̽��ֱ�� of Cambridge - Cambridge Mathematics of Information in Healthcare

Heart surgery delays will cost lives, warns research

sc604 — Fri, 17 Jun 2022 09:19:34 +0000

Urgent action is needed to clear the backlog of people with a common heart condition who are waiting for lifesaving treatment, according to research published in the journal BMJ Open. ̽��ֱ��researchers have warned that a lack of action could result in thousands of people dying while waiting for treatment.

̽��ֱ��COVID-19 pandemic has led to thousands of heart procedures being postponed and record waiting lists. Previous work has estimated that 4,989 people in England with severe aortic stenosis missed out on life-saving treatment between March and November 2020.

Aortic stenosis develops when the heart’s aortic valve becomes narrowed, restricting blood flow out of the heart. Prompt treatment is vital for people diagnosed with severe aortic stenosis, as around 50 percent will die within two years of symptoms beginning.

Now, an international team of researchers, including from the ̽��ֱ�� of Cambridge, has modelled the impact that increasing treatment capacity and using a quicker, less invasive treatment option would have on waiting lists. Even in the best-case scenario, they found that the waiting list would take nearly a year to clear and over 700 people would die while waiting for treatment. ̽��ֱ��research was funded by the British Heart Foundation and the EPSRC Cambridge Centre for Mathematics of Information in Healthcare.

̽��ֱ��traditional treatment for aortic stenosis involves replacing the narrowed valve, most commonly through open-heart surgery (a surgical aortic valve replacement, SAVR). However, a newer keyhole procedure called a transcatheter aortic valve implantation (TAVI) is increasingly being used and is now recommended for patients aged 75 and over.

̽��ֱ��researchers investigated the impact that increasing treatment capacity and converting a proportion of operations to the quicker TAVI procedure would have on the backlog. They looked at how long it would take to clear the backlog and the number of people who would die while waiting for treatment.

They found that the best and most achievable option involved a combination of increasing capacity by 20 percent and converting 40 percent of procedures from SAVR to TAVI. This would clear the backlog within 343 days with 784 deaths while people wait for treatment.

“This simple yet relevant model tackles the critical question of how to clear waiting lists and is easy to interpret in practice,” said study co-author Professor Houyuan Jiang from Cambridge Judge Business School.

̽��ֱ��team say they want to see greater collaboration at local and national levels to agree the changes needed that can ensure that people with severe aortic stenosis receive life-saving treatment as quickly as possible.

Before the pandemic around 13,500 SAVR and TAVI procedures were performed each year across the UK. Increasing capacity by 20 percent would represent one or two additional TAVI procedures each week per centre.

“We think that with local and national collaboration this increase is achievable,” said study co-author Professor Mamas Mamas from Keele ̽��ֱ��. “Furthermore, we have created an algorithm that NHS Trusts can use to work out the best approach locally.

“Since November 2020 the UK has been hit with further waves of COVID-19 which have led to extreme pressure on the NHS and additional delays to treatment. We expect that number of people waiting for treatment in recent months will be even higher than the figure we used in our study. Doing nothing is simply not an option. If we continue as we are currently thousands of people will die from untreated aortic stenosis.”

“Our approach does not put the onus on only management or doctors, but creates a joint solution that is easier to implement in practice,” said co-author Professor Feryal Erhun, from Cambridge Judge Business School.

“As this modelling study shows, even increased use of this quicker and less invasive procedure won’t be enough to overcome the impact of COVID-19 related delays and stop people with aortic stenosis dying while waiting for treatment,” said Dr Sonya Babu-Narayan, Associate Medical Director at the British Heart Foundation and consultant cardiologist. “Cardiac care can’t wait. ̽��ֱ��NHS desperately needs additional resources to help it tackle the backlog of care and ensure that heart patients receive the treatment and care they need.”

Reference:
Christian Philip Stickels et al. 'Aortic stenosis post-COVID-19: a mathematical model on waiting lists and mortality.' BMJ Open (2022). DOI: 10.1136/bmjopen-2021-059309

Adapted from a BHF press release.

Pandemic has delayed lifesaving treatment for thousands of people with severe aortic stenosis.

Our approach does not put the onus on only management or doctors, but creates a joint solution that is easier to implement in practice

Feryal Erhun

Thierry Dosogne via Getty Images

Surgeons performing heart surgery

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Trinity Challenge announces inaugural winners

Anonymous — Fri, 25 Jun 2021 14:43:12 +0000

̽��ֱ��eight winners have been selected by an international panel of expert judges, out of a total of 340 applications from 61 countries. ̽��ֱ��competition has seen unprecedented collaborations between the private, public, charitable and academic sectors, and will drive a step-change in using data and analytics for pandemic preparedness.

̽��ֱ�� ̽��ֱ�� of Cambridge joined a coalition of some of the world’s leading businesses and academic and tech institutions to launch ̽��ֱ��Trinity Challenge in September 2020. ̽��ֱ��global challenge, convened by Dame Sally Davies, Master of Trinity College, provides a £10m prize fund for breakthrough solutions to make sure one billion more people are better protected against health emergencies.

Participatory One Health Disease Detection (PODD), which empowers farmers to identify and report zoonotic diseases that could potentially pass from animals to humans, has been named the grand prize winner at the inaugural awards ceremony. ̽��ֱ��organisation is being awarded £1.3 million (US$1.8 million) in pledged funding.

