236 resultados para STATISTICAL-MECHANICAL TREATMENT
em Queensland University of Technology - ePrints Archive
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Aims: This paper describes the development of a risk adjustment (RA) model predictive of individual lesion treatment failure in percutaneous coronary interventions (PCI) for use in a quality monitoring and improvement program. Methods and results: Prospectively collected data for 3972 consecutive revascularisation procedures (5601 lesions) performed between January 2003 and September 2011 were studied. Data on procedures to September 2009 (n = 3100) were used to identify factors predictive of lesion treatment failure. Factors identified included lesion risk class (p < 0.001), occlusion type (p < 0.001), patient age (p = 0.001), vessel system (p < 0.04), vessel diameter (p < 0.001), unstable angina (p = 0.003) and presence of major cardiac risk factors (p = 0.01). A Bayesian RA model was built using these factors with predictive performance of the model tested on the remaining procedures (area under the receiver operating curve: 0.765, Hosmer–Lemeshow p value: 0.11). Cumulative sum, exponentially weighted moving average and funnel plots were constructed using the RA model and subjectively evaluated. Conclusion: A RA model was developed and applied to SPC monitoring for lesion failure in a PCI database. If linked to appropriate quality improvement governance response protocols, SPC using this RA tool might improve quality control and risk management by identifying variation in performance based on a comparison of observed and expected outcomes.
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Objectives To compare the efficacy of two exercise programs in reducing pain and disability for individuals with non-specific low back pain and to examine the underlying mechanical factors related to pain and disability for individuals with NSLBP. Design A single-blind, randomized controlled trial. Methods: Eighty participants were recruited from eleven community-based general medical practices and randomized into two groups completing either a lumbopelvic motor control or a combined lumbopelvic motor control and progressive hip strengthening exercise therapy program. All participants received an education session, 6 rehabilitation sessions including real time ultrasound training, and a home based exercise program manual and log book. The primary outcomes were pain (0-100mm visual analogue scale), and disability (Oswestry Disability Index V2). The secondary outcomes were hip strength (N/kg) and two-dimensional frontal plane biomechanics (°) measure during the static Trendelenburg test and while walking. All outcomes were measured at baseline and at 6-week follow up. Results There was no statistical difference in the change in pain (xˉ = -4.0mm, t= -1.07, p =0.29, 95%CI -11.5, 3.5) or disability (xˉ = -0.3%, t= -0.19, p =0.85, 95%CI -3.5, 2.8) between groups. Within group comparisons revealed clinically meaningful reductions in pain for both Group One (xˉ =-20.9mm, 95%CI -25.7, -16.1) and Group Two (xˉ =-24.9, 95%CI -30.8, -19.0). Conclusion Both exercise programs had similar efficacy in reducing pain. The addition of hip strengthening exercises to a motor control exercise program does not appear to result in improved clinical outcome for pain for individuals with non-specific low back pain.
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This naturalistic study investigated the mechanisms of change in measures of negative thinking and in 24-h urinary metabolites of noradrenaline (norepinephrine), dopamine and serotonin in a sample of 43 depressed hospital patients attending an eight-session group cognitive behavior therapy program. Most participants (91%) were taking antidepressant medication throughout the therapy period according to their treating Psychiatrists' prescriptions. The sample was divided into outcome categories (19 Responders and 24 Non-responders) on the basis of a clinically reliable change index [Jacobson, N.S., & Truax, P., 1991. Clinical significance: a statistical approach to defining meaningful change in psychotherapy research. Journal of Consulting and Clinical Psychology, 59, 12–19.] applied to the Beck Depression Inventory scores at the end of the therapy. Results of repeated measures analysis of variance [ANOVA] analyses of variance indicated that all measures of negative thinking improved significantly during therapy, and significantly more so in the Responders as expected. The treatment had a significant impact on urinary adrenaline and metadrenaline excretion however, these changes occurred in both Responders and Non-responders. Acute treatment did not significantly influence the six other monoamine metabolites. In summary, changes in urinary monoamine levels during combined treatment for depression were not associated with self-reported changes in mood symptoms.
