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    ABSTRACT: Suppose that U = (U(1), … , U(d)) has a Uniform ([0, 1](d)) distribution, that Y = (Y(1), … , Y(d)) has the distribution G on [Formula: see text], and let X = (X(1), … , X(d)) = (U(1)Y(1), … , U(d)Y(d)). The resulting class of distributions of X (as G varies over all distributions on [Formula: see text]) is called the Scale Mixture of Uniforms class of distributions, and the corresponding class of densities on [Formula: see text] is denoted by [Formula: see text]. We study maximum likelihood estimation in the family [Formula: see text]. We prove existence of the MLE, establish Fenchel characterizations, and prove strong consistency of the almost surely unique maximum likelihood estimator (MLE) in [Formula: see text]. We also provide an asymptotic minimax lower bound for estimating the functional f ↦ f(x) under reasonable differentiability assumptions on f ∈ [Formula: see text] in a neighborhood of x. We conclude the paper with discussion, conjectures and open problems pertaining to global and local rates of convergence of the MLE.
    Journal of Multivariate Analysis 05/2012; 107:71-89.
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    ABSTRACT: The aim of this paper is to use Markov modelling to investigate survival for particular types of kidney patients in relation to their exposure to anti-hypertensive treatment drugs. In order to monitor kidney function an intuitive three point assessment is proposed through the collection of blood samples in relation to chronic kidney disease for Northern Ireland patients. A five state Markov model was devised using specific transition probabilities for males and females over all age groups. These transition probabilities were then adjusted appropriately using relative risk scores for the event death for different subgroups of patients. The model was built using TreeAge software package in order to explore the effects of anti-hypertensive drugs on patients.
    Computer-Based Medical Systems, 2008. CBMS '08. 21st IEEE International Symposium on; 07/2008
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    ABSTRACT: To determine the diagnostic accuracy of advanced medical priority dispatch system (AMPDS) software used to dispatch public access defibrillation first responders to out-of-hospital cardiac arrests (OHCA). All true OHCA events in North and West Belfast in 2004 were prospectively collated. This was achieved by a comprehensive search of all manually completed Patient Report Forms compiled by paramedics, together with autopsy reports, death certificates and medical records. The dispatch coding of all emergency calls by AMPDS software was also obtained for the same time period and region, and a comparison was made between these two datasets. A single urban ambulance control centre in Northern Ireland. All 238 individuals with a presumed or actual OHCA in the North and West Belfast Health and Social Services Trust population of 138 591 (2001 Census), as defined by the Utstein Criteria. The accurate dispatch of an emergency ambulance to a true OHCA. The sensitivity of the dispatch mechanism for detecting OHCA was 68.9% (115/167, 95% confidence interval (CI) 61.3% to 75.8%). However, the sensitivity for arrests with ventricular fibrillation (VF) was 44.4% (12/27) with sensitivity for witnessed VF of 47.1% (8/17). The positive predictive value was 63.5% (115/181, 95% CI 56.1% to 70.6%). The sensitivity of this dispatch process for cardiac arrest is moderate and will constrain the effectiveness of Public Access Defibrillation (PAD) schemes which utilise it. controlled-trials.com ISRCTN07286796.
    Heart (British Cardiac Society) 04/2008; 94(3):349-53.
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    ABSTRACT: Kidney Disease Outcomes Quality Initiative (KDOQI) chronic kidney disease (CKD) guidelines have focused on the utility of using the modified four-variable MDRD equation (now traceable by isotope dilution mass spectrometry IDMS) in calculating estimated glomerular filtration rates (eGFRs). This study assesses the practical implications of eGFR correction equations on the range of creatinine assays currently used in the UK and further investigates the effect of these equations on the calculated prevalence of CKD in one UK region Using simulation, a range of creatinine data (30-300 micromol/l) was generated for male and female patients aged 20-100 years. The maximum differences between the IDMS and MDRD equations for all 14 UK laboratory techniques for serum creatinine measurement were explored with an average of individual eGFRs calculated according to MDRD and IDMS < 60 ml/min/1.73 m(2) and 30 ml/min/1.73 m(2). Similar procedures were applied to 712,540 samples from patients > or = 18 years (reflecting the five methods for serum creatinine measurement utilized in Northern Ireland) to explore, graphically, maximum differences in assays. CKD prevalence using both estimation equations was compared using an existing cohort of observed data. Simulated data indicates that the majority of laboratories in the UK have small differences between the IDMS and MDRD methods of eGFR measurement for stages 4 and 5 CKD (where the averaged maximum difference for all laboratory methods was 1.27 ml/min/1.73 m(2) for females and 1.59 ml/min/1.73 m(2) for males). MDRD deviated furthest from the IDMS results for the Endpoint Jaffe method: the maximum difference of 9.93 ml/min/1.73 m(2) for females and 5.42 ml/min/1.73 m(2) for males occurred at extreme ages and in those with eGFR > 30 ml/min/1.73 m(2). Observed data for 93,870 patients yielded a first MDRD eGFR < 60 ml/min/1.73 m(2) in 2001. 66,429 (71%) had a second test > 3 months later of which 47,093 (71%) continued to have an eGFR < 60 ml/min/1.73 m(2). Estimated crude prevalence was 3.97% for laboratory detected CKD in adults using the MDRD equation which fell to 3.69% when applying the IDMS equation. Over 95% of this difference in prevalence was explained by older females with stage 3 CKD (eGFR 30-59 ml/min/1.73 m(2)) close to the stage 2 CKD (eGFR 60-90 ml/min/1.73 m(2)) interface. Improved accuracy of eGFR is obtainable by using IDMS correction especially in the earlier stages of CKD 1-3. Our data indicates that this improved accuracy could lead to reduced prevalence estimates and potentially a decreased likelihood of onward referral to nephrology services particularly in older females.
