162 resultados para MDD


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Background The objective was to examine the course and longitudinal associations of generalized anxiety disorder (GAD) and major depressive disorder (MDD) in mothers over the postpartum 2 years. Method Using a prospective naturalistic design, 296 mothers recruited from a large community pool were assessed for GAD and MDD at 3, 6, 10, 14, and 24 months postpartum. Structured clinical interviews were used for diagnoses, and symptoms were assessed using self-report questionnaires. Logistic regression analyses were used to examine diagnostic stability and longitudinal relations, and latent variable modeling was employed to examine change in symptoms. Results MDD without co-occurring GAD, GAD without co-occurring MDD, and co-occurring GAD and MDD, displayed significant stability during the postpartum period. Whereas MDD did not predict subsequent GAD, GAD predicted subsequent MDD (in the form of GAD + MDD). Those with GAD + MDD at 3 months postpartum were significantly less likely to be diagnosis free during the follow-up period than those in other diagnostic categories. At the symptom level, symptoms of GAD were more trait-like than those of depression. Conclusions Postpartum GAD and MDD are relatively stable conditions, and GAD is a risk factor for MDD but not vice versa. Given the tendency of MDD and GAD to be persistent, especially when comorbid, and the increased risk for MDD in mothers with GAD, as well as the potential negative effects of cumulative exposure to maternal depression and anxiety on child development, the present findings clearly highlight the need for screening and treatment of GAD in addition to MDD during the postpartum period.

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Various trials have been conducted evaluating depression management programs for patients with Coronary Heart Disease (CHD). However, to date, the most effective way to manage this co-morbidity in the real world setting remains unclear. To better understand the past successes and failures of previous trials and subsequently develop suitable interventions that target key components of health related quality of life (HRQOL) such as mental, physical and vocational functioning, we first need to understand the mechanisms underpinning the relationship between the two conditions. This paper will draw on the key literature in this field as identified by psychiatric, medical and social sciences databases (Cochrane Central Register of Controlled Trials, PubMed, OVID, Medline) available up to January 2012, with the aim to conduct a narrative review which explores: the aetiological relationship between depression and CHD; its association with HRQOL; the relationship between CHD, depression and vocational functioning; and the impact of depression treatment on these outcomes. Key recommendations are made regarding the management of this prevalent co-morbidity in clinical settings.

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Aspect Oriented approaches associated to different activities of the software development process are, in general, independent and their models and artifacts are not aligned and inserted in a coherent process. In the model driven development, the various models and the correspondence between them are rigorously specified. With the integration of aspect oriented software development (DSOA) and model driven development (MDD) it is possible to automatically propagate models from one activity to another, avoiding the loss of information and important decisions established in each activity. This work presents MARISA-MDD, a strategy based on models that integrate aspect-oriented requirements, architecture and detailed design, using the languages AOV-graph, AspectualACME and aSideML, respectively. MARISA-MDD defines, for each activity, representative models (and corresponding metamodels) and a number of transformations between the models of each language. These transformations have been specified and implemented in ATL (Atlas Definition Language), in the Eclipse environment. MARISA-MDD allows the automatic propagation between AOV-graph, AspectualACME, and aSideML models. To validate the proposed approach two case studies, the Health Watcher and the Mobile Media have been used in the MARISA-MDD environment for the automatic generation of AspectualACME and aSideML models, from the AOV-graph model

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Aspect-Oriented Software Development (AOSD) is a technique that complements the Object- Oriented Software Development (OOSD) modularizing several concepts that OOSD approaches do not modularize appropriately. However, the current state-of-the art on AOSD suffers with software evolution, mainly because aspect definition can stop to work correctly when base elements evolve. A promising approach to deal with that problem is the definition of model-based pointcuts, where pointcuts are defined based on a conceptual model. That strategy makes pointcut less prone to software evolution than model-base elements. Based on that strategy, this work defines a conceptual model at high abstraction level where we can specify software patterns and architectures that through Model Driven Development techniques they can be instantiated and composed in architecture description language that allows aspect modeling at architecture level. Our MDD approach allows propagate concepts in architecture level to another abstraction levels (design level, for example) through MDA transformation rules. Also, this work shows a plug-in implemented to Eclipse platform called AOADLwithCM. That plug-in was created to support our development process. The AOADLwithCM plug-in was used to describe a case study based on MobileMedia System. MobileMedia case study shows step-by-step how the Conceptual Model approach could minimize Pointcut Fragile Problems, due to software evolution. MobileMedia case study was used as input to analyses evolutions on software according to software metrics proposed by KHATCHADOURIAN, GREENWOOD and RASHID. Also, we analyze how evolution in base model could affect maintenance on aspectual model with and without Conceptual Model approaches

