668 resultados para Bipolar Affective-disorder


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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 and Aims: True Colours is an online prospective mood-monitoring system developed at the University of Oxford to assist local patients and clinicians with monitoring course of illness in bipolar disorder. We report our initial experiences of using True Colours for research purposes in the Bipolar Disorder Research Network (BDRN; www.bdrn.org), a large research network of individuals with mood disorders spread throughout the UK. Methods: After initial piloting to ensure the practicality/acceptability of using True Colours within BDRN, we invited all BDRN participants (n = 7000) to participate in weekly True Colours ratings via three postal invitations sent over an 8-month period. Results: Following the three postal invitations, 915 individuals have so far expressed an interest in joining True Colours, and, of these, 662 (72.3%) have registered. 32 of those who registered for True Colours (5%) have so far asked to leave the system. Positive feedback from participants has focused around the ease of use and convenience of True Colours and potential clinical utility of the graphical representation of weekly mood scores. Conclusions: We have demonstrated that large-scale prospective mood monitoring for research purposes using a contemporary online approach is feasible. Challenges have included: (i) variation in participants’ technological ability; (ii) management of requests for clinical advice based on mood scores within a research setting; and, (iii) resources required to provide access and on-going support for participants using True Colours. We continue to expand recruitment to True Colours within BDRN, and plan to trial email invitations in the next phase of recruitment.

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Background and Aims Affective instability (AI), childhood trauma, and mental illness are linked, but evidence in affective disorders is limited, despite both AI and childhood trauma being associated with poorer outcomes. Aims were to compare AI levels in bipolar disorder I (BPI) and II (BPII), and major depressive disorder recurrent (MDDR), and to examine the association of AI and childhood trauma within each diagnostic group. Methods AI, measured using the Affective Lability Scale (ALS), was compared between people with DSM-IV BPI (n = 923), BPII (n = 363) and MDDR (n = 207) accounting for confounders and current mood. Regression modelling was used to examine the association between AI and childhood traumas in each diagnostic group. Results ALS scores in descending order were BPII, BPI, MDDR, and differences between groups were significant (p < 0.05). Within the BPI group any childhood abuse (p = 0.021), childhood physical abuse (p = 0.003) and the death of a close friend in childhood (p = 0.002) were significantly associated with higher ALS score but no association was found between childhood trauma and AI in BPII and MDDR. Conclusions AI is an important dimension in bipolar disorder independent of current mood state. There is a strong link between childhood traumatic events and AI levels in BPI and this may be one way in which exposure and disorder are linked. Clinical interventions targeting AI in people who have suffered significant childhood trauma could potentially change the clinical course of bipolar disorder.

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Objective: The study was designed to validate use of elec-tronic health records (EHRs) for diagnosing bipolar disorder and classifying control subjects. Method: EHR data were obtained from a health care system of more than 4.6 million patients spanning more than 20 years. Experienced clinicians reviewed charts to identify text features and coded data consistent or inconsistent with a diagnosis of bipolar disorder. Natural language processing was used to train a diagnostic algorithm with 95% specificity for classifying bipolar disorder. Filtered coded data were used to derive three additional classification rules for case subjects and one for control subjects. The positive predictive value (PPV) of EHR-based bipolar disorder and subphenotype di- agnoses was calculated against diagnoses from direct semi- structured interviews of 190 patients by trained clinicians blind to EHR diagnosis. Results: The PPV of bipolar disorder defined by natural language processing was 0.85. Coded classification based on strict filtering achieved a value of 0.79, but classifications based on less stringent criteria performed less well. No EHR- classified control subject received a diagnosis of bipolar dis- order on the basis of direct interview (PPV=1.0). For most subphenotypes, values exceeded 0.80. The EHR-based clas- sifications were used to accrue 4,500 bipolar disorder cases and 5,000 controls for genetic analyses. Conclusions: Semiautomated mining of EHRs can be used to ascertain bipolar disorder patients and control subjects with high specificity and predictive value compared with diagnostic interviews. EHRs provide a powerful resource for high-throughput phenotyping for genetic and clinical research.

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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.

