54 resultados para insulated-gate bipolar transistors (IGBTs)


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We analyse time series from 100 patients with bipolar disorder for correlates of depression symptoms. As the sampling interval is non-uniform, we quantify the extent of missing and irregular data using new measures of compliance and continuity. We find that uniformity of response is negatively correlated with the standard deviation of sleep ratings (ρ = -0.26, p = 0.01). To investigate the correlation structure of the time series themselves, we apply the Edelson-Krolik method for correlation estimation. We examine the correlation between depression symptoms for a subset of patients and find that self-reported measures of sleep and appetite/weight show a lower average correlation than other symptoms. Using surrogate time series as a reference dataset, we find no evidence that depression is correlated between patients, though we note a possible loss of information from sparse sampling. © 2013 The Author(s).

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Bipolar disorder is a severe affective disorder which can present in adolescence, or sometimes earlier, and often requires a pharmacotherapeutic approach. The phenomenology of bipolar disorder in children and adolescents appears to differ from that of adult patients, prompting the need for specific pharmacotherapy guidelines for long-term management in this patient population. Current treatment guidelines were mainly developed based on evidence from studies in adult patients, highlighting the requirement for further research into the pharmacotherapy of children and adolescents with bipolar disorder. This review compares and critically analyzes the available guidelines, discussing the recommended medication classes, their mechanisms of action, side effect profiles and evidence base

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Introduction: Impulsivity and risk-taking behaviours are reported in bipolar disorder (BD). We examined whether financial management skills are related to impulsivity in patients with BD. Methods: We assessed financial management skills using the Executive Personal Finance Scale (EPFS), impulsivity using the Barratt Impulsiveness Scale (BIS) and response inhibition using an emotional go/no-go task in bipolar individuals (N = 21) and healthy controls (HC; N = 23). Results: Patients had fewer financial management skills and higher levels of impulsivity than HC. In patients and controls, increased impulsivity was associated with poorer personal financial management. Patients and HC performed equally on the emotional go/no-go task. Higher BIS scores were associated with faster reaction times in HC. In patients, however, higher BIS scores were associated with slower reaction times, possibly indicating compensatory cognitive strategies to counter increased impulsivity. Conclusions: Patients with BD may have reduced abilities to manage personal finances, when compared against healthy participants. Difficulty with personal finance management may arise in part as a result of increased levels of impulsivity. Patients may learn to compensate for increased impulsivity by modulating response times in our experimental situations although whether such compensatory strategies generalize to real-world situations is unknown.

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Most people with bipolar disorder first seek treatment for depressive rather than manic symptoms. However, effective management of bipolar depression remains a challenge. In this review, Celia Feetam highlights how bipolar depression differs from unipolar depression both in its characteristics and in the approach to its treatment. © 2011 John Wiley & Sons, Ltd.

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Background: Impairment in social cognition may contribute to deficits in social functioning in patients with bipolar disorder (BD). In this study, a complex social cognition task was administered during a neuroimaging session. The behavioral and neural correlates of social cogniton in patients with BD were compared to healthy comparison (HC) subjects. Methods: The task was administered to 25 HC and 25 patients with depression scores ranging from euthymic to depressed at the time of assessment. The task required participants to evaluate situations that were “enhancing” or “threatening” to self-esteem, directed at both oneself, and at other people. For instance, self-esteem enhancing scenarios involved vignettes of activities such as receiving praise during a sports game, while a threatening scenario involved, for example, receiving criticism at a party. Participants were then required to evaluate characters in the scenarios on the basis of positive (“kind”) or negative (“mean”) descriptors. Evaluations were classified from extremely negative to extremely positive. The frequencies of behavioral responses were analyzed using chi-square tests and fMRI data were analyzed using Statistical Parametric Mapping software. Results: Patients differed significantly from HCs in their evaluation of threatening scenarios, directed at both oneself and at other people (p<0.001). Patients had a lower proportion of responses in the neutral category, and more responses in the positive and negative categories, relative to HCs. Neuroimaging results reveal differential patterns of prefrontal-cortical and limbic-subcortical activation in BDs throughout the task [p<0.05 (unc.)]. Conclusions: Findings will contribute to understanding difficulty in interpersonal functioning in patients with BD.

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There is considerable international interest in online education of patients with bipolar disorder, yet little understanding of how patients use the Internet and other sources to seek information. 1171 patients with bipolar disorder diagnosis in 17 countries completed a paper-based, anonymous survey. 81% of the patients used the Internet, a percentage similar to the general public. Older age, less education, and challenges in country telecommunications infrastructure and demographics decreased the odds of using the Internet. About 78% of the Internet users looked online for information on bipolar disorder or 63% of the total sample. More years of education in relation to the country mean, and feeling very confident about managing life decreased the odds of seeking information on bipolar disorder online, while having attended support groups increased the odds. Patients who looked online for information on bipolar disorder consulted medical professionals plus a mean of 2.3 other information sources such as books, physician handouts, and others with bipolar disorder. Patients not using the Internet consulted medical professionals plus a mean of 1.6 other information sources. The percentage of patients with bipolar disorder who use the Internet is about the same as the general public. Other information sources remain important.

