterns. It can make a reliable outcome prediction, and thus forms a valuable extra source of information.
In The Netherlands, about one third of the people that had a cardiac arrest followed by resuscitation, will have to be treated at the ICU. These patients, about 7000 each year, are in a coma. More than half of them will not regain consciousness. The family will want to know what the prospects are and, if their relative regains consciousness, what will be the quality of life. The question ‘does further treatment make sense?’ can only be answered after careful analysis of the situation. One of the options, now, is the SEPP-t
The electrical signals of the brain, the EEG pattern measured via electrodes on the head, give a lot of information as well. Analysis of EEG using artificial intelligence gives a very accurate outcome prediction, as the researchers show in their latest paper. Twelve hours after resuscitation, the learning network is capable of predicting a good outcome with 58 percent accuracy and a bad outcome with 48 percent. This is a better performance than the trained eye of a neurologist. Both computer and human, however, still have a category ‘I don’t know’, in situations the EEG data are not specific enough.
The first author, Marleen Tjepkema, already made a plea for using EEG in the outcome prediction, in her PhD thesis in 2014 as a UT Technical Medicine graduate. She and her colleagues now take this an important step further by introducing automated interpretation of the EEG scan. The learning network has been trained using 600 EEG patterns, it did not get any hints on what to look at. After that, it was fed with 300 EEG patterns to see how it performed in giving a prediction. Neurologists have to look at hundreds of EEG’s as well, as part of their training. An experienced neurologist will point out specific characteristics. Still, the EEG-patterns are so information-rich that the computer outperforms the human eye.
Once trained, the network will be capable of judging the EEG very fast, well within a second. The researchers expect that this adds valuable information to human judgment. One of the other advantages is flexibility, a prediction can be made any time of the day. Using the new technology at ICU’s will show if the ‘intensivist’ also sees as a valuable tool.
University Twentehttps://tinyurl.com/y6amneh9
IHF gathers leading healthcare thinkers for the 43rd World Hospital Congress
The 43rd World Hospital Congress of the International Hospital Federation has invited thought leaders, experts and top-level professionals to explore how health services can be better provided during peace and crisis. Topics have been lined up to explore how health services can be more responsive through better resilience, supportive through appropriate health investments and prospective through health impactful innovations.
The World Hospital Congress is a unique global forum where leaders of national and international hospital and healthcare organizations convene to share knowledge, expertise, experiences and best practices in leadership in hospital and healthcare management and service delivery.
Hosted by the Ministry of Health of the Sultanate of Oman on 6 to 9 November in Muscat, the Congress will feature more than 100 presenters in 40 sessions, poster displays, pre-conference session, hospital site visits, healthcare exhibition, special events and networking opportunities in three transformative days which will give delegates opportunities to learn, exchange, and engage with peers.
Keynote speakers include the following thought leaders and experts:
1. Hon. Yuthar Mohammed Al Rawahy, Founder & Honorary Life President of the Oman Cancer Association will share her perspectives on the role of patients in time of peace and crisis from self-empowerment to social mobilization;
2. Sir Andrew Dillon CBE, Chief Executive of the National Institute for Health and Care Excellence will share how to align the ambition of health systems and the life sciences industry for successful adoption of new health technologies;
3. Dr. Melinda Estes, President and CEO of Saint Luke’s Health System and Chair-elect of the American Hospital Association will provide insights on how hospitals and health systems are driving community health and prosperity;
4. Dr. Agnés Soucat, Director for Health Systems Governance and Financing at the World Health Organization will discuss the role of hospitals and health services in support to population well-being.
Besides keynote presentations, panel discussions with leading industry professionals and patient representatives will examine a range of topics including:
· The role of hospitals in time of crisis;
· Patient and community voice in time of peace and crisis;
· Health service providers contributing to health and prosperity;
· Health services in support to better well-being;
· Taking the innovation to the service.
Early bird registration to the Congress closes on 15 August 2019. https://worldhospitalcongress.org/2019-registration/ congress@ihf-fih.org
My Personal Therapeutics and Pentavere receive Eureka funding
My Personal Therapeutics, a London-based medtech/digital therapeutics company and Pentavere Research Group, a Canadian-based Artificial Intelligence and data insight company have been awarded Eurkela Collaborative R&D funding for artificial intelligence and quantum technologies. The funding is for a project titled: Utilisation of AI to develop Personalised Treatment Plans for cancer.
Funding totalling £792,000 (Euro 870,000) is co-funded by the UK’s innovation agency, Innovate UK, and Canada’s National Research Council’s Industrial Research Assistant Program, as part of their collaborate R&D programme.