Led by Susumpat Patipow, General Director at OpenDream, PODD has developed a platform for livestock owners to report suspected animal illness, and in return receive veterinary care to improve animal health. If it appears a disease outbreak is likely, local health officials will quarantine the sick animals, saving the remaining livestock and possibly preventing the next COVID-19-type outbreak.

Having already achieved significant success in Thailand, with a network of 20,000 farmers helping to detect and control disease outbreaks, PODD is looking to expand its operations to Cambodia, India, Indonesia, Laos, Uganda and Vietnam over the next three years.

BloodCounts! - an international consortium of scientists, led by Professor Carola-Bibiane Schönlieb from Cambridge’s Department of Applied Mathematics and Theoretical Physics (DAMTP) that has developed an innovative infectious disease outbreak detection system, was one of two second-prize winners, each awarded £1 million in pledged funding.

Developed by Dr Michael Roberts and Dr Nicholas Gleadall, the BloodCounts! Solution uses data from routine blood tests and powerful AI-based techniques to provide a ‘tsunami-like’ early warning system for new disease outbreaks.

“Since the beginning of the pandemic I have been developing AI-based methods to aid in medical decision making for COVID-19 patients, starting with analysis of Chest X-ray data,” said Roberts, who is affiliated with DAMTP and the Cambridge Mathematics of Information in Healthcare (CMIH) Hub. “Echoing the observations made by the clinical teams, we saw profound and unique differences in the medical measurements of infected individuals, particularly in their full blood count data. It is these changes that we can train models to detect at scale.”

Unlike many current test methods, their approach doesn't require any prior knowledge of a specific pathogen to work, instead, they use full blood count data to exploit the pathogen detecting abilities of the human immune system by observing changes in the blood measurements associated with infection.

As the full blood count is the world’s most common medical laboratory test, with over 3.6 billion being performed worldwide each year, the BloodCounts! team can rapidly apply their methods to scan for abnormal changes in the blood cells of large populations - alerting public health agencies to potential outbreaks of pathogen infection.

This solution is a demonstration of how the application of AI-based methods can lead to healthcare benefits. It also highlights the importance of strong collaboration between leading organisations, as the development of these algorithms was only possible due the EpiCov data sharing initiative pioneered by Cambridge ̽��ֱ�� Hospitals.

“Hundreds of millions of full blood count tests are being performed every day worldwide, and this meant that we could apply our AI methods at population scale,” said Gleadall, from the ̽��ֱ�� of Cambridge and NHS Blood and Transplant. “Usually the rich measurement data are discarded after summary results have been reported, but by working with Cambridge ̽��ֱ��, Barts Health London, and ̽��ֱ�� College London NHS Hospitals we have rescued throughout the pandemic the rich data from 2.8 million full blood count tests.”

̽��ֱ��Sentinel Forecasting System is the other second-prize winner, and will explore the emergence of new infectious diseases in West Africa, beginning with Lassa fever. ̽��ֱ��system will combine data from ecology, social science, genomics and epidemiology to provide real-time disease risk for haemorrhagic fevers, such as Lassa and Ebola.

Lassa is a virus usually passed to humans through exposure to food or household items contaminated by infected rats. It is endemic in West African countries including Benin, Ghana, Guinea, Liberia, Mali, Sierra Leone, Togo and Nigeria.

Around 80% of people who become infected with Lassa virus have no symptoms, and the overall case-fatality rate is 1%. 1 in 5 infections can result in severe disease affecting the liver, spleen and kidneys.

̽��ֱ��UCL team will partner with the African Centre of Excellence for Genomics of Infectious Diseases in Nigeria, Nigeria Centre for Disease Control, Zoological Society of London, London School of Hygiene and Tropical Medicine, Microsoft, and Cambridge’s Laboratory of Viral Zoonotics (LVZ) to produce the system.

“This Trinity Challenge project brings new multidisciplinary technologies together to anticipate climatic, human, animal population, agricultural impacts on the likelihood of spill overs of infections from animals to humans,” said Professor Jonathan Heeney, who leads LVZ at Cambridge’s Department of Veterinary Medicine.

Additionally, five 3rd prize winners are each being awarded £480,000 (US$ 660,000) in pledged funding.

Dame Sally Davies said: “It was crystal clear at the beginning of this pandemic that the world had a lack of data, a lack of access to data, and a lack of interoperability of data, presenting a challenge. While others talked, we took action. ̽��ֱ��solutions we have discovered in the course of the Challenge will be a link between systems and countries.”

In addition to financial support, ̽��ֱ��Trinity Challenge will provide connections to the right organisations to maximise the impact of these solutions. Since its inception nine months ago, TTC has united early applicants with partners from the private, academic and social sectors to receive access to digital platforms, data, and technical advice, to scale-up the use of data and analytics to protect the world from future health emergencies. ̽��ֱ��Trinity Challenge has helped form over 200 connections between applicants and its members.

̽��ֱ��Trinity Challenge has announced the winners of its inaugural competition, and is investing a £5.7 million (US$8 million) charitable pledged prize fund into one grand prize winner, two 2nd prize winners, and five 3rd prize winners.

While others talked, we took action. ̽��ֱ��solutions we have discovered in the course of the Challenge will be a link between systems and countries

Dame Sally Davies

̽��ֱ��Trinity Challenge

Collage of Trinity Challenge finalists

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