536 results match your criteria: "Leicester Diabetes Centre[Affiliation]"

Objective: The associated risk of vascular disease following diagnosis of type 2 diabetes in people previously identified as having pre-diabetes in real-world settings is unknown. We examined the presence of microvascular and macrovascular disease in individuals with newly diagnosed type 2 diabetes by glycemic status within 3 years before diagnosis.

Research Design And Methods: We identified 159 736 individuals with newly diagnosed type 2 diabetes from the UK Clinical Practice Research Datalink database in England between 2004 and 2017.

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Structured diabetes education (SDE) is an evidence-based intervention that supports self-management in people with type 2 diabetes. In the United Kingdom, health care providers working in primary care settings are responsible for referring people with type 2 diabetes to SDE programs. However, national audits record a high percentage of nonattenders.

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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 or COVID-19) has been declared a pandemic by the World Health Organization and sent all countries scrambling to review emergency healthcare provisions. There is global evidence of each nation struggling to effectively manage the number of people being diagnosed with the virus. These are testing times which have not been experienced in recent generations and there are a number of insecurities regarding the management of people with COVID-19 and cardiometabolic diseases.

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Use of incretin-based medications: what do current international recommendations suggest with respect to GLP-1 receptor agonists and DPP-4 inhibitors?

Metabolism

June 2020

Department of Clinical & Experimental Medicine, Section of Diabetes & Metabolic Diseases, University of Pisa, Pisa, Italy. Electronic address:

In recent years guidelines for the treatment of type 2 diabetes (T2DM) have evolved substantially. Initially limited to a few glucose lowering agents, early guidelines predicated strict glycemic control as a main goal in the attempt to reduce the risk of long-term diabetic complications. Nowadays, guidelines are not limited to such a goal but include cardiovascular (and renal) protection.

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The last decade has witnessed an exponential growth in the opportunities to collect and link health-related data from multiple resources, including primary care, administrative, and device data. The availability of these "real-world," "big data" has fuelled also an intense methodological research into methods to handle them and extract actionable information. In medicine, the evidence generated from "real-world data" (RWD), which are not purposely collected to answer biomedical questions, is commonly termed "real-world evidence" (RWE).

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Further case for cohort studies of non-communicable diseases in sub-Saharan Africa.

Nutr Metab Cardiovasc Dis

June 2020

Leicester Diabetes Centre, Leicester General Hospital, Gwendolen Road, Leicester, LE5 4WP, UK; Diabetes Research Centre, University of Leicester, Leicester General Hospital, Gwendolen Road, Leicester, LE5 4WP, UK.

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Uses and Limitations of the Restricted Mean Survival Time: Illustrative Examples From Cardiovascular Outcomes and Mortality Trials in Type 2 Diabetes.

Ann Intern Med

April 2020

Leicester Real World Evidence Unit and Diabetes Reasearch Centre, Leicester Diabetes Centre, Leicester General Hospital, Leicester, United Kingdom (D.E.K., K.K., F.Z.).

The restricted mean survival time (RMST) has been advocated as an alternative or a supplement to the hazard ratio for reporting the effect of an intervention in a randomized clinical trial. The RMST difference allows quantification of the postponement of an outcome during a specified (restricted) interval and corresponds to the difference between the areas under the 2 survival curves for the intervention and control groups. This article presents examples of the use of the RMST in a research and a clinical context.

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FilterK: A new outlier detection method for k-means clustering of physical activity.

J Biomed Inform

April 2020

School of Mathematics and Actuarial Science, University of Leicester, University Road, Leicester LE1 7RD, UK.

In this paper, a new algorithm denoted as FilterK is proposed for improving the purity of k-means derived physical activity clusters by reducing outlier influence. We applied it to physical activity data obtained with body-worn accelerometers and clustered using k-means. We compared its performance with three existing outlier detection methods: Local Outlier Factor, Isolation Forests and KNN using the ground truth (class labels), average cluster and event purity (ACEP).

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Aim: To examine the influence of sociodemographic factors of interest on preference for a particular health education format among people with type 2 diabetes and/or cardiovascular disease.

Methods: A questionnaire was used to collect information on the influence of six sociodemographic factors of interest on the preference for health education formats in people with type 2 diabetes and/or cardiovascular disease. Chi-squared tests were used to examine the distribution of preferences between groups.

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A Cost and Cost-Benefit Analysis of the Stand More AT Work (SMArT Work) Intervention.

Int J Environ Res Public Health

February 2020

Diabetes Research Centre, University of Leicester, Leicester General Hospital, Leicester LE5 4PW, UK.