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Substance misuse in people with serious mental disorders is common and has a wideranging negative impact. The multiplicity of problems suggests that this comorbidity is better conceptualized as a type of complex disorder than by ‘dual diagnosis’. Problems with sequential and parallel treatments have led to the development of integrated approaches, with one practitioner or team addressing both the substance use and mental disorder. These treatments are typically characterized by motivation enhancement, minimizing treatment-related stress, emphasizing harm reduction as well as abstinence, and assertive outreach. A review of published randomized trials demonstrates that superior effects to controls are rarely consistent across treatment foci and over time. While motivational interventions assist engagement, more intervention is usually required for integrated treatment programs to improve long-term outcomes more than control conditions. More intensive case management does not consistently improve impact, but extended cognitive-behavioral therapies have promise. Suggestions for maximizing treatment effects and improving research evidence are provided.

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Previous studies yielded evidence for dysbindin (DTNBP1) to impact the pathogenesis of schizophrenia on the one hand and affective disorders such as bipolar or major depressive disorder (MDD) on the other. Thus, in the present study we investigated whether DTNBP1 variation was associated with psychotic depression as a severe clinical manifestation of MDD possibly constituting an overlapping phenotype between affective disorders and schizophrenia. A sample of 243 Caucasian inpatients with MDD (SCID-I) was genotyped for 12 SNPs spanning 92% of the DTNBP1 gene region. Differences in DTNBP1 genotype distributions across diagnostic subgroups of psychotic (N = 131) vs. non-psychotic depression were estimated by Pearson Chi2 test and logistic regression analyses adjusted for age, gender, Beck Depression Inventory (BDI) and the Global Assessment of Functioning Scale (GAF). Overall, patients with psychotic depression presented with higher BDI and lower GAF scores expressing a higher severity of the illness as compared to depressed patients without psychotic features. Four DTNBP1 SNPs, particularly rs1997679 and rs9370822, and the corresponding haplotypes, respectively, were found to be significantly associated with the risk of psychotic depression in an allele-dose fashion. In summary, the present results provide preliminary support for dysbindin (DTNBP1) gene variation, particularly SNPs rs1997679 and rs9370822, to be associated with the clinical phenotype of psychotic depression suggesting a possible neurobiological mechanism for an intermediate trait on the continuum between affective disorders and schizophrenia.

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Negative mood regulation (NMR) expectancies, stress, anxiety, depression and affect intensity were examined by means of self-report questionnaires in 158 volunteers, including 99 clients enrolled in addiction treatment programs. As expected, addicts reported significantly higher levels of stress, anxiety, depression and affect intensity and lower levels of NMR compared to non-addict controls. NMR was negatively correlated with stress, anxiety, depression and affect intensity. The findings indicate that mood self-regulation is impaired in addicts. Low NMR and high affect intensity may predispose to substance abuse and addiction, or alternatively may reflect chronic drug-induced affective dysregulation.

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Much of what we know regarding the long-term course and outcome of major depressive disorder (MDD) is based on studies of mostly inpatient tertiary level cohorts and samples predating the era of the current antidepressants and the use of maintenance therapies. In addition, there is a lack of studies investigating the comprehensive significance of comorbid axis I and II disorders on the outcome of MDD. The present study forms a part of the Vantaa Depression Study (VDS), a regionally representative prospective and naturalistic cohort study of 269 secondary-level care psychiatric out- and inpatients (aged 20-59) with a new episode of DSM-IV MDD, and followed-up up to five years (n=182) with a life-chart and semistructured interviews. The aim was to investigate the long-term outcome of MDD and risk factors for poor recovery, recurrences, suicidal attempts and diagnostic switch to bipolar disorder, and the association of a family history of different psychiatric disorders on the outcome. The effects of comorbid disorders together with various other predictors from different domains on the outcome were comprehensively investigated. According to this study, the long-term outcome of MDD appears to be more variable when its outcome is investigated among modern, community-treated, secondary-care outpatients compared to previous mostly inpatient studies. MDD was also highly recurrent in these settings, but the recurrent episodes seemed shorter, and the outcome was unlikely to be uniformly chronic. Higher severity of MDD predicted significantly the number of recurrences and longer time spent ill. In addition, longer episode duration, comorbid dysthymic disorder, cluster C personality disorders and social phobia predicted a worse outcome. The incidence rate of suicide attempts varied robustly de¬pending on the level of depression, being 21-fold during major depressive episodes (MDEs), and 4-fold during partial remission compared to periods of full remission. Although a history of previous attempts and poor social support also indicated risk, time spent depressed was the central factor determining overall long-term risk. Switch to bipolar disorder occurred mainly to type II, earlier to type I, and more gradually over time to type II. Higher severity of MDD, comorbid social phobia, obsessive compulsive disorder, and cluster B personality disorder features predicted the diagnostic switch. The majority of patients were also likely to have positive family histories not exclusively of mood, but also of other mental disorders. Having a positive family history of severe mental disorders was likely to be clinically associated with a significantly more adverse outcome.