These funds will be used by Pentavere Research Group and My Personal Therapeutics to access Genomics England’s whole genome sequencing lung cancer data set and selectively generate drosophila avatars for high-throughput drug screening. The resulting tumour genomic profile and corresponding drug treatment recommendation data will feed into their AI Personal Discovery Process (PDP) predictive model.
Laura Towart, CEO, My Personal Therapeutics, commented: “This Eureka award will partly fund this ground-breaking collaboration between My Personal Therapeutics, Pentavere and Genomics England towards the development of our rapid personalised cancer therapeutics offering – AI PDP.”
The PDP technology leverages Big Data curated from electronic health records, and genomics to build personalised fruit fly ‘avatars’ that model individual patients at an unprecedented level of complexity. Using robotics, thousands of drugs are screened in combinations to identify drug cocktails designed to target the tumour while preserving the patient’s quality of life. Nearly all combinations incorporate non-cancer drugs, making them less toxic and more affordable. The company says they are integrating AI predictive modelling to enable rapid personalised treatment recommendations.
Can your pets get infected with the coronavirus?
A small study published 8 April 2020 in Science by researchers in China found that cats are highly susceptible to SARS-CoV-2 and can pass the virus on to other cats via airborne transmission. However, dogs showed low susceptibility, and livestock including pigs, chickens, and ducks were not susceptible to the virus.
They did not study specifically whether cats can pass the virus to humans, although this seems likely as cats can pass the virus to other cats via airborne transmission.
From their findings, the researchers suggest that surveillance for SARS-CoV-2 in cats should be considered as an adjunct to elimination of COVID-19 in humans.>/p>
Two viruses – SARS-CoV 2/F13/environment/2020/Wuhan, isolated from an environmental sample collected in the Huanan Seafood Market in Wuhan (F13-E), and SARS-CoV-2/CTan/human/2020/Wuhan (CTan-H), isolated from a human patient – were used in the study.
The researchers first investigated the replication of SARS-CoV-2 in cats. Seven subadult cats (aged 6-9 months) were intranasally inoculated with 105 PFU of CTan-H. Two animals were scheduled to be euthanized on days 3 post infection (p.i.) and 6 p.i., respectively, to evaluate viral replication in their organs. Three subadult cats were placed in separate cages within an isolator. To monitor respiratory droplet transmission, an uninfected cat was placed in a cage adjacent to each of the infected cats.
In the transmission study, viral RNA was detected in the faeces of two virus-inoculated subadult cats on day 3 p.i., and in all three virus-inoculated subadult cats on day 5 p.i. Viral RNA was detected in the faeces of one exposed cat on day 3 p.i. The pair of subadult cats with viral RNA-positive faeces were euthanized on day 11 p.i., and viral RNA was detected in the soft palate and tonsils of the virus-inoculated animal and in the nasal turbinate, soft palate, tonsils, and trachea of the exposed animal indicating that respiratory droplet transmission had occurred in this pair of cats. Antibodies against SARS-CoV-2 were detected in all three virus-inoculated subadult cats and one exposed cat.
They replicated the study in juvenile cats and found “massive lesions in the nasal and tracheal mucosa epitheliums, and lungs”, indicating that SARS-CoV-2 can replicate efficiently in cats, with younger cats being more permissive.
Additionally, and importantly, the study showed that the virus can transmit between cats via the airborne route.
For the study in dogs, five 3-month-old beagles were intranasally inoculated with 105 PFU of CTan-H, and housed with two uninoculated beagles in a room. Oropharyngeal and rectal swabs from each beagle were collected over a series of days.
Viral RNA was detected in the rectal swabs of two virus-inoculated dogs on day 2 p.i and in the rectal swab of one dog on day 6 p.i. However, they note that “infectious virus was not detected in any swabs collected from these dogs”.
Two virus-inoculated dogs showed antibodies. The other two virus-inoculated dogs and the two contact dogs were all seronegative for SARS-CoV-2.
The dog study was repeated in pigs, chickens and ducks and viral RNA was not detected in any swabs collected from these animals or from naïve contact animals. All were seronegative for SARS-CoV-2.
doi: 10.1126/science.abb7015
Diarrhea-causing bacteria adapted to spread in hospitals
An emerging species of C. difficile, named clade A, was found to make up approximately 70 per cent of the samples taken from hospital patients
Scientists have discovered that the gut-infecting bacterium C. difficile is evolving into two separate species, with one group highly adapted to spread in hospitals. Researchers at the Wellcome Sanger Institute, London School of Hygiene & Tropical Medicine and collaborators identified genetic changes in the newly-emerging species that allow it to thrive on the Western sugar-rich diet, evade common hospital disinfectants and spread easily. Able to cause debilitating diarrhea, they estimated this emerging species started to appear thousands of years ago, and accounts for over two thirds of healthcare C. difficile infections.
