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Eight new research projects that will help people self-manage chronic conditions, such as COPD and diabetes, at home while linked to support from carers and clinicians, were announced today by the Engineering and Physical Sciences Research Council (EPSRC) which is funding the work with a £10 million investment. The research will take place at seven UK universities; involve over 30 partners from industry, charities and the public sector who will add contributions worth over three quarters of a million pounds. It will explore how to improve the use and development of networks that connect patients, and those supporting them, to clinicians and treatment. It will investigate how using wearable devices like sensors, smart-watches, activity and heart rate monitors can allow clinicians to get the right sort of data to make choices and advise patients. The studies will use conditions such as COPD, rheumatoid arthritis, diabetes, and dementia as examples to test technology and systems' designs. The projects have different emphases, some will concentrate on how systems can be made more intelligent and interpret data coming into them, while others will develop and refine sensors and monitoring equipment and ensure they can be accessed securely. Professor Philip Nelson, Chief Executive of the Engineering and Physical Sciences Research Council (EPSRC), said: "The UK has an aging population and the demands on our health services are growing. Monitoring chronic conditions through outpatients' clinics is both costly and time consuming for patients, surgeries and hospitals. Using these new technologies provides ways of gauging a patient's health in real-time and detecting any deterioration quickly. This will help people remain in their homes for longer, avoid congestion and delay and mean treatment can be targeted quickly and when it can be most appropriate and effective." For further information please contact the EPSRC Press Office on 01793 444 404 or email Details of the projects are listed below: ASPIRE: Automated Sensing & Predictive Inference for Respiratory Exacerbation - Led by Professor David Clifton, University of Oxford The team proposes to develop an 'intelligent' home-based system, with smart algorithms embedded within lightweight healthcare sensors, to overcome current limitations. Its novel work will incorporate next-generation machine learning algorithms to combine information from healthcare sensors with information from GP and hospital visits. This will enable the system to learn the 'normal' health condition for individual patients, with knowledge of other conditions from which they may be suffering, and which can then make recommendations to the patient concerning self-management of their condition. PAMBAYESIAN: PAtient Managed decision-support using Bayesian networks - Led by Professor Norman Fenton, Queen Mary University of London The overall goal of the project is to create a new generation of intelligent medical decision support systems with real-time monitoring for chronic conditions, based on expert-built Bayesian Networks (BNs). The team's aim to extend current techniques for developing BNs so that they can be used in a system with several layers (sensor, patient, clinician) in a co-ordinated way. They will design systems that fit into, and improve, the interaction between patients and the healthcare team. Enable BNs to run in the computing resources available at different places in the overall system eg on small computers. They will also look towards practical applications. This project has a number of technology companies involved on the Advisory Board to help ensure effective commercial exploitation in the long run. Project Partners: Mediwise Ltd; IBM United Kingdom Limited; Rescon Technologies; uMotif Limited; SMART Medical Limited; Hasiba Medical GmbH; Be More Digital Ltd. ARISES: An Adaptive, Real-time, Intelligent System to Enhance Self-care of chronic disease - Led by Dr Pantelis Georgiou, Imperial College London This project will develop an Adaptive, Realtime, Intelligent System (ARISES) that will run on a smart phone locally and collect data from multiple sources to deliver an intervention to the patient that allows self-management of chronic disease. The core of ARISES will use Case-based reasoning (CBR), a consolidated artificial intelligence technique which can solve problems in much the same way as a human does, using historical data and scenarios as a reference to recommend a current solution which can treat the patient. CBR is also powerful in that it has the capability to be adaptive according to patient lifestyle and behaviour and always provide the most optimum solutions for a given set of resources. ARISES will have the capability to collect data from wearable devices such as smart-watches, activity monitors, heart rate monitors and continuous glucose meters and using smart-algorithms will be able to extract meaningful information to provide to the CBR system. Underpinning this will be energy efficient algorithms which make ARISES aware of what sensors are connected to the patients local area network, safety systems that minimise the risk of any possible undesired event related to the management of the disease, and a data security to make sure information is protected against non-authorised access. ARISES will provide a generic framework which can be used to treat many chronic diseases such as asthma, chronic obstructive airways