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This study is part of an ongoing collaborative bipolar research project, the Jorvi Bipolar Study (JoBS). The JoBS is run by the Department of Mental Health and Alcohol Research of the National Public Health Institute, Helsinki, and the Department of Psychiatry, Jorvi Hospital, Helsinki University Central Hospital (HUCH), Espoo, Finland. It is a prospective, naturalistic cohort study of secondary level care psychiatric in- and outpatients with a new episode of bipolar disorder (BD). The second report also included 269 major depressive disorder (MDD) patients from the Vantaa Depression Study (VDS). The VDS was carried out in collaboration with the Department of Psychiatry of the Peijas Medical Care District. Using the Mood Disorder Questionnaire (MDQ), all in- and outpatients at the Department of Psychiatry at Jorvi Hospital who currently had a possible new phase of DSM-IV BD were sought. Altogether, 1630 psychiatric patients were screened, and 490 were interviewed using a semistructured interview (SCID-I/P). The patients included in the cohort (n=191) had at intake a current phase of BD. The patients were evaluated at intake and at 6- and 18-month interviews. Based on this study, BD is poorly recognized even in psychiatric settings. Of the BD patients with acute worsening of illness, 39% had never been correctly diagnosed. The classic presentations of BD with hospitalizations, manic episodes, and psychotic symptoms lead clinicians to correct diagnosis of BD I in psychiatric care. Time of follow-up elapsed in psychiatric care, but none of the clinical features, seemed to explain correct diagnosis of BD II, suggesting reliance on cross- sectional presentation of illness. Even though BD II was clearly less often correctly diagnosed than BD I, few other differences between the two types of BD were detected. BD I and II patients appeared to differ little in terms of clinical picture or comorbidity, and the prevalence of psychiatric comorbidity was strongly related to the current illness phase in both types. At the same time, the difference in outcome was clear. BD II patients spent about 40% more time depressed than BD I patients. Patterns of psychiatric comorbidity of BD and MDD differed somewhat qualitatively. Overall, MDD patients were likely to have more anxiety disorders and cluster A personality disorders, and bipolar patients to have more cluster B personality disorders. The adverse consequences of missing or delayed diagnosis are potentially serious. Thus, these findings strongly support the value of screening for BD in psychiatric settings, especially among the major depressive patients. Nevertheless, the diagnosis must be based on a clinical interview and follow-up of mood. Comorbidity, present in 59% of bipolar patients in a current phase, needs concomitant evaluation, follow-up, and treatment. To improve outcome in BD, treatment of bipolar depression is a major challenge for clinicians.

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Background: While pain is frequently associated with unipolar depression, few studies have investigated the link between pain and bipolar depression. In the present study we estimated the prevalence and characteristics of pain among patients with bipolar depression treated by psychiatrists in their regular clinical practice. The study was designed to identify factors associated with the manifestation of pain in these patients.- Methods:Patients diagnosed with bipolar disorder (n=121) were selected to participate in a cross-sectional study in which DSM-IV-TR criteria were employed to identify depressive episodes. The patients were asked to describe any pain experienced during the study, and in the 6 weeks beforehand, by means of a Visual Analogical Scale (VAS).- Results: Over half of the bipolar depressed patients (51.2%, 95% CI: 41.9%–60.6%), and 2/3 of the female experienced concomitant pain. The pain was of moderate to severe intensity and prolonged duration, and it occurred at multiple sites, significantly limiting the patient’s everyday activities. The most important factors associated with the presence of pain were older age, sleep disorders and delayed diagnosis of bipolar disorder.- Conclusions: Chronic pain is common in bipolar depressed patients, and it is related to sleep disorders and delayed diagnosis of their disorder. More attention should be paid to study the presence of pain in bipolar depressed patients, in order to achieve more accurate diagnoses and to provide better treatment options.

