Artificial intelligence (AI) has shown promise to select heart failure patients for expensive treatments to prevent lethal arrhythmias, reports a study presented today at ICNC 2019. The study is the first to use a machine-learning algorithm to predict sudden death in heart failure patients.
Around 1-2% of adults in developed countries have heart failure, a clinical syndrome characterised by breathlessness, ankle swelling, and fatigue. A high proportion of deaths in these patients, especially those with milder symptoms, occur suddenly due to ventricular arrhythmias. Implantable cardioverter defibrillators (ICDs) or cardiac resynchronisation therapy with a pacemaker and defibrillator (CRT-D) are recommended for some patients to correct potentially lethal arrhythmias and reduce the risk of sudden death. However, these treatments are expensive and do not work in all patients.
Study author Professor Kenichi Nakajima, of Kanazawa University Hospital, Japan, said: "Our model calculated the probability of a sudden arrhythmic event with an area under the curve (AUC) of 0.74, where 1.0 is perfect prediction and 0.5 is a random result. This could be used to identify very low risk patients for whom an ICD or CRT-D is not required, and very high risk patients who should receive a device. Optimising risk evaluation in this way will improve the cost effectiveness of treatment."
The study included 529 heart failure patients with known two-year outcomes for sudden arrhythmic events (including arrhythmic death, sudden cardiac death, and appropriate shock from an ICD) and death due to heart failure.
Machine learning — a type of AI used by the Google search engine and face recognition on smartphones — was used to discover how eight variables used to predict prognosis of heart failure patients were connected and create a formula correlating them to two-year outcomes.
The eight factors were age, sex, heart failure severity (New York Heart Association functional class), heart pumping function (left ventricular ejection fraction), whether heart failure was caused by restricted blood supply (ischaemia), B-type natriuretic peptide level in the blood, kidney function (estimated glomerular filtration rate), and a nuclear imaging parameter.
During the two-year follow-up there were 141 events (27%) consisting of 37 sudden arrhythmic events (7%) and 104 deaths due to heart failure (20%). The AUC for predicting all events was 0.87, while for arrhythmic events and heart failure death it was 0.74 and 0.91, respectively.
Professor Nakajima said: "This is a preliminary study and we can improve the prediction of arrhythmic events by adding variables and continuing to train the machine learning algorithm."
The imaging parameter was heart-to-mediastinum ratio (HMR) of 123Iodine-metaiodobenzylguanidine (MIBG) uptake. MIBG is a radioisotope analogue of norepinephrine and is used to assess the activity of cardiac sympathetic nerves. Previous studies have shown that HMR predicts cardiac death in patients with heart failure. The measure is obtained by injecting MIBG into a vein, then using imaging to assess uptake in the heart and upper mediastinum (centre of the thoracic cavity).
Professor Nakajima noted that while MIBG imaging is approved in the US and Japan for clinical practice, and in Europe for clinical research, it is less commonly used outside Japan due to its cost. A typical MIBG tracer costs €350 in Japan compared to €1,900-3,400 in the US.3 He said: "While the costs of the scan may be high, it would be value for money if unnecessary device implantations were avoided."
ScienceDaily https://tinyurl.com/y3qx6zso