The largest ever genomic study of C. difficile shows how bacteria can evolve into a new species, and demonstrates that C. difficile is continuing to evolve in response to human behaviour. The results could help inform patient diet and infection control in hospitals.
C. difficile bacteria can infect the gut and are the leading cause of antibiotic-associated diarrhea worldwide. While someone is healthy and not taking antibiotics, millions of ‘good’ bacteria in the gut keep the C. difficile under control. However, antibiotics wipe out the normal gut bacteria, leaving the patient vulnerable to C. difficile infection in the gut. This is then difficult to treat and can cause bowel inflammation and severe diarrhea.
Often found in hospital environments, C. difficile forms resistant spores that allow it to remain on surfaces and spread easily between people, making it a significant burden on the healthcare system.
To understand how this bacterium is evolving, researchers collected and cultured 906 strains of C. difficile isolated from humans, animals, such as dogs, pigs and horses, and the environment. By sequencing the DNA of each strain, and comparing and analysing all the genomes, the researchers discovered that C. difficile is currently evolving into two separate species.
“Our large-scale genetic analysis allowed us to discover that C. difficile is currently forming a new species with one group specialized to spread in hospital environments. This emerging species has existed for thousands of years, but this is the first time anyone has studied C. difficile genomes in this way to identify it. This particular bacteria was primed to take advantage of modern healthcare practices and human diets, before hospitals even existed” said Dr Nitin Kumar, joint first author from the Wellcome Sanger Institute.
The researchers found that this emerging species, named C. difficile clade A, made up approximately 70 per cent of the samples from hospital patients. It had changes in genes that metabolize simple sugars, so the researchers then studied C. difficile in mice, and found that the newly emerging strains colonized mice better when their diet was enriched with sugar. It had also evolved differences in the genes involved in forming spores, giving much greater resistance to common hospital disinfectants. These changes allow it to spread more easily in healthcare environments.
Dating analysis revealed that while C. difficile Clade A first appeared about 76,000 years ago, the number of different strains of this started to increase at the end of the 16th century, before the founding of modern hospitals. This group has since thrived in hospital settings with many strains that keep adapting and evolving.
“Our study provides genome and laboratory based evidence that human lifestyles can drive bacteria to form new species so they can spread more effectively. We show that strains of C. difficile bacteria have continued to evolve in response to modern diets and healthcare systems and reveal that focusing on diet and looking for new disinfectants could help in the fight against this bacterium.
The Wellcome Sanger Institutehttps://tinyurl.com/y2lumdmn
Coronavirus Global Response raises €7.4 billion in pledges
€7.4 billion was raised at the Coronavirus Global Response pledging event on 4 May to kick-start an unprecedented global cooperation between scientists and regulators, industry and governments, international organisations, foundations and health care professionals to ensure the collaborative development and universal deployment of diagnostics, treatments and vaccines against coronavirus.
The pledging event was co-convened by the European Union, Canada, France, Germany, Italy, Japan, the Kingdom of Saudi Arabia, Norway, Spain and the United Kingdom. It builds on the commitment made by G20 leaders on 26 March and follows a call by the WHO on 24 April for a global collaboration for the accelerated development, production and equitable global access to new coronavirus essential health technologies.
Commenting on the success of the event, President of the European Commission, Ursula von der Leyen, said: “The world showed extraordinary unity for the common good. Governments and global health organisations joined forces against coronavirus. With such commitment, we are on track for developing, producing and deploying a vaccine for all. However, this is only the beginning. We need to sustain the effort and to stand ready to contribute more. The pledging marathon will continue. After governments, civil society and people worldwide need to join in, in a global mobilisation of hope and resolve.”
The funds raised will be channelled primarily through recognised global health organisations such as CEPI, Gavi, the Vaccines Alliance, as well as the Global Fund and Unitaid into developing and deploying as quickly as possible, for as many as possible, the diagnostics, treatments and vaccines that will help the world overcome the pandemic.
The Coronavirus Global Response Initiative is comprised of three partnerships for testing, treating and preventing underpinned by health systems strengthening. The three partnerships will work as autonomously as possible, with a transversal work stream on enhancing the capacity of health systems and knowledge and data sharing.
The European Commission will register and keep track of pledges up until end of May but will not receive any payments into its accounts. Funds go directly to the recipients. Recipients will, however, not decide alone on the use of the donation, but deploy it in concert with the partnership. The commitment is for all new vaccines, diagnostics and treatments against coronavirus to be made available globally for an affordable price, regardless of where they were developed.