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The approach Software Product Line (SPL) has become very promising these days, since it allows the production of customized systems on large scale through product families. For the modeling of these families the Features Model is being widely used, however, it is a model that has low level of detail and not may be sufficient to guide the development team of LPS. Thus, it is recommended add the Features Model to other models representing the system from other perspectives. The goals model PL-AOVgraph can assume this role complementary to the Features Model, since it has a to context oriented language of LPS's, which allows the requirements modeling in detail and identification of crosscutting concerns that may arise as result of variability. In order to insert PL-AOVgraph in development of LPS's, this paper proposes a bi-directional mapping between PL-AOVgraph and Features Model, which will be automated by tool ReqSys-MDD. This tool uses the approach of Model-Driven Development (MDD), which allows the construction of systems from high level models through successive transformations. This enables the integration of ReqSys-MDD with other tools MDD that use their output models as input to other transformations. So it is possible keep consistency among the models involved, avoiding loss of informations on transitions between stages of development

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Context: Today’s project managers have a myriad of methods to choose from for the development of software applications. However, they lack empirical data about the character of these methods in terms of usefulness, ease of use or compatibility, all of these being relevant variables to assess the developer’s intention to use them. Objective: To compare three methods, each following a different paradigm (Model-Driven, Model-Based and Code-Centric) with respect to their adoption potential by junior software developers engaged in the development of the business layer of a Web 2.0 application. Method: We have conducted a quasi-experiment with 26 graduate students of the University of Alicante. The application developed was a Social Network, which was organized around a fixed set of modules. Three of them, similar in complexity, were used for the experiment. Subjects were asked to use a different method for each module, and then to answer a questionnaire that gathered their perceptions during such use. Results: The results show that the Model-Driven method is regarded as the most useful, although it is also considered the least compatible with previous developers’ experiences. They also show that junior software developers feel comfortable with the use of models, and that they are likely to use them if the models are accompanied by a Model-Driven development environment. Conclusions: Despite their relatively low level of compatibility, Model-Driven development methods seem to show a great potential for adoption. That said, however, further experimentation is needed to make it possible to generalize the results to a different population, different methods, other languages and tools, different domains or different application sizes.

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Objective - We report the first randomised controlled trial (RCT) using a combination of St. John’s wort (SJW) and Kava for the treatment of major depressive disorder (MDD) with comorbid anxiety. Methods - Twenty-eight adults with MDD and co-occurring anxiety were recruited for a double-blind RCT. After a placebo run-in of 2 weeks, the trial had a crossover design testing SJW and Kava against placebo over two controlled phases, each of 4 weeks. The primary analyses used intention-to-treat and completer analyses. Results - On both intention-to-treat ( p¼0.047) and completer analyses ( p¼0.003), SJW and Kava gave a significantly greater reduction in self-reported depression on the Beck Depression Inventory (BDI-II) over placebo in the first controlled phase. However, in the crossover phase, a replication of those effects in the delayed medication group did not occur. Nor were there significant effects on anxiety or quality of life. Conclusion - There was some evidence of antidepressant effects using SJW and Kava in a small sample with comorbid anxiety. Possible explanations for the absence of anxiolysis may include a potential interaction with SJW, the presence of depression, or an inadequate dose of Kava.

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Background: Mood and anxiety disorders pose significant health burdens on the community. Kava and St John’s wort (SJW) are the most commonly used herbal medicines in the treatment of anxiety and depressive disorders, respectively. Objectives: To conduct a comprehensive review of kava and SJW, to review any evidence of efficacy, mode of action, pharmacokinetics, safety and use in Major Depressive Disorder (MDD), Bipolar Disorder (BP), Seasonal Affective Disorder (SAD), Generalized Anxiety Disorder (GAD), Social Phobia (SP), Panic Disorder (PD), Obsessive-Compulsive Disorder (OCD), and Post Traumatic Stress Disorder (PTSD). Methods: A systematic review was conducted using the electronic databases MEDLINE, CINAHL, and The Cochrane Library during late 2008. The search criteria involved mood and anxiety disorder search terms in combination with kava, Piper methysticum, kavalactones, St John’s wort, Hypericum perforatum, hypericin and hyperforin. Additional search criteria for safety, pharmacodynamics , and pharmacokinetics was employed. A subsequent forward search was conducted of the papers using Web of Science cited reference search. Results: Current evidence supports the use of SJW in treating mild-moderate depression, and for kava in treatment of generalized anxiety. In respect to the other disorders, only weak preliminary evidence exists for use of SJW in SAD. Currently there is no published human trial on use of kava in affective disorders, or in OCD, PTSD, PD or SP. These disorders constitute potential applications that warrant exploration. Conclusions: Current evidence for herbal medicines in the treatment of depression and anxiety only supports the use of Hypericum perforatum for depression, and Piper methysticum for generalized anxiety.