disease, hypertension, heart failure, ischaemic heart disease, arrhythmias and chronic neurological conditions. The team will use diabetes, which currently affects 3 per cent of the world's population, as an exemplar chronic condition to demonstrate the ARISES framework, and will target improvement in glycaemic control which can reduce micro- and macrovascular complications associated with the disease. In this context the system will promote the self-management of diabetes by optimising glucose control through insulin dosage recommendations, exercise and physical activity support, carbohydrate recommendations to prevent hypoglycaemia, and behavioural change through education. SCAMPI: Self-Care Advice, Monitoring, Planning and Intervention - Led by Professor Neil Maiden, City, University of London The project's prime objective is to prototype a new computerised toolset to support the more seamless care planning, monitoring and interventions by people with chronic conditions and their carers. To achieve this, a team of leading researchers in computer science, the health sciences and digital business at City, University of London will co-design, prototype and evaluate the feasibility of the toolset with people with two example chronic conditions - dementia and Parkinson's disease. The researchers will work closely with the Alzheimer's Society and Parkinson's UK in order to engage people with these conditions, their families, carers and disease experts. CONSULT will combine wireless 'wellness' sensors with intelligent software running on mobile devices, to support patient decision making, and thus actively engage patients in managing their healthcare. Software will use computational argumentation to help patients follow treatment guidelines and will learn details specific to individuals, personalising treatment advice within medically sound limits. The technology will be evaluated in many ways in a proof-of-concept study, engaging stroke patients, their carers and medical professionals, while capitalising on King's College London's world-leading position in stroke research and its established patient groups, particularly those connected to the South London Stroke Register programme. The Wearable Clinic: Connecting Health, Self and Care - Led by Dr Niels Peek, The University of Manchester The research team propose to develop a set of software tools for smartphones and tablets, called the 'Wearable Clinic'. This will help patients with long term conditions, together with their carers and doctors, to better manage their health in daily life, respond more quickly to changes in symptoms and prevent fall back episodes. The project will trial methods of data collection and use that will take account of individual risk factors (eg age, ethnicity) and conserve the battery life of devices. While the Wearable Clinic concept could potentially be useful for managing a range of long term conditions, the team will test it with two different conditions, where symptoms are known to fluctuate over time: schizophrenia and chronic kidney disease. Project partners: Cerner Corporaton; Withings SAS; UK Renal Registry; Manchester Mental Health & Social Care; Nat Institute for Health and Care Excellence; Health and Social Care Information Centre; Manchester mHealth Ecosystem; Health Innovation Manchester. The STRETCH project aims to coordinate "circles" of support for older adults recovering at home following hospital treatment. These 'circles', which include relatives and neighbours, the voluntary sector, carers and medical professionals, would be coordinated through the use of both wearable and smart home technologies with the double benefit of increasing NHS capacity to cope with an increasing number of older patients, while improving care by ensuring that medical professionals have timely and accurate information at all times about patients. A Novel Wearable Technology for Early Detection of Exacerbations in COPD - Led by Professor Esther Rodriguez-Villegas - Imperial College London The aim of the project is to create a small, lightweight and low-cost novel wearable wireless technology which can be worn around the neck to monitor patients suffering from Chronic Obstructive Pulmonary Disease, currently the fourth leading cause of death in the world that affects about 3 million people in the UK. It is hoped that the devices will be able to provide early detection of potential exacerbations and inform patients and medical professionals so they can be treated promptly. It is also anticipated that the devices will reduce the cost of hospitalisations and visits to GPs, therefore resulting in savings to the NHS. As the main funding agency for engineering and physical sciences research, our vision is for the UK to be the best place in the world to Research, Discover and Innovate. By investing £800 million a year in research and postgraduate training, we are building the knowledge and skills base needed to address the scientific and technological challenges facing the nation. Our portfolio covers a vast range of fields from healthcare technologies to structural engineering, manufacturing to mathematics, advanced materials to chemistry. The research we fund has impact across all sectors. It provides a platform for future economic development in the UK and improvements for everyone's health, lifestyle and culture. We work collectively with our partners and other Research Councils on issues of common concern via Research Councils UK. http://www.

