173 resultados para Psychiatric Diagnosis
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Recent developments in genetic science will potentially have a significant impact on reproductive decision-making by adding to the list of conditions which can be diagnosed through prenatal diagnosis. This article analyses the jurisdictional variations that exist in Australian abortion laws and examines the extent to which Australian abortion laws specifically provide for termination of pregnancy on the grounds of fetal disability. The article also examines the potential impact of pre-implantation genetic diagnosis on reproductive decision-making and considers the meaning of reproductive autonomy in the context of the new genetics.
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Background: Population-based surveys demonstrate cannabis users are more likely to use both illicit and licit substances, compared with non-cannabis users. Few studies have examined the substance use profiles of cannabis users referred for treatment. Co-existing mental health symptoms and underlying cannabis-related beliefs associated with these profiles remains unexplored. Methods: Comprehensive drug use and dependence severity (Severity of Dependence Scale-Cannabis) data were collected on a sample of 826 cannabis users referred for treatment. Patients completed the General Health Questionnaire, Cannabis Expectancy Questionnaire, Cannabis Refusal Self-Efficacy Questionnaire, and Positive Symptoms and Manic-Excitement subscales of the Brief Psychiatric Rating Scale. Latent class analysis was performed on last month use of drugs to identify patterns of multiple drug use. Mental health comorbidity and cannabis beliefs were examined by identified drug use pattern. Results: A three-class solution provided the best fit to the data: (1) cannabis and tobacco users (n = 176), (2) cannabis, tobacco, and alcohol users (n = 498), and (3) wide-ranging sub- stance users (n = 132). Wide-ranging substance users (3) reported higher levels of cannabis dependence severity, negative cannabis expectancies, lower opportunistic, and emotional relief self-efficacy, higher levels of depression and anxiety and higher manic-excitement and positive psychotic symptoms. Conclusion: In a sample of cannabis users referred for treatment, wide-ranging substance use was associated with elevated risk on measures of cannabis dependence, co-morbid psychopathology, and dysfunctional cannabis cognitions. These findings have implications for cognitive-behavioral assessment and treatment.
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This paper presents a practical recursive fault detection and diagnosis (FDD) scheme for online identification of actuator faults for unmanned aerial systems (UASs) based on the unscented Kalman filtering (UKF) method. The proposed FDD algorithm aims to monitor health status of actuators and provide indication of actuator faults with reliability, offering necessary information for the design of fault-tolerant flight control systems to compensate for side-effects and improve fail-safe capability when actuator faults occur. The fault detection is conducted by designing separate UKFs to detect aileron and elevator faults using a nonlinear six degree-of-freedom (DOF) UAS model. The fault diagnosis is achieved by isolating true faults by using the Bayesian Classifier (BC) method together with a decision criterion to avoid false alarms. High-fidelity simulations with and without measurement noise are conducted with practical constraints considered for typical actuator fault scenarios, and the proposed FDD exhibits consistent effectiveness in identifying occurrence of actuator faults, verifying its suitability for integration into the design of fault-tolerant flight control systems for emergency landing of UASs.
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This chapter explains the main categories of personality disorders and their diagnosis.Nursing interventions are described, and challenges working with people who have personality disorders are discussed.Limitations in our understanding of personality disorders, and problems of categorisation, diagnosis and treatment are also discussed.
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Continuous monitoring of diesel engine performance is critical for early detection of fault developments in an engine before they materialize into a functional failure. Instantaneous crank angular speed (IAS) analysis is one of a few nonintrusive condition monitoring techniques that can be utilized for such a task. Furthermore, the technique is more suitable for mass industry deployments than other non-intrusive methods such as vibration and acoustic emission techniques due to the low instrumentation cost, smaller data size and robust signal clarity since IAS is not affected by the engine operation noise and noise from the surrounding environment. A combination of IAS and order analysis was employed in this experimental study and the major order component of the IAS spectrum was used for engine loading estimation and fault diagnosis of a four-stroke four-cylinder diesel engine. It was shown that IAS analysis can provide useful information about engine speed variation caused by changing piston momentum and crankshaft acceleration during the engine combustion process. It was also found that the major order component of the IAS spectra directly associated with the engine firing frequency (at twice the mean shaft rotating speed) can be utilized to estimate engine loading condition regardless of whether the engine is operating at healthy condition or with faults. The amplitude of this order component follows a distinctive exponential curve as the loading condition changes. A mathematical relationship was then established in the paper to estimate the engine power output based on the amplitude of this order component of the IAS spectrum. It was further illustrated that IAS technique can be employed for the detection of a simulated exhaust valve fault in this study.