HEALTH DATA Researchers from the University of Copenhagen and Rigshospitalet have used data on more than 230,000 intensive care patients to develop a new algorithm. Among other things, it uses disease history from the past 23 years to predict patients’ chances of survival in intensive care units.
Every year, tens of thousands of patients are admitted to intensive care units throughout Denmark. Determining which treatment is best for the individual patient is a great challenge. To make this decision, doctors and nurses use various methods to try to predict the patient’s chances of survival and mortality. However, the existing methods can be significantly improved.
Therefore, researchers from the Faculty of Health and Medical Sciences at the University of Copenhagen and Rigshospitalet have developed a new algorithm which much more accurately predicts an intensive care patient’s chances of surviving.
‘We have used Danish health data in a new way, using an algorithm to analyse file data from the individual patient’s disease history. The Danish National Patient Registry contains data on the disease history of millions of Danes, and in principle the algorithm is able to draw on the history of the individual citizen of benefit to the individual patient in connection with treatment,’ says Professor Søren Brunak from the Novo Nordisk Foundation Center for Protein Research.
Developing the algorithm, the researchers used data on more than 230,000 patients admitted to intensive care units in Denmark in the period 2004-2016. In the study the algorithm analysed the individual patient’s disease history, covering as much as 23 years. At the same time, they included in their calculations measurements and tests made during the first 24 hours of the admission in question. The result was a significantly more accurate prediction of the patient’s mortality risk than offered by existing methods.
‘Excessive treatment is a serious risk among terminally ill patients treated in Danish intensive care units. Doctors and nurses have lacked a support tool capable of instructing them on who will benefit from intensive care. With these results we have come a significant step closer to testing such tools and directly improving treatment of the sickest patients,’ says Professor Anders Perner from the Department of Clinical Medicine and the Department of Intensive Care, Rigshospitalet.
The algorithm made three predictions: the risk of the patient dying in hospital (which could be any number of days following admission), within 30 days of admission and within 90 days of admission.
For example, the researchers could tell that up to 10-year-old diagnoses affected predictions, and that young age lowered the risk of dying, even when other values were critical, while old age increased mortality risk. The algorithm is not just a useful tool in everyday practice in intensive care units throughout the country. It can also tell us which factors are significant when it comes to a person’s death or survival.
’We “train” the algorithm to remember which previous diagnoses have had the greatest effect on the patient’s chances of survival. No matter whether they are one, five or 10 years old. This is possible when we also have data from the actual admission, such as heart rate or answers to blood tests. By analysing the method, we are able to understand the importance it attaches to the various parameters with regard to death and survival,’ says Søren Brunak.
University of Copenhagen The Faculty of Health and Medical Scienceshttps://tinyurl.com/y237ogab

Cardiovascular-related technology is an exciting field as new devices and biotech products continue to emerge from research labs with rapid succession propelled by a vigorous stream of innovation. In this focus on smart tech for cardiology we look at some of the latest developments in this extremely dynamic arena – from 3D bioprinted cardiovascular tissue to a new bionic heart and synthetic blood.
Engineers at MIT have recently developed a bionic heart, not for transplant or a bridge to transplant, but for research. The demand for prosthetic heart valves and other cardiac devices is expected to grow significantly in the coming years driven by a growing geriatric population.
Prosthetic valves are designed to mimic a real, healthy heart valve in helping to circulate blood through the body. However, many of them have issues, such as leakage around the valve. Engineers working to improve these designs must test them repeatedly, first in simple benchtop simulators, then in animal subjects, before reaching human trials – a long and expensive process. This is where the bionic heart comes in. The bionic heart offers a more realistic model for testing artificial valves and other cardiac devices.
The device is a real biological heart in which the tough muscle tissue has been replaced with a soft matrix of artificial heart muscles, resembling bubble wrap. The orientation of the artificial muscles mimics the pattern of the heart’s natural muscle fibres, in such a way that when the researchers remotely inflate the bubbles, they act together to squeeze and twist the inner heart, similar to the way a real, whole heart twists when it beats and pumps blood.
With this new design, which the researchers call a “biorobotic hybrid heart”, they envision that device designers and engineers could iterate and fine-tune designs more quickly by testing on the biohybrid heart, significantly reducing the cost of cardiac device development. Ellen Roche, assistant professor of mechanical engineering at MIT, explains: “Regulatory testing of cardiac devices requires many fatigue tests and animal tests. The biorobotic hybrid heart could realistically represent what happens in a real heart, to reduce the amount of animal testing or iterate the design more quickly.”
Roche and her colleagues published their results January 29, 2020 in the journal Science Robotics.
Inspired design
The heart normally pumps blood by squeezing and twisting, a complex combination of motions that is a result of the alignment of muscle fibres along the outer myocardium that covers each of the heart’s ventricles. The team planned to fabricate a matrix of artificial muscles resembling inflatable bubbles, aligned in the orientations of the natural cardiac muscle. But copying these patterns by studying a ventricle’s three-dimensional geometry proved extremely challenging.
They eventually came across the helical ventricular myocardial band theory, the idea that cardiac muscle is essentially a large helical band that wraps around each of the heart’s ventricles. This theory is still a subject of debate by some researchers, but Roche and her colleagues took it as inspiration for their design. Instead of trying to copy the left ventricle’s muscle fibre orientation from a 3D perspective, the team decided to remove the ventricle’s outer muscle tissue and unwrap it to form a long, flat band – a geometry that should be far easier to recreate. In this case, they used the cardiac tissue from an explanted pig heart.
In collaboration with co-lead author Chris Nguyen at Massachusetts General Hospital, the researchers used diffusion tensor imaging, an advanced technique that typically tracks how water flows through white matter in the brain, to map the microscopic fibre orientations of a left ventricle’s unfurled, two-dimensional muscle band. They then fabricated a matrix of artificial muscle fibres made from thin air tubes, each connected to a series of inflatable pockets, or bubbles, the orientation of which they patterned after the imaged muscle fibres.
The soft matrix consists of two layers of silicone, with a watersoluble layer between them to prevent the layers from sticking, as well as two layers of laser-cut paper, which ensures that the bubbles inflate in a specific orientation.
Finally, the researchers placed the entire hybrid heart in a mould that they had previously cast of the original, whole heart, and filled the mould with silicone to encase the hybrid heart in a uniform covering – a step that produced a form similar to a real heart and ensured to a real heart and ensured that the robotic bubble wrap fitted snugly around the real ventricle.
“That way, you don’t lose transmission of motion from the synthetic muscle to the biological tissue,” Roche explained.
When the researchers pumped air into the bubble wrap at frequencies resembling a naturally beating heart, and imaged the bionic heart’s response, it contracted in a manner similar to the way a real heart moves to pump blood through the body.
Ultimately, the researchers hope to use the bionic heart as a realistic environment to help designers test cardiac devices, such as prosthetic heart valves.