Udayaraj U.,Southmead Hospital | Pruthi R.,UK Renal Registry | Casula A.,UK Renal Registry | Roderick P.,University of Southampton
Nephron - Clinical Practice | Year: 2014

Introduction: This chapter describes the patient characteristics and outcomes for the three main ethnic groups (White, South Asian, Black) on renal replacement therapy (RRT) in the UK. Methods: Data on patients (>18 years old) from all 71 UK adult renal centres starting RRT between 2003 and 2012 were considered. Scottish centres were excluded due to poor ethnicity data. Results: The age-gender standardized incidence ratio of RRT was higher (2-3 times) in regions with a high ethnic minority population compared to those with a low ethnic minority population. South Asian and Black patients were significantly younger than Whites; had more diabetes causing established renal failure and lived in more deprived areas. The proportion of patients with at least one comorbidity was greater amongst White patients compared to South Asian and Black patients. The proportion of patients starting PD and having preemptive transplantation was lower amongst both ethnic minorities. The attainment of various laboratory standards was comparable or better for the ethnic minorities compared to White patients except for calcium standard attainment (for South Asians) and haemodialysis dose attainment (for Black patients). Compared to White patients, both ethnic minorities had similar rates of listing for deceased donor kidney transplantation but had lower rates of transplantation once wait-listed, and lower rates of living kidney donor transplantation. One and five year kidney allograft adjusted survival was poorer for Black patients but similar for South Asians compared to White patients. Black and South Asian patients had a better adjusted survival on dialysis compared to White patients. Conclusions: The persistent high incidence of RRT, the better survival on dialysis and the poor access to kidney transplantation for South Asian and Black patients and early allograft loss for Black patients will impose a disproportionate demand on dialysis provision in those areas with a high ethnic minority population. © 2014 S. Karger AG, Basel.

Crowley L.,Royal Derby Hospital | Wilson J.,Imperial Healthcare NHS Trust | Guy R.,National Infections Surveillance Center | Pitcher D.,UK Renal Registry | Fluck R.,Royal Derby Hospital
Nephron - Clinical Practice | Year: 2012

Introduction: Infection remains one of the leading causes of death in patients with end-stage renal failure (ESRF) receiving dialysis. Since April 2007, all centres providing renal replacement therapy in England have been required to provide additional data on patients with Methicillin Resistant Staphylococcus Aureus (MRSA) infection. From January 2011 this has also been required for patients with Methicillin Sensitive Staphylococcus Aureus (MSSA). MRSA data for 2009-2011 and the rst 6 months of MSSA data are reported. Methods: Potential bacteraemia were identied by the Health Protection Agency based on clinical details provided and the clinical setting. The records were 'shared' with the parent renal centre who then complete the additional data on the HCAI-DCS website. Centres were also contacted by phone and email as a further validation step. Results: From April 2009-2010 there were 77 conrmed episodes of MRSA bacteraemia at a median rate of 0.25 per 100 prevalent dialysis patients. This number decreased to 61 episodes between April 2010-2011 at a median rate of 0 per 100 prevalent dialysis patients. Overall there has been an 82% reduction in absolute episodes since the rst year of mandatory reporting in 2007. The incidence of bacteraemia in patients with a central venous catheter was approximately six fold higher than in those with an AV stula. From 1st January to 30th June 2011 there were 160 episodes of MSSA bacteraemia with a rate of 1.06 episodes per 100 dialysis patients, again the risk was six fold higher in patients with a CVC. Conclusions: Overall rates of MRSA bacteraemia in dialysis patients continued to fall although there remained variation between renal centres. Initial data from the early days of MSSA reporting suggested high rates of infection and an even greater variation between renal centres. This requires conrmation from future data collection. © 2012 S. Karger AG, Basel.

Crowley L.,Royal Derby Hospital | Pitcher D.,UK Renal Registry | Wilson J.,University of West London | Guy R.,Center for Infectious Disease Surveillance and Control | Fluck R.,Royal Derby Hospital
Nephron - Clinical Practice | Year: 2014

Introduction: Infection remains one of the leading causes of mortality in established renal failure patients receiving renal replacement therapy (RRT). Since 2007, centres providing RRT in England have been asked to provide additional data on patients with methicillin resistant Staphylococcus aureus (MRSA) bacteraemia. Since 2011, the option to provide data on methicillin sensitive Stapylococcus aureus (MSSA) and Escherichia coli bacteraemia, as well as Clostridium difficile infection has also been available. Methods: Data were submitted to Public Health England by laboratories via HCAI-DCS including whether the patients were receiving dialysis. Individual renal centres then confirmed the record either directly via the database or after being contacted. Data were collected for the period of the 1st May 2011 to the 30th April 2012. Results: There were 49 episodes of MRSA bacteraemia, an overall rate of 0.22 per 100 dialysis patients per year, representing a further year on year fall in MRSA rate. There were a higher number of MSSA episodes, 322 in total, with an overall rate of 1.15 per 100 dialysis patients per year. The number of episodes and overall rate of E. coli and C. difficile were 284 and 0.92 per 100 prevalent dialysis patients per year and 172 and 0.61 per 100 prevalent dialysis patients per year respectively. In each infection type the presence of a central venous catheter appeared to correlate with an elevated risk. Conclusions: Data are presented from one year of infections reported to PHE. The rate of MRSA bacteraemia episodes in England continues to fall. There was a higher rate of MSSA infections amongst renal dialysis patients. Findings from the first year of E. coli and C. difficile data collection are also reported. Future cycles will give us a further idea of the trend in incidences of these infections. © 2014 S. Karger AG, Basel.