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Objectives: Children with type 1 diabetes mellitus (DM1) may be at increased risk of psychosocial and adjustment difficulties. We examined behavioral outcomes six months post-diagnosis in a group of children with newly diagnosed DM1. Methods: This study formed part of a larger longitudinal project examining pathophysiology and neuropsychological outcomes in diabetic patients with or without diabetic ketoacidosis (DKA). Participants were 61 children (mean age 11.8 years, SD 2.7 years) who presented with a new diagnosis of DM1 at the Royal Children’s Hospital, Melbourne. Twenty-three (11 female) presented in DKA and 38 (14 female) without DKA. Parents completed the behavior assessment system for children, second edition six months post-diagnosis. Results: There was a non-linear relationship between age and behavior. Internalising problems (i.e. anxiety depression, withdrawal) peaked in the transition from childhood to adolescence; children aged 10–13 years had elevated rates relative to the normal population (t = 2.55, P = 0.018). There was a non-significant trend for children under 10 to display internalising problems (P = 0.052), but rates were not elevated in children over 13 (P = 0.538). Externalising problems were not significantly elevated in any age group. Interestingly, children who presented in DKA were at lower risk of internalising problems than children without DKA (t = 3.83, P < 0.001). There was no effect of DKA on externalising behaviors. Conclusions: Children transitioning from childhood to adolescence are at significant risk for developing internalising problems such as anxiety and lowered mood after diagnosis of DM1. Somewhat counter-intuitively, parents of children presenting in DKA reported fewer internalising symptoms than parents of children without DKA. These results highlight the importance of monitoring and supporting psychosocial adjustment in newly diagnosed children even when they seem physically well.
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The impact that stressful encounters have upon long-lasting behavioural phenotypes is varied. Whereas a significant proportion of the population will develop "stress-related" conditions such as post-traumatic stress disorder or depression in later life, the majority are considered "resilient" and are able to cope with stress and avoid such psychopathologies. The reason for this heterogeneity is undoubtedly multi-factorial, involving a complex interplay between genetic and environmental factors. Both genes and environment are of critical importance when it comes to developmental processes, and it appears that subtle differences in either of these may be responsible for altering developmental trajectories that confer vulnerability or resilience. At the molecular level, developmental processes are regulated by epigenetic mechanisms, with recent clinical and pre-clinical data obtained by ourselves and others suggesting that epigenetic differences in various regions of the brain are associated with a range of psychiatric disorders, including many that are stress-related. Here we provide an overview of how these epigenetic differences, and hence susceptibility to psychiatric disorders, might arise through exposure to stress-related factors during critical periods of development.
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Age-related Macular Degeneration (AMD) is one of the major causes of vision loss and blindness in ageing population. Currently, there is no cure for AMD, however early detection and subsequent treatment may prevent the severe vision loss or slow the progression of the disease. AMD can be classified into two types: dry and wet AMDs. The people with macular degeneration are mostly affected by dry AMD. Early symptoms of AMD are formation of drusen and yellow pigmentation. These lesions are identified by manual inspection of fundus images by the ophthalmologists. It is a time consuming, tiresome process, and hence an automated diagnosis of AMD screening tool can aid clinicians in their diagnosis significantly. This study proposes an automated dry AMD detection system using various entropies (Shannon, Kapur, Renyi and Yager), Higher Order Spectra (HOS) bispectra features, Fractional Dimension (FD), and Gabor wavelet features extracted from greyscale fundus images. The features are ranked using t-test, Kullback–Lieber Divergence (KLD), Chernoff Bound and Bhattacharyya Distance (CBBD), Receiver Operating Characteristics (ROC) curve-based and Wilcoxon ranking methods in order to select optimum features and classified into normal and AMD classes using Naive Bayes (NB), k-Nearest Neighbour (k-NN), Probabilistic Neural Network (PNN), Decision Tree (DT) and Support Vector Machine (SVM) classifiers. The performance of the proposed system is evaluated using private (Kasturba Medical Hospital, Manipal, India), Automated Retinal Image Analysis (ARIA) and STructured Analysis of the Retina (STARE) datasets. The proposed system yielded the highest average classification accuracies of 90.19%, 95.07% and 95% with 42, 54 and 38 optimal ranked features using SVM classifier for private, ARIA and STARE datasets respectively. This automated AMD detection system can be used for mass fundus image screening and aid clinicians by making better use of their expertise on selected images that require further examination.
