Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 20 de 275
Filtrar
1.
Bipolar Disord ; 2021 Oct 02.
Artigo em Inglês | MEDLINE | ID: mdl-34599629

RESUMO

OBJECTIVES: The 2018 Canadian Network for Mood and Anxiety Treatments (CANMAT) and International Society for Bipolar Disorders (ISBD) guidelines provided clinicians with pragmatic treatment recommendations for bipolar disorder (BD). While these guidelines included commentary on how mixed features may direct treatment selection, specific recommendations were not provided- a critical gap which the current update aims to address. METHOD: Overview of research regarding mixed presentations in BD, with treatment recommendations developed using a modified CANMAT/ISBD rating methodology. Limitations are discussed, including the dearth of high-quality data and reliance on expert opinion. RESULTS: No agents met threshold for first line treatment of DSM-5 manic or depressive episodes with mixed features. For mania + mixed features second line treatment options include asenapine, cariprazine, divalproex, and aripiprazole. In depression + mixed features, cariprazine and lurasidone are recommended as second line options. For DSM-IV defined mixed episodes, with a longer history of research, asenapine and aripiprazole are first line, and olanzapine (monotherapy or combination), carbamazepine, and divalproex are second line. Research on maintenance treatments following a DSM-5 mixed presentation is extremely limited, with third-line recommendations based on expert opinion. For maintenance treatment following a DSM-IV mixed episode, quetiapine (monotherapy or combination) is first line, and lithium and olanzapine identified as second line options. CONCLUSION: The CANMAT and ISBD groups hope these guidelines provide valuable support for clinicians providing care to patients experiencing mixed presentations, as well as further influence investment in research to improve diagnosis and treatment of this common and complex clinical state.

2.
J Clin Psychiatry ; 82(5)2021 Sep 28.
Artigo em Inglês | MEDLINE | ID: mdl-34587377

RESUMO

Objective: To determine the efficacy of measurement-based care (MBC), defined as routinely administered outcome measures with practitioner and patient review to inform clinical decision-making, for adults with depressive disorders.Data Sources: Embase, MEDLINE, PsycINFO, ClinicalTrials.gov, CNKI, and Wanfang Data were searched through July 1, 2020, using search terms for measurement-based care, depression, antidepressant or pharmacotherapy, and randomized controlled trials (RCTs), without language restriction.Study Selection: Of 8,879 articles retrieved, 7 RCTs (2,019 participants) evaluating MBC for depressive disorders, all involving pharmacotherapy, were included.Data Extraction: Two independent reviewers extracted data. The primary outcome was response rate (≥ 50% improvement from baseline to endpoint on a depression scale). Secondary clinical outcomes were remission rate (endpoint score in remission range), difference in endpoint severity, and medication adherence.Results: Meta-analysis with random-effects models found no significant difference between MBC and comparison groups in response rates (3 studies; odds ratio [OR] = 1.66; 95% CI, 0.66-4.17; P = .279). MBC was associated with significantly greater remission rates (5 studies; OR = 1.83; 95% CI, 1.12-2.97; P = .015), lower endpoint severity (5 studies; standardized mean difference = 0.53; CI 0.06-0.99; P = .026), and greater medication adherence (3 studies; OR = 1.68; 95% CI, 1.22-2.30; P = .001).Conclusions: Although benefits for clinical response are unclear, MBC is effective in decreasing depression severity, promoting remission, and improving medication adherence in patients with depressive disorders treated with pharmacotherapy. The results are limited by the small number of included trials, high risk of bias, and significant study heterogeneity.