Tomson C.R.,UK Renal Registry
Nephron. Clinical practice | Year: 2010

The 12th Annual Report from the UK Renal Registry (UKRR) contains analyses of data submitted from every centre providing clinical supervision of renal replacement therapy (RRT) in England, Wales, Northern Ireland and (via the Scottish Renal Registry) Scotland. The data are largely extracted direct from clinical information systems used for direct clinical care [1] and the inclusion of laboratory data permit analyses not only of the incidence, prevalence, and outcomes of RRT in the UK, but also the achievement of clinical performance measures as defined by the Renal Association's Clinical Practice Guidelines. The UKRR remains unique amongst renal registries in not only publishing centre-specific analyses of outcomes, including laboratory variables but also including age-adjusted survival statistics. Data are still incomplete, particularly on those data items that require clinical input, including primary renal disease and comorbidity at the start of RRT, and these deficiencies limit the Registry's ability to perform analyses that are fully adjusted for case-mix. In England, the issue of a Dataset Change Notice [2] has made submission of a defined dataset on each patient undergoing RRT mandatory, but how quickly this will accelerate improvement in data returns remains to be determined. (c) 2010 S. Karger AG, Basel.

A preliminary review of the UK Renal Registry (UKRR) pre-RRT study data revealed results suggesting that, for some patients, the date of start of renal replacement therapy (RRT), as reported to the UKRR, was incorrect and often significantly later than the true date of start. A more detailed study then aimed to validate a set of criteria to identify patients with an incorrect start date. Pre-RRT laboratory data were electronically extracted from 8,810 incident RRT patients from 9 UK renal centres. Any patient with a low urea (<15 mmol/L) at the start of RRT or with a substantial improvement in kidney function (either a fall in urea >10 mmol/L or rise in eGFR >2 ml/ min/1.73 m) within the two months prior to RRT were considered to potentially have an incorrect date of start. In 4 selected centres, the electronic patient records of all patients flagged were reviewed to validate these criteria. Of 8,810 patients, 1,616 (18.3%) were flagged by the identification criteria as having a potentially incorrect date of start of RRT, although a single centre accounted for 41% of the total flagged cohort. Of these flagged patients, 61.7% had been assigned an incorrect date of start of haemodialysis (HD), 5.7% had evidence of acute RRT being given before the reported date of start of HD and 9.2% had evidence of starting peritoneal dialysis exchanges prior to the reported date of start. Of those flagged, 10.7% had a correct date of start of RRT. Accurate reporting of RRT episodes is vital for the analysis of time dependent studies such as survival or time to transplantation. A proportion of patients starting RRT were assigned an incorrect start date. In order to improve the accuracy of this reporting the UK Renal Registry must work with renal centres and clinical staff on improving data input for the start of RRT. (c) 2010 S. Karger AG, Basel.

Gilg J.,UK Renal Registry
Nephron. Clinical practice | Year: 2012

This chapter describes the characteristics of adult patients starting renal replacement therapy (RRT) in the UK in 2010 and the incidence rates for RRT in Primary Care Trusts and Health Boards (PCT/HBs) in the UK. The basic demographics and clinical characteristics are reported on patients starting RRT from all UK renal centres. Presentation time, defined as time between first being seen by a nephrologist and start of RRT, was also studied. Age and gender standardised ratios for incidence rates in PCT/HBs were also calculated. In 2010, the incidence rates in the UK and England were similar to 2009 at 107 per million population (pmp). The incidence rate fell in Scotland (from 104 pmp to 95 pmp), increased in Northern Ireland (from 88 pmp to 101 pmp) and Wales (from 120 pmp to 128 pmp). There were wide variations between PCT/HBs in standardised incidence ratios. The median age of all incident patients was 64.9 years (IQR 51.0, 75.2). For transplant centres this was 63.1 years (IQR 49.7, 74.2) and for non-transplanting centres 66.5 years (IQR 52.9, 76.0). The median age for non-Whites was 57.1 years. Diabetic renal disease remained the single most common cause of renal failure (24%). By 90 days, 68.3% of patients were on haemodialysis, 18.1% on peritoneal dialysis, 7.7% had had a transplant and 5.9% had died or stopped treatment. The mean eGFR at the start of RRT was 8.7 ml/ min/1.73 m(2) which was similar to the previous three years. Late presentation (<90 days) fell from 28.2% in 2005 to 20.6% in 2010. There was no relationship between social deprivation and presentation pattern. Incidence rates have plateaued in England over the last five years. They have fallen in Scotland and fallen and then risen again in Northern Ireland and Wales. Wales continued to have the highest incidence rate of the countries making up the UK. Copyright © 2012 S. Karger AG, Basel.