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Fear conditioning is an established model for investigating posttraumatic stress disorder (PTSD). However, symptom triggers may vaguely resemble the initial traumatic event, differing on a variety of sensory and affective dimensions. We extended the fear-conditioning model to assess generalization of conditioned fear on fear processing neurocircuitry in PTSD. Military veterans (n=67) consisting of PTSD (n=32) and trauma-exposed comparison (n=35) groups underwent functional magnetic resonance imaging during fear conditioning to a low fear-expressing face while a neutral face was explicitly unreinforced. Stimuli that varied along a neutral-to-fearful continuum were presented before conditioning to assess baseline responses, and after conditioning to assess experience-dependent changes in neural activity. Compared with trauma-exposed controls, PTSD patients exhibited greater post-study memory distortion of the fear-conditioned stimulus toward the stimulus expressing the highest fear intensity. PTSD patients exhibited biased neural activation toward high-intensity stimuli in fusiform gyrus (P<0.02), insula (P<0.001), primary visual cortex (P<0.05), locus coeruleus (P<0.04), thalamus (P<0.01), and at the trend level in inferior frontal gyrus (P=0.07). All regions except fusiform were moderated by childhood trauma. Amygdala-calcarine (P=0.01) and amygdala-thalamus (P=0.06) functional connectivity selectively increased in PTSD patients for high-intensity stimuli after conditioning. In contrast, amygdala-ventromedial prefrontal cortex (P=0.04) connectivity selectively increased in trauma-exposed controls compared with PTSD patients for low-intensity stimuli after conditioning, representing safety learning. In summary, fear generalization in PTSD is biased toward stimuli with higher emotional intensity than the original conditioned-fear stimulus. Functional brain differences provide a putative neurobiological model for fear generalization whereby PTSD symptoms are triggered by threat cues that merely resemble the index trauma.

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The present research focused on the pathways through which the symptoms of posttraumatic stress disorder (PTSD) may negatively impact intimacy. Previous research has confirmed a link between self-reported PTSD symptoms and intimacy; however, a thorough examination of mediating paths, partner effects, and secondary traumatization has not yet been realized. With a sample of 297 heterosexual couples, intraindividual and dyadic models were developed to explain the relationships between PTSD symptoms and intimacy in the context of interdependence theory, attachment theory, and models of selfpreservation (e.g., fight-or-flight). The current study replicated the findings of others and has supported a process in which affective (alexithymia, negative affect, positive affect) and communication (demand-withdraw behaviour, self-concealment, and constructive communication) pathways mediate the intraindividual and dyadic relationships between PTSD symptoms and intimacy. Moreover, it also found that the PTSD symptoms of each partner were significantly related; however, this was only the case for those dyads in which the partners had disclosed most everything about their traumatic experiences. As such, secondary traumatization was supported. Finally, although the overall pattern of results suggest a total negative effect of PTSD symptoms on intimacy, a sex difference was evident such that the direct effect of the woman's PTSD symptoms were positively associated with both her and her partner's intimacy. I t is possible that the Tend-andBefriend model of threat response, wherein women are said to foster social bonds in the face of distress, may account for this sex difference. Overall, however, it is clear that PTSD symptoms were negatively associated with relationship quality and attention to this impact in the development of diagnostic criteria and treatment protocols is necessary.

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Actuellement, le diagnostic différentiel du trouble bipolaire (TB) et du trouble de personnalité limite (TPL) à l’adolescence s’avère difficile et complique le choix thérapeutique. Portant sur le TB et le TPL, ce mémoire fait le point sur la littérature scientifique adulte et adolescente, vérifie la faisabilité et présente les résultats d’une étude exploratoire portant sur les variables cliniques (instabilité émotionnelle, hostilité, impulsivité, tempraément) et le rythme veille-sommeil à l’adolescence. L’étude exploratoire comprend sept adolescents TB et huit TPL (12-17 ans), évalués par questionnaires autoadministrés pour les variables cliniques, et par actigraphie et agenda de sommeil pour le rythme veille-sommeil. Aucune différence significative n’existe entre les deux troubles pour les variables cliniques. En moyenne, les adolescents TB ont porté l'actigraphie pendant 9,9 jours et ont rempli un agenda de sommeil pendant 5,7 jours; chez les TPL, les chiffres sont respectivement 9,8 et 8,9 jours. Comparés aux TPL, les TB ont un plus grand intervalle d’éveil (p=0,035), ont un plus grand intervalle de sommeil (p>0,05), et ont une plus grand variabilité intrajournalière (p=0,04). Les données subjectives (agenda de sommeil) semblent refléter les données objectives (actigraphie) : aucune différence statistique n’est observée entre les deux mesures pour le délai d’endormissement, la durée du dernier réveil et le temps total de sommeil. La recension de la littérature montre un manque de données chez l’adolescent quant aux deux troubles. La faisabilité de l’étude est démontrée par la présence de résultats analysables. Ceci encourage la poursuite des recherches sur ces variables, afin de distinguer les deux psychopathologies à l’adolescence.