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Conifers are resistant to attack from a large number of potential herbivores or pathogens. Previous molecular and biochemical characterization of selected conifer defence systems support a model of multigenic, constitutive and induced defences that act on invading insects via physical, chemical, biochemical or ecological (multitrophic) mechanisms. However, the genomic foundation of the complex defence and resistance mechanisms of conifers is largely unknown. As part of a genomics strategy to characterize inducible defences and possible resistance mechanisms of conifers against insect herbivory, we developed a cDNA microarray building upon a new spruce (Picea spp.) expressed sequence tag resource. This first-generation spruce cDNA microarray contains 9720 cDNA elements representing c. 5500 unique genes. We used this array to monitor gene expression in Sitka spruce (Picea sitchensis) bark in response to herbivory by white pine weevils (Pissodes strobi, Curculionidae) or wounding, and in young shoot tips in response to western spruce budworm (Choristoneura occidentalis, Lepidopterae) feeding. Weevils are stem-boring insects that feed on phloem, while budworms are foliage feeding larvae that consume needles and young shoot tips. Both insect species and wounding treatment caused substantial changes of the host plant transcriptome detected in each case by differential gene expression of several thousand array elements at 1 or 2 d after the onset of treatment. Overall, there was considerable overlap among differentially expressed gene sets from these three stress treatments. Functional classification of the induced transcripts revealed genes with roles in general plant defence, octadecanoid and ethylene signalling, transport, secondary metabolism, and transcriptional regulation. Several genes involved in primary metabolic processes such as photosynthesis were down-regulated upon insect feeding or wounding, fitting with the concept of dynamic resource allocation in plant defence. Refined expression analysis using gene-specific primers and real-time PCR for selected transcripts was in agreement with microarray results for most genes tested. This study provides the first large-scale survey of insect-induced defence transcripts in a gymnosperm and provides a platform for functional investigation of plant-insect interactions in spruce. Induction of spruce genes of octadecanoid and ethylene signalling, terpenoid biosynthesis, and phenolic secondary metabolism are discussed in more detail.
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A statistical modeling method to accurately determine combustion chamber resonance is proposed and demonstrated. This method utilises Markov-chain Monte Carlo (MCMC) through the use of the Metropolis-Hastings (MH) algorithm to yield a probability density function for the combustion chamber frequency and find the best estimate of the resonant frequency, along with uncertainty. The accurate determination of combustion chamber resonance is then used to investigate various engine phenomena, with appropriate uncertainty, for a range of engine cycles. It is shown that, when operating on various ethanol/diesel fuel combinations, a 20% substitution yields the least amount of inter-cycle variability, in relation to combustion chamber resonance.