3.
BMC Psychiatry ; 21(1): 430, 2021 09 01.
Artigo em Inglês | MEDLINE | ID: mdl-34470624

RESUMO

BACKGROUND: Measurement-based care (MBC) is an evidence-based practice for depression, but its use by clinicians remains low. Enhanced MBC (eMBC), which uses digital technologies, can help to facilitate the use of MBC by clinicians and patients. Understanding factors that act as barriers and drivers to the implementation of MBC and eMBC is important to support the design of implementation strategies, promoting uptake by clinicians and patients. OBJECTIVE: This situational analysis identifies barriers and facilitators to the implementation of standard and eMBC at mental health centers in Shanghai, China. METHODS: We used mixed methods to develop a comprehensive understanding of the factors influencing MBC and eMBC implementation in Shanghai. This study took place across three mental health centers in Shanghai. We used situational analysis tools to collect contextual information about the three centers, conducted surveys with n = 116 clinicians and n = 301 patients, conducted semi-structured interviews with n = 30 clinicians and six focus groups with a total of n = 19 patients. Surveys were analysed using descriptive statistics, and semi-structured interviews and focus groups were analysed using framework analysis. RESULTS: Several potential barriers and facilitators to MBC and eMBC implementation were identified. Infrastructure, cost, attitudes and beliefs, and perceptions about feasibility and efficacy emerged as both challenges and drivers to MBC and eMBC implementation in Shanghai. CONCLUSIONS: The results of this study will directly inform the design of an implementation strategy for MBC and eMBC in Shanghai, that will be tested via a randomized controlled trial. This study contributes to the emerging body of literature on MBC implementation and, to the best of our knowledge, is the first such study to take place in Asia. This study identifies several factors that are relevant to the equitable delivery of MBC, recognizing the need to explicitly address equity concerns in global mental health implementation research.


Assuntos
Depressão , Saúde Mental , China , Grupos Focais , Humanos , Inquéritos e Questionários
4.
Transl Psychiatry ; 11(1): 469, 2021 09 08.
Artigo em Inglês | MEDLINE | ID: mdl-34508068

RESUMO

The pathophysiology of major depressive disorder (MDD) encompasses an array of changes at molecular and neurobiological levels. As chronic stress promotes neurotoxicity there are alterations in the expression of genes and gene-regulatory molecules. The hippocampus is particularly sensitive to the effects of stress and its posterior volumes can deliver clinically valuable information about the outcomes of antidepressant treatment. In the present work, we analyzed individuals with MDD (N = 201) and healthy controls (HC = 104), as part of the CAN-BIND-1 study. We used magnetic resonance imaging (MRI) to measure hippocampal volumes, evaluated gene expression with RNA sequencing, and assessed DNA methylation with the (Infinium MethylationEpic Beadchip), in order to investigate the association between hippocampal volume and both RNA expression and DNA methylation. We identified 60 RNAs which were differentially expressed between groups. Of these, 21 displayed differential methylation, and seven displayed a correlation between methylation and expression. We found a negative association between expression of Brain Abundant Membrane Attached Signal Protein 1 antisense 1 RNA (BASP1-AS1) and right hippocampal tail volume in the MDD group (ß = -0.218, p = 0.021). There was a moderating effect of the duration of the current episode on the association between the expression of BASP1-AS1 and right hippocampal tail volume in the MDD group (ß = -0.48, 95% C.I. [-0.80, -0.16]. t = -2.95 p = 0.004). In conclusion, we found that overexpression of BASP1-AS1 was correlated with DNA methylation, and was negatively associated with right tail hippocampal volume in MDD.


Assuntos
Transtorno Depressivo Maior , RNA Longo não Codificante , Metilação de DNA , Transtorno Depressivo Maior/genética , Hipocampo , Humanos , Imageamento por Ressonância Magnética
5.
Brain Stimul ; 14(6): 1447-1455, 2021 Sep 21.
Artigo em Inglês | MEDLINE | ID: mdl-34560319

RESUMO

BACKGROUND: Intermittent theta burst stimulation (iTBS) is a newer form of repetitive transcranial magnetic stimulation (rTMS) for patients with treatment resistant depression (TRD). Applying multiple daily iTBS sessions may enable patients to achieve remission more rapidly. OBJECTIVE: We compared the efficacy and tolerability of a twice-daily versus once-daily iTBS protocol in patients with TRD. We hypothesized that twice-daily iTBS would result in a greater improvement in depression scores compared to once-daily iTBS. METHODS: 208 participants (131 females) with TRD were randomized to receive either iTBS (600 pulses) delivered twice-daily with a 54-min interval between treatments or once-daily (1200 pulses) with 1 sham treatment with the same interval between treatments, to ensure equal levels of daily therapeutic contact and blinding of patients and raters. The primary outcome measure was change in depression scores on the Hamilton Rating Scale for Depression (HRSD-17) after 10 days of treatment and 30 days of treatments. RESULTS: HRSD-17 scores improved in both the twice-daily and once-daily iTBS groups; however, these improvements did not significantly differ between the two groups at either the 10-day or 30-day timepoints. Response and remission rates were low (<10%) in both groups after 10 days and consistent with prior reports at 30 days; these rates did not differ between the treatment groups. CONCLUSIONS: These results suggest that twice-daily iTBS does not accelerate response to iTBS and is not different from once-daily treatment in terms of improving depressive symptoms in patients with TRD. Clinicaltrials.gov ID: NCT02729792 (https://clinicaltrials.gov/ct2/show/NCT02729792).