The Global Vaccines Summit that Gavi, the Vaccine Alliance, will organise on 4 June will mobilise additional funding to protect the next generation with vaccines. As the world relies on Gavi’s work for making vaccination available everywhere, the success of Gavi’s replenishment will be crucial to the success of the Coronavirus Global Response.
In an Op-ed ahead of the pledging event, co-authored by Giuseppe Conte, President of the Government of the Italian Republic, Emmanuel Macron, President of the French Republic, Angela Merkel, Federal Chancellor of the Federal Republic of Germany, Charles Michel, President of the European Council, Erna Solberg, Prime Minister of the Kingdom of Norway, Justin Trudeau, Prime Minister of Canada and Ursula von der Leyen, President of the European Commission, they said: “None of us is immune to the pandemic and none of us can beat the virus alone. In fact, we will not truly be safe until all of us are safe – across every village, city, region and country in the world. In our interconnected world, the global health system is as strong as its weakest part. We will need to protect each other to protect ourselves.
“This poses a unique and truly global challenge. And it makes it imperative that we give ourselves the best chance to defeat it. This means bringing together the world’s best – and most prepared – minds to find the vaccines, treatments and therapies we need to make our world healthy again
“This is our generation’s duty and we know we can make this happen. High quality and low-cost health technologies are not a daydream. And we have seen how public-private partnerships have managed to make many life-saving vaccines available to the poorest people on earth over the last two decades.
“This is a defining moment for the global community. By rallying around science and solidarity today we will sow the seeds for greater unity tomorrow. Guided by the Sustainable Development Goals, we can redesign the power of community, society and global collaboration, to make sure that nobody is left behind.”
Coronavirus Global Response https://global-response.europa.eu
Oncimmune at Medica
The battle against cancer hinges on the early detection and then delivery of effective treatment. Oncimmune is working to revolutionise both the detection of cancer and its treatment by harnessing the sophisticated disease-detecting capabilities of the immune system to find cancer in its early stages. Oncimmune’s range of diagnostic tests assist clinicians to identify the presence of cancer on average four years before standard clinical diag-
nosis, whilst its technology platform and sample biobanks are helping healthcare companies to develop new cancer treatments.
Coronary artery disease diagnosis improved by deep learning analysis of SPECT MPI
A multicentre international study has demonstrated for the first time that diagnosis of obstructive coronary artery disease can be improved by using deep learning analysis of upright and supine single photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI).
According to the Centers for Disease Control and Prevention, coronary artery disease is the most common type of heart disease, killing more than 370,000 people in the United States annually. SPECT MPI, which is widely used for its diagnosis, shows how well the heart muscle is pumping and examines blood flow through the heart during exercise and at rest. On new cameras with a patient imaged in sitting position, two positions (semi-upright and supine) are routinely used to mitigate attenuation artifacts. The current quantitative standard for analysing MPI data is to calculate the combined total perfusion deficit (TPD) from these 2 positions. Visually, physicians need to reconcile information available from 2 views.
Deep convolutional neural networks, often referred to as deep learning (DL), go beyond machine learning using algorithms. They directly analyse visual data, learn from them, and make intelligent findings based on the image information.
For this study, DL analysis of data from the two-position stress MPI was compared with the standard TPD analysis of 1,160 patients without known coronary artery disease. Patients underwent stress MPI with the nuclear medicine radiotracer technetium (99mTc) sestamibi. New-generation solid-state SPECT scanners in four different centres were used, and images were quantified at the Cedars-Sinai Medical Centre in Los Angeles, California. All patients had on-site clinical reads and invasive coronary angiography correlations within six months of MPI.
Obstructive disease was defined as at least 70 percent narrowing of the three major coronary arteries and at least 50 percent for the left main coronary artery. During the validation procedure, four different DL models were trained (each using data from three centers) and then were evaluated on the one center left aside. Predictions for 4 centers were merged to have an overall estimation of the multicenter performance.
The study revealed that 718 (62 percent) patients and 1,272 of 3,480 (37 percent) arteries had obstructive disease. Per-patient sensitivity improved from 61.8 percent with TPD to 65.6 percent with DL, and per-vessel sensitivity improved from 54.6 percent with TPD to 59.1 percent with DL. In addition, DL had a sensitivity of 84.8 percent, versus 82.6 percent for an on-site clinical read.
The results clearly show that DL improves MPI interpretation over current methods.
“These findings were demonstrated for the first time in a rigorous, repeated external validation,” points out Piotr J. Slomka, PhD, at Cedars-Sinai Medical Center, affirming that “the latest developments in artificial intelligence can be efficiently leveraged to enhance the accuracy of existing nuclear medicine techniques.”
Society of Nuclear Medicine and Molecular Imaging
https://tinyurl.com/y5q537lm