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Background: Patterns of diagnosis and management for men diagnosed with prostate cancer in Queensland, Australia, have not yet been systematically documented and so assumptions of equity are untested. This longitudinal study investigates the association between prostate cancer diagnostic and treatment outcomes and key area-level characteristics and individual-level demographic, clinical and psychosocial factors.---------- Methods/Design: A total of 1064 men diagnosed with prostate cancer between February 2005 and July 2007 were recruited through hospital-based urology outpatient clinics and private practices in the centres of Brisbane, Townsville and Mackay (82% of those referred). Additional clinical and diagnostic information for all 6609 men diagnosed with prostate cancer in Queensland during the study period was obtained via the population-based Queensland Cancer Registry. Respondent data are collected using telephone and self-administered questionnaires at pre-treatment and at 2 months, 6 months, 12 months, 24 months, 36 months, 48 months and 60 months post-treatment. Assessments include demographics, medical history, patterns of care, disease and treatment characteristics together with outcomes associated with prostate cancer, as well as information about quality of life and psychological adjustment. Complementary detailed treatment information is abstracted from participants’ medical records held in hospitals and private treatment facilities and collated with health service utilisation data obtained from Medicare Australia. Information about the characteristics of geographical areas is being obtained from data custodians such as the Australian Bureau of Statistics. Geo-coding and spatial technology will be used to calculate road travel distances from patients’ residences to treatment centres. Analyses will be conducted using standard statistical methods along with multilevel regression models including individual and area-level components.---------- Conclusions: Information about the diagnostic and treatment patterns of men diagnosed with prostate cancer is crucial for rational planning and development of health delivery and supportive care services to ensure equitable access to health services, regardless of geographical location and individual characteristics. This study is a secondary outcome of the randomised controlled trial registered with the Australian New Zealand Clinical Trials Registry (ACTRN12607000233426)
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Background Outcome expectancies are a key cognitive construct in the etiology, assessment and treatment of Substance Use Disorders. There is a research and clinical need for a cannabis expectancy measure validated in a clinical sample of cannabis users. Method The Cannabis Expectancy Questionnaire (CEQ) was subjected to exploratory (n = 501, mean age 27.45, 78% male) and confirmatory (n = 505, mean age 27.69, 78% male) factor analysis in two separate samples of cannabis users attending an outpatient cannabis treatment program. Weekly cannabis consumption was clinically assessed and patients completed the Severity of Dependence Scale-Cannabis (SDS-C) and the General Health Questionnaire (GHQ-28). Results Two factors representing Negative Cannabis Expectancies and Positive Cannabis Expectancies were identified. These provided a robust statistical and conceptual fit for the data. Internal reliabilities were high. Negative expectancies were associated with greater dependence severity (as measured by the SDS) and positive expectancies with higher consumption. The interaction of positive and negative expectancies was consistently significantly associated with self-reported functioning across all four GHQ-28 scales (Somatic Concerns, Anxiety, Social Dysfunction and Depression). Specifically, within the context of high positive cannabis expectancy, higher negative expectancy was predictive of more impaired functioning. By contrast, within the context of low positive cannabis expectancy, higher negative expectancy was predictive of better functioning. Conclusions The CEQ is the first cannabis expectancy measure to be validated in a sample of cannabis users in treatment. Negative and positive cannabis expectancy domains were uniquely associated with consumption, dependence severity and self-reported mental health functioning.
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BACKGROUND: Treatment of proximal humerus fractures in elderly patients is challenging because of reduced bone quality. We determined the in vitro characteristics of a new implant developed to target the remaining bone stock, and compared it with an implant in clinical use. METHODS: Following osteotomy, left and right humeral pairs from cadavers were treated with either the Button-Fix or the Humerusblock fixation system. Implant stiffness was determined for three clinically relevant cases of load: axial compression, torsion, and varus bending. In addition, a cyclic varus-bending test was performed. RESULTS: We found higher stiffness values for the humeri treated with the ButtonFix system--with almost a doubling of the compression, torsion, and bending stiffness values. Under dynamic loading, the ButtonFix system had superior stiffness and less K-wire migration compared to the Humerusblock system. INTERPRETATION: When compared to the Humerusblock design, the ButtonFix system showed superior biomechanical properties, both static and dynamic. It offers a minimally invasive alternative for the treatment of proximal humerus fractures.