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Background and aim In recent years policy in Australia has endorsed recovery-oriented mental health services underpinned by the needs, rights and values of people with lived experience of mental illness. This paper critically reviews the idea of recovery understood by nurses at the frontline of services for people experiencing acute psychiatric distress. Method Data gathered from focus groups held with nurses from two hospitals were used to ascertain their use of terminology, understanding of attributes and current practices that support recovery for people experiencing acute psychiatric distress. A review of literature further examined current nurse based evidence and nurse knowledge of recovery approaches specific to psychiatric intensive care settings. Results Four defining attributes of recovery based on nurses’ perspectives are shared to identify and describe strategies that may help underpin recovery specific to psychiatric intensive care settings. Conclusion The four attributes described in this paper provide a pragmatic framework with which nurses can reinforce their clinical decision-making and negotiate the dynamic and often incongruous challenges they experience to embed recovery-oriented culture in acute psychiatric settings.
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Saliva as a biological fluid is gaining wider acceptance for diagnosing diseases. The growing interest in saliva as a biological fluid is due to its noninvasiveness, ease of use, cost-effectiveness, and multiple sample collection possibilities as well as minimal risk to health care professionals of contracting infectious organisms such as HIV and Hep B. However, the clinical translation of saliva is hampered by our lack of understanding of the biomolecular transportation from blood into saliva, the diurnal variations of biomolecules present in saliva, and relatively low levels of analytes (100th to a 1000th fold less than in blood). We provide information on the current status of salivary research, salivary diagnostics empowered by nanotechnology, and future prospects in this emerging field of saliva diagnostics.
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Stress has been identified as a common trigger for psychosis. Dopamine pathways are suggested to be affected by chronic and severe stress and to play an important role in psychosis. This pilot study investigates the potential relationship of stress and psychosis in subclinical psychotic experiences. It was hypothesized that single-nucleotide polymorphisms (SNPs) previously found to be associated with psychiatric disorders would be associated with both stress and subclinical psychotic experiences. University students (N=182) were genotyped for 17 SNPs across 11 genes. Higher stress reporting was associated with rs4680 COMT, rs13211507 HLA region, and rs13107325 SLC39A8. Reports of higher subclinical psychotic experiences were associated with DRD2 SNPs rs17601612 and rs658986 and an AKT1 SNP rs2494732. Replication studies are recommended to further pursue this line of research for identification of markers of psychosis for early diagnosis and intervention.
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To complement the existing treatment guidelines for all tumour types, ESMO organises consensus conferences to focus on specific issues in each type of tumour. The 2nd ESMO Consensus Conference on Lung Cancer was held on 11-12 May 2013 in Lugano. A total of 35 experts met to address several questions on non-small-cell lung cancer (NSCLC) in each of four areas: pathology and molecular biomarkers, first-line/second and further lines in advanced disease, earlystage disease and locally advanced disease. For each question, recommendations were made including reference to the grade of recommendation and level of evidence. This consensus paper focuses on early-stage disease. © The Author 2014. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved.
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Purpose The purpose of this study is to examine the prevalence, sociodemographic and clinical predictors, and physical and psychosocial correlates of unmet needs among women 3–5 years following treatment for endometrial cancer. Methods Women with endometrial cancer completed a survey around the time of diagnosis and again 3–5 years later. The follow-up survey asked women about their physical and psychosocial functioning and supportive care needs (CaSUN). Multivariable-adjusted logistic regression identified the predictors and correlates of women’s unmet needs 3–5 years after diagnosis. Results Of the 629 women who completed the cancer survivors’ unmet needs measure (CaSUN), 24 % (n = 153) women reported one or more unmet supportive care needs in the last month. Unmet needs at 3–5 years post-diagnosis were predicted by younger age (OR = 4.47; 95 % CI: 2.09–9.56) and advanced disease stage at diagnosis (OR = 2.47; 95 % CI: 1.38–4.45) and correlated with greater cancer symptoms (OR = 1.78; 95 % CI: 1.05–3.02), lower limb swelling (OR = 2.50; 95 % CI: 1.51–4.15), symptoms of anxiety (OR = 2.21; 95 % CI: 1.31–3.72), and less availability of social support (OR = 3.42; 95 % CI: 1.92–6.11). Women with a history of comorbidities (OR = 0.47; 95 % CI: 0.27–0.82) and those living in a rural area at the time of diagnosis (OR = 0.56; 95 % CI: 0.34–0.92) were less likely to report unmet needs. Conclusions Sociodemographic, health, and psychosocial factors seem important for identifying women who will or will not have unmet needs several years following endometrial cancer. Longitudinal assessments of people’s needs over the course of their cancer trajectory may be an effective way to identify areas that should receive further attention by health providers.