911 research outputs found

    Development and evaluation of an intelligent handheld insulin dose advisor for patients with Type-1 diabetes

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    Diabetes mellitus is an increasingly common, chronic, incurable disease requiring careful monitoring and treatment so as to minimise the risk of serious long-term complications. It has been suggested that computers used by healthcare professionals and/or patients themselves may playa useful role in the diabetes care process. Seven key systems (AIDA, ADICOL, DIABETES, DIAS, IIumaLink, T-IDDM, POIRO) in the area of diabetes decision support, and their underlying techniques and approaches are summarised and compared. The development of the Patient-Oriented Insulin Regimen Optimiser (POIRO) for insulindependent (Type-I) diabetes, and its hybrid statistical and rule-based expert system is then taken forward. The re-implementation and updating of the system for the Palm OS family of modern Personal Digital Assistants (PDAs) is described. The evaluation of this new version in a seven week, randomised, open, cross-over clinical pilot study involving eight patients on short-acting plus long-acting insulin basalbolus regimens showed it to be easy-to-operate, reliable, not time consuming and well liked by patients. Following this, the characteristics and use of all currently available insulin formulations, and the corresponding insulin regimens are summarised. Algorithms to provide dose advice and decision support for patients taking the new rapid-acting, intermediate-acting and premixed insulin formulations are then developed. The user interface is improved and extended, amongst others through the development and use of a model describing individual user's meal time habits. Implementation-related issues encountered are discussed, and further work and future directions are identified and outlined. Motivated by the complex and safety-critical nature of systems such as POIRO, we also report on the use of the B abstract machine notation for the formal specification of the original POIRO system, and focusing on projects and published case studies. review the use of formal methods in the development of medical computer systems

    Generalizable automated pixel-level structural segmentation of medical and biological data

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    Over the years, the rapid expansion in imaging techniques and equipments has driven the demand for more automation in handling large medical and biological data sets. A wealth of approaches have been suggested as optimal solutions for their respective imaging types. These solutions span various image resolutions, modalities and contrast (staining) mechanisms. Few approaches generalise well across multiple image types, contrasts or resolution. This thesis proposes an automated pixel-level framework that addresses 2D, 2D+t and 3D structural segmentation in a more generalizable manner, yet has enough adaptability to address a number of specific image modalities, spanning retinal funduscopy, sequential fluorescein angiography and two-photon microscopy. The pixel-level segmentation scheme involves: i ) constructing a phase-invariant orientation field of the local spatial neighbourhood; ii ) combining local feature maps with intensity-based measures in a structural patch context; iii ) using a complex supervised learning process to interpret the combination of all the elements in the patch in order to reach a classification decision. This has the advantage of transferability from retinal blood vessels in 2D to neural structures in 3D. To process the temporal components in non-standard 2D+t retinal angiography sequences, we first introduce a co-registration procedure: at the pairwise level, we combine projective RANSAC with a quadratic homography transformation to map the coordinate systems between any two frames. At the joint level, we construct a hierarchical approach in order for each individual frame to be registered to the global reference intra- and inter- sequence(s). We then take a non-training approach that searches in both the spatial neighbourhood of each pixel and the filter output across varying scales to locate and link microvascular centrelines to (sub-) pixel accuracy. In essence, this \link while extract" piece-wise segmentation approach combines the local phase-invariant orientation field information with additional local phase estimates to obtain a soft classification of the centreline (sub-) pixel locations. Unlike retinal segmentation problems where vasculature is the main focus, 3D neural segmentation requires additional exibility, allowing a variety of structures of anatomical importance yet with different geometric properties to be differentiated both from the background and against other structures. Notably, cellular structures, such as Purkinje cells, neural dendrites and interneurons, all display certain elongation along their medial axes, yet each class has a characteristic shape captured by an orientation field that distinguishes it from other structures. To take this into consideration, we introduce a 5D orientation mapping to capture these orientation properties. This mapping is incorporated into the local feature map description prior to a learning machine. Extensive performance evaluations and validation of each of the techniques presented in this thesis is carried out. For retinal fundus images, we compute Receiver Operating Characteristic (ROC) curves on existing public databases (DRIVE & STARE) to assess and compare our algorithms with other benchmark methods. For 2D+t retinal angiography sequences, we compute the error metrics ("Centreline Error") of our scheme with other benchmark methods. For microscopic cortical data stacks, we present segmentation results on both surrogate data with known ground-truth and experimental rat cerebellar cortex two-photon microscopic tissue stacks.Open Acces