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The research objectives of this thesis were to contribute to Bayesian statistical methodology by contributing to risk assessment statistical methodology, and to spatial and spatio-temporal methodology, by modelling error structures using complex hierarchical models. Specifically, I hoped to consider two applied areas, and use these applications as a springboard for developing new statistical methods as well as undertaking analyses which might give answers to particular applied questions. Thus, this thesis considers a series of models, firstly in the context of risk assessments for recycled water, and secondly in the context of water usage by crops. The research objective was to model error structures using hierarchical models in two problems, namely risk assessment analyses for wastewater, and secondly, in a four dimensional dataset, assessing differences between cropping systems over time and over three spatial dimensions. The aim was to use the simplicity and insight afforded by Bayesian networks to develop appropriate models for risk scenarios, and again to use Bayesian hierarchical models to explore the necessarily complex modelling of four dimensional agricultural data. The specific objectives of the research were to develop a method for the calculation of credible intervals for the point estimates of Bayesian networks; to develop a model structure to incorporate all the experimental uncertainty associated with various constants thereby allowing the calculation of more credible credible intervals for a risk assessment; to model a single day’s data from the agricultural dataset which satisfactorily captured the complexities of the data; to build a model for several days’ data, in order to consider how the full data might be modelled; and finally to build a model for the full four dimensional dataset and to consider the timevarying nature of the contrast of interest, having satisfactorily accounted for possible spatial and temporal autocorrelations. This work forms five papers, two of which have been published, with two submitted, and the final paper still in draft. The first two objectives were met by recasting the risk assessments as directed, acyclic graphs (DAGs). In the first case, we elicited uncertainty for the conditional probabilities needed by the Bayesian net, incorporated these into a corresponding DAG, and used Markov chain Monte Carlo (MCMC) to find credible intervals, for all the scenarios and outcomes of interest. In the second case, we incorporated the experimental data underlying the risk assessment constants into the DAG, and also treated some of that data as needing to be modelled as an ‘errors-invariables’ problem [Fuller, 1987]. This illustrated a simple method for the incorporation of experimental error into risk assessments. In considering one day of the three-dimensional agricultural data, it became clear that geostatistical models or conditional autoregressive (CAR) models over the three dimensions were not the best way to approach the data. Instead CAR models are used with neighbours only in the same depth layer. This gave flexibility to the model, allowing both the spatially structured and non-structured variances to differ at all depths. We call this model the CAR layered model. Given the experimental design, the fixed part of the model could have been modelled as a set of means by treatment and by depth, but doing so allows little insight into how the treatment effects vary with depth. Hence, a number of essentially non-parametric approaches were taken to see the effects of depth on treatment, with the model of choice incorporating an errors-in-variables approach for depth in addition to a non-parametric smooth. The statistical contribution here was the introduction of the CAR layered model, the applied contribution the analysis of moisture over depth and estimation of the contrast of interest together with its credible intervals. These models were fitted using WinBUGS [Lunn et al., 2000]. The work in the fifth paper deals with the fact that with large datasets, the use of WinBUGS becomes more problematic because of its highly correlated term by term updating. In this work, we introduce a Gibbs sampler with block updating for the CAR layered model. The Gibbs sampler was implemented by Chris Strickland using pyMCMC [Strickland, 2010]. This framework is then used to consider five days data, and we show that moisture in the soil for all the various treatments reaches levels particular to each treatment at a depth of 200 cm and thereafter stays constant, albeit with increasing variances with depth. In an analysis across three spatial dimensions and across time, there are many interactions of time and the spatial dimensions to be considered. Hence, we chose to use a daily model and to repeat the analysis at all time points, effectively creating an interaction model of time by the daily model. Such an approach allows great flexibility. However, this approach does not allow insight into the way in which the parameter of interest varies over time. Hence, a two-stage approach was also used, with estimates from the first-stage being analysed as a set of time series. We see this spatio-temporal interaction model as being a useful approach to data measured across three spatial dimensions and time, since it does not assume additivity of the random spatial or temporal effects.