This study conducted a cost and cost-benefit analysis of the Stand More AT (SMArT) Work workplace intervention, designed to reduce sitting time. The study was a cluster two-armed randomised controlled trial involving 37 office clusters (146 desk-based workers) in a National Health Service Trust. The intervention group received a height-adjustable workstation with supporting behaviour change strategies.

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As a consequence of responding to colleagues who asked about the publication of the original article [1], the authors have determined that the data published in Table 4 of the paper are incorrect.

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Type 2 Diabetes (T2D) is increasing but the effectiveness of large-scale diabetes screening programmes is debated. We assessed associations between coverage of a national cardiovascular and diabetes risk assessment programme in England (NHS Health Check) and detection and management of incident cases of non-diabetic hyperglycaemia (NDH) and T2D. Retrospective analysis employing propensity score covariate adjustment method of prospectively collected data of 348,987 individuals aged 40-74 years and registered with 455 general practices in England (January 2009-May 2016).

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Aim: To develop and internally validate prognostic models on the long-term durability of glycaemic control in patients with type 2 diabetes after metformin failure.

Materials And Methods: DISCOVER is a 3-year, prospective observational study across six continents investigating second-line glucose-lowering therapies. In this analysis from 35 countries, we included patients on metformin initiating second-line glucose-lowering medication(s) because of physician-defined lack of efficacy.

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Aims: Muslims can choose to fast during Ramadan. Guidelines exist for providing clinical support for this group, but there is a lack of culturally tailored diabetes management interventions to provide guidance. The study evaluates the implementation of a programme developed to meet this need.

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Introduction: Heavy goods vehicle (HGV) drivers exhibit higher than nationally representative rates of obesity, and obesity-related comorbidities, in comparison to other occupational groups. Their working environments are not conducive to a healthy lifestyle, yet there has been limited attention to health promotion efforts. We have developed a Structured Health Intervention For Truckers (the SHIFT programme), a multicomponent, theory-driven, health-behaviour intervention targeting physical activity, diet and sitting in HGV drivers.

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Background: Diabetes mellitus, largely type 2, affects nearly 10% of the global adult population according to the World Health Organization. Diabetes is an independent risk factor for atherosclerotic cardiovascular diseases, including coronary artery disease. Diabetes patients experience a two to three-fold increased incidence of coronary artery disease, despite improved metabolic control and management of other cardiovascular risk factors.

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The inverse association between physical activity and arterial thrombotic disease is well established. Evidence on the association between physical activity and venous thromboembolism (VTE) is divergent. We conducted a systematic review and meta-analysis of published observational prospective cohort studies evaluating the associations of physical activity with VTE risk.

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Introduction: A person's chronotype is their entrained preference for sleep time within the 24 hours clock. It is described by the well-known concept of the 'lark' (early riser) and 'owl' (late sleeper). Evidence suggests that the 'owl' is metabolically disadvantaged due to the standard organisation of our society which favours the 'lark' and places physiological stresses on this chronotype.

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Objective: To assess weight and HbA changes in the Healthier You: National Health Service Diabetes Prevention Programme (NHS DPP), the largest DPP globally to achieve universal population coverage.

Research Design And Methods: A service evaluation assessed intervention effectiveness for adults with nondiabetic hyperglycemia (HbA 42-47 mmol/mol [6.0-6.

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Background: Approximately 425 million people globally have diabetes, with ~ 90% of these having Type 2 Diabetes Mellitus (T2DM). This is a condition that leads to a poor quality of life and increased risk of serious health complications. Structured self-management education (SSME) has been shown to be effective in improving glycaemic control and patient related outcome measures and to be cost-effective.

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Background: Impaired glucose tolerance (IGT) is associated with increased cardiovascular morbidity and mortality. Enhanced thromboxane (TX)-dependent platelet activation plays a pivotal role in atherothrombosis and characterizes type 2 diabetes mellitus (DM). Whether this also pertains to IGT is currently unknown.

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Towards a Portable Model to Discriminate Activity Clusters from Accelerometer Data.

Sensors (Basel)

October 2019

Diabetes Research Centre, University of Leicester, Leicester General Hospital, Gwendolen Road, Leicester LE5 4PW, UK.

Few methods for classifying physical activity from accelerometer data have been tested using an independent dataset for cross-validation, and even fewer using multiple independent datasets. The aim of this study was to evaluate whether unsupervised machine learning was a viable approach for the development of a reusable clustering model that was generalisable to independent datasets. We used two labelled adult laboratory datasets to generate a k-means clustering model.

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