    Aerospace Medicine and Biology: A continuing bibliography with indexes, supplement 127, April 1974

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    This special bibliography lists 279 reports, articles, and other documents introduced into the NASA scientific and technical information system in March 1974

    M-CDS: Mobile Carbohydrate Delivery System

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    When patients with type 1 diabetes (T1D) are physically active, they encounter an issue with keeping their blood glucose (BG) stable. Generally, their blood glucose level (BGL) will drop, causing hypoglycaemia which can have fatal consequences. The simple solution is to consume carbohydrates in the form of liquids or food, but during physical activities, it can be difficult to follow their BGL at the same time as they exercise. This thesis presents the design and implementation of a mobile carbohydrate delivery system, M-CDS. Previous work has shown that it is possible to create a stationary carbohydrate delivery system that reads the user’s BG data in real-time, gives feedback to the user when their BGL is nearing hypoglycaemia, and issues a dose of juice with 15 grams of carbohydrates. The proof-of-concept system in this thesis has the same functions but is contained within a modified CamelBak backpack. A Raspberry Pi, together with various sensors and a peristaltic pump, can transfer juice from a drinking reservoir to a drinking tube, which the user can easily drink from while physically active. The results show that the backpack works as intended and was able to avoid a BGL under 3.9 mmol/L while testing the system with a user using physical activity, thus successfully avoiding a hypoglycaemic event. As the system is a proof-of-concept, many things can be improved or modified to create a more robust, user-friendly, compact, and complex system. However, creating a prototype proved to be a time-costly project, whereas future work can use this project as a base to further improve it

    Evaluation of strategies for reducing the burden of COPD in the UK using Bayesian methods

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    Chronic obstructive pulmonary disease (COPD) is responsible for 5.3% of all deaths and 1.7% of all hospital admissions in the UK. This thesis focuses on strategies to reduce COPD burden by targeting three aspects across the public healthcare system: prevention, emergency treatment, and long-term management. Analyses were performed in a Bayesian framework to exploit its flexibility in modelling uncertainty and the incorporation of prior knowledge. First, I assessed whether communication of personalised disease risk in primary care is an effective smoking cessation intervention, using cost-effectiveness and value of information analyses based on various data sources across the literature. The odds ratio for the effectiveness of communication of personalised disease risk was 1.48 (95%CrI:0.91-2.26). While I found a probability of cost-effectiveness of about 90%, further research up to a maximum of £27 million is justified to reduce the uncertainty around this estimate. Secondly, I assessed whether case ascertainment affects the detection of poorly performing hospital trusts in the treatment of acute exacerbation of COPD (AECOPD) in secondary care, using data from the National Asthma and COPD Audit Programme. Case ascertainment was associated with 30-day mortality (OR:1.74; 1.25-2.41) and adjusting for it impacted the findings, with 5 trusts becoming outliers and 2 trusts no longer classified as outliers. Finally, using general practice data from Clinical Practice Research Datalink, I assessed whether new guidelines suggesting triple therapy (long-acting beta-2 agonists, LABA + long-acting muscarinic antagonists, LAMA + inhaled corticosteroids, ICS) for the treatment of those with poorly-controlled COPD on LABA+LAMA dual therapy improves disease outcomes. Triple therapy was not associated with severe AECOPD (IRR:1.00; 0.93-1.07) or mortality (IRR:0.95; 0.86-1.06), but was associated with increased risk of pneumonia (IRR:1.19; 1.05-1.35). This thesis applied sophisticated Bayesian methods to increase understanding of how COPD burden could be reduced in different areas of the public healthcare system.Open Acces

    What is the role of caspase-2 mediated lipoapoptosis in the pathogenesis of the metabolic syndrome-associated liver disease, nonalcoholic fatty liver disease (NAFLD)?