3D bioprinted cardiovascular tissue

Cardiovascular disease (CVD) is the leading cause of mortality worldwide, with over 17 million deaths per year, according to the World Health Organisation.
The ideal treatment for some forms of severe CVD, such as chronic heart failure or extensive myocardial injury, is cardiac transplantation. Due to shortages in available donor tissue, this cannot be given to all patients. The average waiting time for a suitable donor is six to twelve months in the United States and around one in six people die before they can receive a transplant. There is a clear need for a more abundant supply of hearts suitable for transplantation.
A common strategy to address heart failure is to use a cardiac pump, such as a left ventricular assist device (LVAD), when a donor heart is not available. Current treatment options are useful to a certain extent, but personalized solutions are required to improve patient outcomes and quality of life. This need is driving the development of cardiovascular 3D bioprinting technologies, which make use of 3D printinglike techniques to combine cells and biomaterials to fabricate biomimetic structures that replicate natural tissue physiology and function.
Developing a dynamic cardiac tissue capable of mimicking the mechanical and electroconductive properties of native myocardium is proving difficult for researchers. Many challenges stand in their way including, among others, re-creating tissue matrix and providing an adequate oxygen supply to each cell.
The success of 3D bioprinting depends on researchers’ ability to vascularise the tissue. For this reason, a lot of focus has recently been placed on the generation of blood vessels. Several promising studies have already been conducted. For instance, researchers at University of California San Diego 3D printed a functional blood vessel network which, once implanted in mice, merged with the animal’s blood vessels and was capable of transporting blood. Similar achievements have been reported by Sichuan Revotek, Rice University and the University of Pennsylvania in the past few years.
Cardiac patches
An important innovation in the we move towards 3D bioprinting cardiac tissue is the development of cell sheets. Terumo, a Japanese conglomerate, has commercialized the Heart Sheet for treatment of heart failure in Japan. To develop Heart Sheet, muscle tissue is harvested from the patient’s leg and cultured in vitro. Terumo has developed a tissue culture plate that allows cells to float off the surface in an intact sheet when the temperature is lowered, thus preserving the extracellular matrix that is lost when cells are removed by other methods.
Cardiac tissue engineering techniques such as this one can be used to create functional constructs capable of re-establishing the structure and function of damaged myocardium following myocardial infarction. The engineered cardiac tissue, which often comes in the form of a “patch”, is implanted directly onto scar tissue. The intention is to compensate for the heart’s reduced function by strengthening its structure and boosting its ability to pump blood. This way, researchers hope to reduce the need for transplants, improve recovery and prevent subsequent events.
Researchers across the world are developing “cardiac patches”. In June 2019, Imperial College London announced the creation of thumbsize patches of heart tissue that start to beat spontaneously after three days and start to mimic mature heart tissue within one month. These patches successfully led to improvements in heart function following a heart attack after only four weeks. Importantly, blood vessels appeared to have formed within the patch after that time. Clinical trials are expected to start this year or 2021.
Once implanted, cardiac patches could do more than just promote cardiac tissue regeneration. For instance, a bionic patch could deliver electrical shocks and act as a pacemaker. Scientists at the University of Tel Aviv also investigated integrating electronic sensors into the patch to enable remote monitoring of cardiac activity.
Although researchers have not yet been able to create a fully functioning artificial heart, an important leap was made in 2019. Researchers from Tel Aviv University unveiled the first 3D bioprinted heart with human tissue including chambers, ventricles and blood vessels. Although the heart is capable of contracting, it remains a long way off from being ready for clinical trials as it cannot yet pump blood.
3D bioprinting has the potential to provide a heart or blood vessels to patients in need of transplants. The tissue would be made from their own cells, thereby considerably reducing the risk of rejection. Despite promising recent innovations, 3D bioprinting technology remains in its early days and is unlikely to become a viable therapeutic option in the near future. This will change once the technology evolves and full-sized hearts and vessels can be constructed efficiently and at scale.