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Core(polyvinyl neodecanoate-ethylene glycol dimethacrylate)-shell(polyvinyl alcohol) (core (P(VND-EGDMA))-shell(PVA)) microspheres were developed by seeded polymerization with the use of conventional free radical and RAFT/MADIX mediated polymerization. Poly(vinyl pivalate) PVPi was grafted onto microspheres prepared via suspension polymerization of vinylneodecanoate and ethylene glycol dimethacrylate. The amount of grafted polymer was found to be independent from the technique used with conventional free radical polymerization and MADIX polymerization resulting into similar shell thicknesses. Both systems—grafting via free radical polymerization or the MADIX process—were found to follow slightly different kinetics. While the free radical polymerization resulted in a weight gain linear with the monomer consumption in solution the growth in the MADIX controlled system experienced a delay. The core-shell microspheres were obtained by hydrolysis of the poly(vinyl pivalate) surface grafted brushes to form poly(vinyl alcohol). During hydrolysis the microspheres lost a significant amount of weight, consistent with the hydrolysis of 40–70% of all VPi units. Drug loading was found to be independent of the shell layer thickness, suggesting that the drug loading is governed by the amount of bulk material. The shell layer does not appear to represent an obstacle to the drug ingress. Cell testing using colorectal cancer cell lines HT 29 confirm the biocompatibility of the empty microspheres whereas the clofazimine loaded particles lead to 50% cell death, confirming the release of the drug.
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STUDY OBJECTIVES: To determine whether cerebral metabolite changes may underlie abnormalities of neurocognitive function and respiratory control in OSA. DESIGN: Observational, before and after CPAP treatment. SETTING: Two tertiary hospital research institutes. PARTICIPANTS: 30 untreated severe OSA patients, and 25 age-matched healthy controls, all males free of comorbidities, and all having had detailed structural brain analysis using voxel-based morphometry (VBM). MEASUREMENTS AND RESULTS: Single voxel bilateral hippocampal and brainstem, and multivoxel frontal metabolite concentrations were measured using magnetic resonance spectroscopy (MRS) in a high resolution (3T) scanner. Subjects also completed a battery of neurocognitive tests. Patients had repeat testing after 6 months of CPAP. There were significant differences at baseline in frontal N-acetylaspartate/choline (NAA/Cho) ratios (patients [mean (SD)] 4.56 [0.41], controls 4.92 [0.44], P = 0.001), and in hippocampal choline/creatine (Cho/Cr) ratios (0.38 [0.04] vs 0.41 [0.04], P = 0.006), (both ANCOVA, with age and premorbid IQ as covariates). No longitudinal changes were seen with treatment (n = 27, paired t tests), however the hippocampal differences were no longer significant at 6 months, and frontal NAA/Cr ratios were now also significantly different (patients 1.55 [0.13] vs control 1.65 [0.18] P = 0.01). No significant correlations were found between spectroscopy results and neurocognitive test results, but significant negative correlations were seen between arousal index and frontal NAA/Cho (r = -0.39, corrected P = 0.033) and between % total sleep time at SpO(2) < 90% and hippocampal Cho/Cr (r = -0.40, corrected P = 0.01). CONCLUSIONS: OSA patients have brain metabolite changes detected by MRS, suggestive of decreased frontal lobe neuronal viability and integrity, and decreased hippocampal membrane turnover. These regions have previously been shown to have no gross structural lesions using VBM. Little change was seen with treatment with CPAP for 6 months. No correlation of metabolite concentrations was seen with results on neurocognitive tests, but there were significant negative correlations with OSA severity as measured by severity of nocturnal hypoxemia. CITATION: O'Donoghue FJ; Wellard RM; Rochford PD; Dawson A; Barnes M; Ruehland WR; Jackson ML; Howard ME; Pierce RJ; Jackson GD. Magnetic resonance spectroscopy and neurocognitive dysfunction in obstructive sleep apnea before and after CPAP treatment.
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In this study on the basis of lab data and available resources in Bangladesh, feasibility study has been carried out for pyrolysis process converting solid tire wastes into pyrolysis oils, solid char and gases. The process considered for detailed analysis was fixed-bed fire-tube heating pyrolysis reactor system. The comparative techno-economic assessment was carried out in US$ for three different sizes plants: medium commercial scale (144 tons/day), small commercial scale (36 tons/day), pilot scale (3.6 tons/day). The assessment showed that medium commercial scale plant was economically feasible, with the lowest unit production cost than small commercial and pilot scale plants for the production of crude pyrolysis oil that could be used as boiler fuel oil and for the production of upgraded liquid-products.