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    Nonalcoholic fatty liver disease can be considered the hepatic manifestation of obesity and the metabolic syndrome. It is the number one cause of chronic liver disease in the Western world. Lipotoxicity in the liver induces epithelial lesion that triggers a wound healing response. In susceptible subjects the wound healing response is ineffective in repairing and regenerating the injured liver, leading to scarring, fibrogenesis and eventually hepatic cirrhosis. Though important advances in the knowledge of the pathogenesis of NAFLD have occurred since its firsts descriptions in 1980, gaps in knowledge still precludes Hepatologists to find an effective treatment for this pandemic. We first extensively characterized and compared two dietary mouse models of NAFLD, methionine-choline deficient (MCD) and Western diets. We found that MCD diet induces severe disease with significant fibrosis, whereas Western diet induces mild disease, but associates with obesity, insulin resistance and the metabolic syndrome. Afterwards, we demonstrated a pivotal role of caspase-2 in the development of the metabolic syndrome, NAFLD, progression to severe liver disease and hepatic fibrogenesis. Caspase-2 was up-regulated in human NAFLD and in in several different mouse models of NAFLD, correlating with the degree of fibrosis. Also, caspase-2 deficient mice were protected from the metabolic syndrome and liver injury/fibrosis in both MCD and Western diet mouse models. Finally, we found that in different mouse models of NAFLD, hepatic free coenzyme A content is decreased, which could potentiate caspase-2 activation. We conducted a preclinical trial in mice submitted to MCD diet, treating them with coenzyme A precursors. This approach failed to correct hepatic free coenzyme A levels and had no impact in liver histology or caspase-2 expression/activation. Our work places caspase-2 as a potential therapeutic target for obesity-associated diseases, such as type 2 diabetes mellitus and NAFLD.Fundação Calouste GulbenkianFundação CampalimaudMinistério da saúdeFundação para a Ciência e Tecnologi

    Safety and efficacy of basal bolus and premixed insulin intensification regimes in the management of type 2 diabetes mellitus : A 13 year narrative review of literature

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    Background: Type 2 Diabetes Mellitus (T2DM) is a chronic condition due to insulin resistance or relative insulin deficiency. Although insulin intensification regimens are commonly prescribed for the management of T2DM, there is uncertainty regarding their optimal use. We conducted a 13 Year narrative review to compare outcomes of these regimens in the treatment of T2DM. Method: We searched electronic databases (PubMed, Scopus, Proquest and Google Search), and “grey literature” from January 2000 to December 2013 to identify studies comparing insulin intensification regimens. Results: Out of 17 studies identified, we only included 10 studies specifically comparing Basal-Bolus regimens (BB) versus Pre-mixed Insulin Regimens (PM). Seven trials comparing regimens other than the studied regimens; with study duration lesser than 12 weeks; or involving Type 1 diabetes mellitus patients were excluded. The outcomes measured were divided into safety and efficacy parameters. Among the safety outcomes measured were Hypoglycemia, Weight Gain, Quality of Life (QoL), and other Adverse Events (AE). Whereas, efficacy outcomes measured were Glycosylated Haemoglobin (HbA1c), Fasting Plasma Glucose, Daily Plasma Glucose, Post Prandial Plasma Glucose, Carotid Intima Media Thickness (IMT), Adinopectin Level, 1-5-anhydroglucitol(1,5-AG),Total Daily Insulin (TDI) Dose and Cost. Mixed results were discovered among all the parameters measured favoring in between BB and PM regimens. Conclusion: We found that BB regimens showed better glycemic control especially in terms of the primary endpoint of HbAlc but at the expanse of significantly higher TDI dose, weight gain, and further increase in cost of treatment. Whereas, all other parameters measured were comparable between regimens. Locally, conventional human insulin is still the mainstay of insulin therapy in health facilities nationwide. Yet, none of the identified studies compared head-to-head human insulin in both arms. Thus, future researches comparing non-analogue insulin may be conducted to gather new evidence in the field of diabetes locally
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