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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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Background Anxiety disorders and major depressive disorder (MDD) are common and disabling mental disorders. This paper aims to test the hypothesis that common mental disorders have become more prevalent over the past two decades. Methods We conducted a systematic review of prevalence, remission, duration, and excess mortality studies for anxiety disorders and MDD and then used a Bayesian meta-regression approach to estimate point prevalence for 1990, 2005, and 2010. We also conducted a post-hoc search for studies that used the General Health Questionnaire (GHQ) as a measure of psychological distress and tested for trends to present a qualitative comparison of study findings. Results This study found no evidence for an increased prevalence of anxiety disorders or MDD. While the crude number of cases increased by 36%, this was explained by population growth and changing age structures. Point prevalence of anxiety disorders was estimated at 3.8% (3.6-4.1%) in 1990 and 4.0% (3.7-4.2%) in 2010. The prevalence of MDD was unchanged at 4.4% in 1990 (4.2-4.7%) and 2010 (4.1-4.7%). However, 8 of the 11 GHQ studies found a significant increase in psychological distress over time. Conclusions The perceived "epidemic" of common mental disorders is most likely explained by the increasing numbers of affected patients driven by increasing population sizes. Additional factors that may explain this perception include the higher rates of psychological distress as measured using symptom checklists, greater public awareness, and the use of terms such as anxiety and depression in a context where they do not represent clinical disorders.

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Background Cardiovascular disease and mental health both hold enormous public health importance, both ranking highly in results of the recent Global Burden of Disease Study 2010 (GBD 2010). For the first time, the GBD 2010 has systematically and quantitatively assessed major depression as an independent risk factor for the development of ischemic heart disease (IHD) using comparative risk assessment methodology. Methods A pooled relative risk (RR) was calculated from studies identified through a systematic review with strict inclusion criteria designed to provide evidence of independent risk factor status. Accepted case definitions of depression include diagnosis by a clinician or by non-clinician raters adhering to Diagnostic and Statistical Manual of Mental Disorders (DSM) or International Classification of Diseases (ICD) classifications. We therefore refer to the exposure in this paper as major depression as opposed to the DSM-IV category of major depressive disorder (MDD). The population attributable fraction (PAF) was calculated using the pooled RR estimate. Attributable burden was calculated by multiplying the PAF by the underlying burden of IHD estimated as part of GBD 2010. Results The pooled relative risk of developing IHD in those with major depression was 1.56 (95% CI 1.30 to 1.87). Globally there were almost 4 million estimated IHD disability-adjusted life years (DALYs), which can be attributed to major depression in 2010; 3.5 million years of life lost and 250,000 years of life lived with a disability. These findings highlight a previously underestimated mortality component of the burden of major depression. As a proportion of overall IHD burden, 2.95% (95% CI 1.48 to 4.46%) of IHD DALYs were estimated to be attributable to MDD in 2010. Eastern Europe and North Africa/Middle East demonstrate the highest proportion with Asia Pacific, high income representing the lowest. Conclusions The present work comprises the most robust systematic review of its kind to date. The key finding that major depression may be responsible for approximately 3% of global IHD DALYs warrants assessment for depression in patients at high risk of developing IHD or at risk of a repeat IHD event.

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Background Although the detrimental impact of major depressive disorder (MDD) at the individual level has been described, its global epidemiology remains unclear given limitations in the data. Here we present the modelled epidemiological profile of MDD dealing with heterogeneity in the data, enforcing internal consistency between epidemiological parameters and making estimates for world regions with no empirical data. These estimates were used to quantify the burden of MDD for the Global Burden of Disease Study 2010 (GBD 2010). Method Analyses drew on data from our existing literature review of the epidemiology of MDD. DisMod-MR, the latest version of the generic disease modelling system redesigned as a Bayesian meta-regression tool, derived prevalence by age, year and sex for 21 regions. Prior epidemiological knowledge, study- and country-level covariates adjusted sub-optimal raw data. Results There were over 298 million cases of MDD globally at any point in time in 2010, with the highest proportion of cases occurring between 25 and 34 years. Global point prevalence was very similar across time (4.4% (95% uncertainty: 4.2–4.7%) in 1990, 4.4% (4.1–4.7%) in 2005 and 2010), but higher in females (5.5% (5.0–6.0%) compared to males (3.2% (3.0–3.6%) in 2010. Regions in conflict had higher prevalence than those with no conflict. The annual incidence of an episode of MDD followed a similar age and regional pattern to prevalence but was about one and a half times higher, consistent with an average duration of 37.7 weeks. Conclusion We were able to integrate available data, including those from high quality surveys and sub-optimal studies, into a model adjusting for known methodological sources of heterogeneity. We were also able to estimate the epidemiology of MDD in regions with no available data. This informed GBD 2010 and the public health field, with a clearer understanding of the global distribution of MDD.