    Nephrology Dialysis Transplantation 02/2008; 23(2):542-8.
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    ABSTRACT: Previous research has introduced the conditional phase-type distribution as a model that can suitably represent a skewed survival distribution conditioned on a network of inter-related variables. The technique has successfully been applied to modeling the stay of elderly patients in hospital which typically includes extreme stays in hospital resulting in a highly skewed survival distribution. This paper uses the Conditional phase-type distribution in a different setting whereby the focus is on patients who are in hospital due to having suffered a hip fracture. The model represents the patient length of stay in hospital conditioned on a Bayesian network of inter-related patient variables. In particular, the network highlights the key factors influencing length of stay and identifies relationships between long stay patients, delays in surgery and the patients condition. The delays identified in the system, could therefore be addressed to hopefully reduce the length of stay in hospital and increase the flow of patients in the hospital system.
    Proceedings of the Twenty-First IEEE International Symposium on Computer-Based Medical Systems, June 17-19, 2008, Jyväskylä, Finland; 01/2008
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    ABSTRACT: The length of stay in hospital of geriatric patients may be modelled using the Coxian phase-type distribution. This paper examines previous methods which have been used to model health-care costs and presents a new methodology to estimate the costs for a cohort of patients for their duration of stay in hospital, assuming there are no further admissions. The model, applied to 1392 patients admitted into the geriatric ward of a local hospital in Northern Ireland, between 2002 and 2003, should be beneficial to hospital managers, as future decisions and policy changes could be tested on the model to investigate their influence on costs before the decisions were carried out on a real ward.
    Statistics in Medicine 07/2007; 26(13):2716-29.
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    ABSTRACT: This paper extends a method for modeling the survival of patients in hospitals to allow the expected cost to be estimated for the patients' accumulated duration of time in care. An extension of Bayesian network (BN) theory has previously been developed to model patients' survival time in hospitals with respect to the graphical and probabilistic representation of the interrelationships between the patients' clinical variables. Unlike previous BN techniques, this extended model can accommodate continuous times that are skewed in nature. This paper presents the theory behind such an approach and extends it by attaching a cost variable to the survival times, enabling the costing and efficient management of groups of patients in hospitals. An application of the model is illustrated by considering a group of 4260 patients admitted into the geriatric department of a U.K. hospital between 1994-1997. Results are derived for the distribution for their length of stay in the hospital and associated costs. The model's practical use is highlighted by illustrating how hospital managers could benefit using such a method for investigating the influence of future decisions and policy changes on the hospital's expenditure.
    IEEE Transactions on Information Technology in Biomedicine 08/2006; 10(3):526-32.
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    ABSTRACT: The ability to model and predict the progression of disease in a patient can have wide ranging benefits, including the ability to successfully manage bed allocation in hospitals or the increase understanding of the evolution of the disease. This paper describes a new method of modelling the progression of a disease through different stages called a Coxian hidden Markov model. This model can be used to increase understanding of the characteristics of the different stages of the disease and to predict patient survival time given repeated measurements of dynamically changing clinical variables. This knowledge could then be used to provide better patient management
    Computer-Based Medical Systems, 2006. CBMS 2006. 19th IEEE International Symposium on; 02/2006
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    ABSTRACT: This paper describes the development of a model to assess the distribution of response times for mobile volunteers of a public access defibrillation (PAD) scheme in Northern Ireland. Using parameters based on a trial period, the model predicts that a PAD volunteer would arrive before the emergency medical services (EMS) to 18.8% of events to which they are paged in a given year period. This is in agreement with what has actually been observed during the trial period (where volunteers have actually reached 15% of events before the EMS), and thus assisting validation of the model. Results from this model illustrate how ongoing volunteer commitment is key to the success of the scheme
    19th IEEE International Symposium on Computer-Based Medical Systems (CBMS 2006), 22-23 June 2006, Salt Lake City, Utah, USA; 01/2006
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    ABSTRACT: This paper introduces a special computer-based roster scheme developed to allocate and manage volunteers working as part of a public access defibrillation trial. The roster scheme, developed for the urban region, is rooted on population statistics and demographics for that area and utilizes geographical mapping software and spatial modelling techniques to subdivide the geographical location into appropriate paging zones. The central location for zones was constrained to be within a reasonable travelling time for each volunteer. By estimating sudden cardiac arrest occurrences using a Poisson process, the model, together with road network information, selects a roster which minimizes volunteer response time.
    Computer-Based Medical Systems, 2005. Proceedings. 18th IEEE Symposium on; 07/2005
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