Castledine C.,UK Renal Registry
Nephron. Clinical practice | Year: 2012

This chapter describes the characteristics of adult patients on renal replacement therapy (RRT) in the UK in 2010. Data were electronically collected from all 72 renal centres within the UK. Cross-sectional and longitudinal analyses were performed to describe the demographics of prevalent RRT patients in 2010 at centre and national level. Age and gender standardised ratios for prevalence rates per million population per year were calculated. There were 50,965 adult patients receiving RRT in the UK on 31st December 2010. The UK prevalence of RRT (including paediatric patients) was 832 pmp. This represented an annual increase in prevalent numbers of approximately 4% although there was significant variation between centres and regions. From 2009 to 2010 there was a 1.5% increase in the number of patients on haemodialysis (HD), a 3.2% fall in peritoneal dialysis (PD) patients and a 5.4% increase in patients with a functioning transplant. The number of patients receiving home HD has increased 23% since 2009. Median RRT vintage was 5.6 years. The median age was 57.9 years (HD 66.3 years, PD 61.7 years and transplant 51.2 years) compared to 55 years in 2000. Prevalence rates in males exceeded those in females. The most common identifiable renal diagnosis was biopsyproven glomerulonephritis (16.0%), followed by diabetes (14.9%). Transplantation was the most common treatment modality (48%), HD in 44% and PD 8%. The HD and transplant population continued to expand whilst the PD population contracted. There were national, regional and dialysis centre level variations in prevalence rates. Prevalent patients were on average 4 years older than 10 years ago. This has implications for service planning and ensuring equity of care for RRT patients. Copyright © 2012 S. Karger AG, Basel.

A total of 917 children and young people under 18 years with established renal failure (ERF) were receiving treatment at paediatric nephrology centres in 2014.At the census date (31st December 2014), 79.3% of prevalent paediatric patients aged ,18 years had a functioning kidney transplant, 11.2% were receiving haemodialysis (HD) and 9.5% were receiving peritoneal dialysis (PD). In patients aged ,16 years, prevalence of ERF was 60.4 per million age related population (pmarp) and the incidence 9.4 pmarp. The most common primary renal diagnosis was renal dysplasia+reflux, present in 32.6% of prevalent paediatric patients aged ,16 years. About a third of patients had one or more reported comorbidity at onset of renal replacement therapy (RRT). The improvement in rates of pre-emptive transplantation for those referred early has been maintained over the last 10 years at 37.5%, compared to 27.4% in 20002004. At transfer to adult services, 90.3% of patients had a functioning kidney transplant. Survival during childhood amongst children commencing RRT was the lowest in those aged less than two years compared to those aged 12 to less than 16 years with a hazard ratio of 4.1 (confidence interval 2.28.0), and in those receiving dialysis compared to having a functioning transplant with a hazard ratio of 6.3 (confidence interval 3.910.2).

MacDougall I.C.,King's College | Tomson C.R.V.,UK Renal Registry | Steenkamp M.,UK Renal Registry | Ansell D.,UK Renal Registry
Nephrology Dialysis Transplantation | Year: 2010

Background. Much controversy has been generated in recent times over the optimal target haemoglobin in chronic kidney disease patients receiving erythropoiesis-stimulating agent therapy. This has arisen from the paradoxical conclusions obtained from large retrospective or epidemiological studies versus interventional randomized controlled trials.Methods. Data from haemodialysis patients in the UK Renal Registry from 1999 to 2005 were analysed year by year for the relative risk of death at different haemoglobin concentrations, compared with a reference of 10-11 g/dl. The population size varied from 2291 in 1999 to 8209 in 2005. The data were analysed by chi-square tests, and a multivariate analysis was performed.Results. Across the years 1999 to 2005, there was a consistent relationship between the haemoglobin achieved and the risk of death (P < 0.0001). In 2005, the relative risk (RR) of death = 1.32 for a haemoglobin (Hb) of 9-10 g/dl; RR = 0.44 for Hb > 13 g/dl. The relationship between Hb and the RR of death is nevertheless remarkably consistent across the 7 years of study, with an S-shaped correlation (polynomial) between an Hb range of <9 g/dl and an Hb range of >13 g/dl (P < 0.0001). Multivariate analysis also showed age, time on dialysis and diabetes to be strongly predictive of death across all 7 years analysed (P < 0.0001 in all cases).Conclusion. There is a significant relationship between achieved haemoglobin and mortality across the 7 years analysed, with no increase in risk seen with higher Hb levels.

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