Synthetic blood

For decades scientists have been trying to develop synthetic red blood cells (RBCs) that mimic the favourable properties of natural ones, such as flexibility, oxygen transport and long circulation times. Most have been met with limited success, demonstrating only one or just a few of the key properties. Now, researchers, reporting in the journal ACS Nano [1], have made synthetic RBCs that have all of the cells’ natural abilities, plus a few new ones.
Wei Zhu, C. Jeffrey Brinker and colleagues wanted to make artificial RBCs that had similar properties to natural ones, but that could also perform new jobs such as therapeutic drug delivery, magnetic targeting and toxin detection.
The researchers made the synthetic cells by first coating donated human RBCs with a thin layer of silica. They layered positively and negatively charged polymers over the silica-RBCs, and then etched away the silica, producing flexible replicas. Finally, the team coated the surface of the replicas with natural RBC membranes. The artificial cells were similar in size, shape, charge and surface proteins to natural cells, and they could squeeze through model capillaries without losing their shape. In mice, the synthetic RBCs lasted for more than 48 hours, with no observable toxicity. The researchers loaded the artificial cells with either haemoglobin, an anticancer drug, a toxin sensor or magnetic nanoparticles to demonstrate that they could carry cargoes. They also showed that the new RBCs could act as decoys for a bacterial toxin.
The researchers say future studies will explore the potential of the artificial cells in medical applications, such as cancer therapy and toxin biosensing.
Reference

1. Biomimetic Rebuilding of Multifunctional Red Blood Cells: Modular Design Using Functional Components https://pubs.acs.org/doi/abs/10.1021/acsnano.9b08714

Hand hygiene is a critical component of infection prevention in hospitals, but the unintended consequences include water splashing out of a sink to spread contaminants from dirty taps according to new research.
Researchers at the University of Michigan Health System assessed eight different designs across four intensive care units to determine how dirty sinks and taps really are. They found that a shallow depth of the sink bowl enabled potentially contaminated water to splash onto patient care items, healthcare worker hands, and into patient care spaces – at times at a distance of more than four feet (1.2 meter) from the sink itself.  
“The inside of taps where you can’t clean were much dirtier than expected,” said study author Kristen VanderElzen, MPH, CIC. “Potentially hazardous germs in and around sinks present a quandary for infection preventionists, since having accessible sinks for hand washing is so integral to everything we promote. Acting on the information we found, we have undertaken a comprehensive tap replacement program across our hospital.”
To identify the grime level of the sinks, the researchers used adenosine triphosphate (ATP) monitoring to measure the cleanliness. Visible biofilm was associated with higher ATP readings, and cultures tested over the course of the study grew Pseudomonas aeruginosa, mould, and other environmental organisms.
The research team also found aerators on sinks where they had previously been removed, pointing to an overall inconsistency of equipment protocols across the facility. Included in the design improvement program were sink guards, which were shown to limit splash significantly.
“As we learn more about the often stealthy ways in which germs can spread inside healthcare facilities, infection preventionists play an increasingly important role in healthcare facility design – including in the selection of sink and tap fixtures – as this study illustrates,” said 2019 APIC President Karen Hoffmann, RN, MS, CIC, FSHEA, FAPIC.
“Because the healthcare environment can serve as a source of resistant organisms capable of causing dangerous infections, an organization’s infection prevention and control program must ensure that measures are in place to reduce the risk of transmission from environmental sources and monitor compliance with those measures.”
APIChttps://tinyurl.com/yysdlvsb

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