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Background: Information seeking is an important coping mechanism for dealing with chronic illness. Despite a growing number of mental health websites, there is little understanding of how patients with bipolar disorder use the Internet to seek information. Methods: A 39 question, paper-based, anonymous survey, translated into 12 languages, was completed by 1222 patients in 17 countries as a convenience sample between March 2014 and January 2016. All patients had a diagnosis of bipolar disorder from a psychiatrist. Data were analyzed using descriptive statistics and generalized estimating equations to account for correlated data. Results: 976 (81 % of 1212 valid responses) of the patients used the Internet, and of these 750 (77 %) looked for information on bipolar disorder. When looking online for information, 89 % used a computer rather than a smartphone, and 79 % started with a general search engine. The primary reasons for searching were drug side effects (51 %), to learn anonymously (43 %), and for help coping (39 %). About 1/3 rated their search skills as expert, and 2/3 as basic or intermediate. 59 % preferred a website on mental illness and 33 % preferred Wikipedia. Only 20 % read or participated in online support groups. Most patients (62 %) searched a couple times a year. Online information seeking helped about 2/3 to cope (41 % of the entire sample). About 2/3 did not discuss Internet findings with their doctor. Conclusion: Online information seeking helps many patients to cope although alternative information sources remain important. Most patients do not discuss Internet findings with their doctor, and concern remains about the quality of online information especially related to prescription drugs. Patients may not rate search skills accurately, and may not understand limitations of online privacy. More patient education about online information searching is needed and physicians should recommend a few high quality websites.

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Background: Increased impulsivity and aberrant response inhibition have been observed in bipolar disorder (BD). This study examined the functional abnormalities and underlying neural processes during response inhibition in BD, and its relationship to impulsivity. Methods: We assessed impulsivity using the Barratt Impulsiveness Scale (BIS) and, using functional magnetic resonance imaging (fMRI), measured neural activity in response to an Affective Go-NoGo Task, consisting of emotional facial stimuli (fear, happy, anger faces) and non-emotional control stimuli (neutral female and male faces) in euthymic BD (n=23) and healthy individuals (HI; n=25). Results: BD patients were significantly more impulsive, yet did not differ from HI on accuracy or reaction time on the emotional go/no-go task. Comparing neural patterns of activation when processing emotional Go versus emotional NoGo trials yielded increased activation in BD within temporal and cingulate cortices and within prefrontal-cortical regions in HI. Furthermore, higher BIS scores for BD were associated with slower reaction times, and indicative of compensatory cognitive strategies to counter increased impulsivity. Conclusions: These findings illustrate cognition-emotion interference in BD and the observed differences in neural activation indicate potentially altered emotion modulation. Increased activation in brain regions previously shown in emotion regulation and response inhibition tasks could represent a disease-specific marker for BD

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Improved clinical care for Bipolar Disorder (BD) relies on the identification of diagnostic markers that can reliably detect disease-related signals in clinically heterogeneous populations. At the very least, diagnostic markers should be able to differentiate patients with BD from healthy individuals and from individuals at familial risk for BD who either remain well or develop other psychopathology, most commonly Major Depressive Disorder (MDD). These issues are particularly pertinent to the development of translational applications of neuroimaging as they represent challenges for which clinical observation alone is insufficient. We therefore applied pattern classification to task-based functional magnetic resonance imaging (fMRI) data of the n-back working memory task, to test their predictive value in differentiating patients with BD (n=30) from healthy individuals (n=30) and from patients' relatives who were either diagnosed with MDD (n=30) or were free of any personal lifetime history of psychopathology (n=30). Diagnostic stability in these groups was confirmed with 4-year prospective follow-up. Task-based activation patterns from the fMRI data were analyzed with Gaussian Process Classifiers (GPC), a machine learning approach to detecting multivariate patterns in neuroimaging datasets. Consistent significant classification results were only obtained using data from the 3-back versus 0-back contrast. Using contrast, patients with BD were correctly classified compared to unrelated healthy individuals with an accuracy of 83.5%, sensitivity of 84.6% and specificity of 92.3%. Classification accuracy, sensitivity and specificity when comparing patients with BD to their relatives with MDD, were respectively 73.1%, 53.9% and 94.5%. Classification accuracy, sensitivity and specificity when comparing patients with BD to their healthy relatives were respectively 81.8%, 72.7% and 90.9%. We show that significant individual classification can be achieved using whole brain pattern analysis of task-based working memory fMRI data. The high accuracy and specificity achieved by all three classifiers suggest that multivariate pattern recognition analyses can aid clinicians in the clinical care of BD in situations of true clinical uncertainty regarding the diagnosis and prognosis.