6.
Cereb Cortex ; 2021 Aug 20.
Artigo em Inglês | MEDLINE | ID: mdl-34416758

RESUMO

Understanding the neural underpinnings of major depressive disorder (MDD) and its treatment could improve treatment outcomes. So far, findings are variable and large sample replications scarce. We aimed to replicate and extend altered functional connectivity associated with MDD and pharmacotherapy outcomes in a large, multisite sample. Resting-state fMRI data were collected from 129 patients and 99 controls through the Canadian Biomarker Integration Network in Depression. Symptoms were assessed with the Montgomery-Åsberg Depression Rating Scale (MADRS). Connectivity was measured as correlations between four seeds (anterior and posterior cingulate cortex, insula and dorsolateral prefrontal cortex) and all other brain voxels. Partial least squares was used to compare connectivity prior to treatment between patients and controls, and between patients reaching remission (MADRS ≤ 10) early (within 8 weeks), late (within 16 weeks), or not at all. We replicated previous findings of altered connectivity in patients. In addition, baseline connectivity of the anterior/posterior cingulate and insula seeds differentiated patients with different treatment outcomes. The stability of these differences was established in the largest single-site subsample. Our replication and extension of altered connectivity highlighted previously reported and new differences between patients and controls, and revealed features that might predict remission prior to pharmacotherapy. Trial registration:  ClinicalTrials.gov: NCT01655706.

7.
Can J Psychiatry ; : 7067437211037141, 2021 Aug 11.
Artigo em Inglês | MEDLINE | ID: mdl-34379019

RESUMO

BACKGROUND: Major depressive disorder (MDD) is a common and burdensome condition that has low rates of treatment success for each individual treatment. This means that many patients require several medication switches to achieve remission; selecting an effective antidepressant is typically a sequential trial-and-error process. Machine learning techniques may be able to learn models that can predict whether a specific patient will respond to a given treatment, before it is administered. This study uses baseline clinical data to create a machine-learned model that accurately predicts remission status for a patient after desvenlafaxine (DVS) treatment. METHODS: We applied machine learning algorithms to data from 3,399 MDD patients (90% of the 3,776 subjects in 11 phase-III/IV clinical trials, each described using 92 features), to produce a model that uses 26 of these features to predict symptom remission, defined as an 8-week Hamilton Depression Rating Scale score of 7 or below. We evaluated that learned model on the remaining held-out 10% of the data (n = 377). RESULTS: Our resulting classifier, a trained linear support vector machine, had a holdout set accuracy of 69.0%, significantly greater than the probability of classifying a patient correctly by chance. We demonstrate that this learning process is stable by repeatedly sampling part of the training dataset and running the learner on this sample, then evaluating the learned model on the held-out instances of the training set; these runs had an average accuracy of 67.0% ± 1.8%. CONCLUSIONS: Our model, based on 26 clinical features, proved sufficient to predict DVS remission significantly better than chance. This may allow more accurate use of DVS without waiting 8 weeks to determine treatment outcome, and may serve as a first step toward changing psychiatric care by incorporating clinical assistive technologies using machine-learned models.

8.
Transl Psychiatry ; 11(1): 439, 2021 08 21.
Artigo em Inglês | MEDLINE | ID: mdl-34420030

RESUMO

Identifying biomarkers of antidepressant response may advance personalized treatment of major depressive disorder (MDD). We aimed to identify longitudinal changes in gene expression associated with response to antidepressants in a sample of MDD patients treated with escitalopram. Patients (N = 153) from the CAN-BIND-1 cohort were treated for 8 weeks, and depressive symptoms were assessed using the Montgomery-Åsberg Depression Rating Scale at 0, 2, 4, 6, and 8 weeks. We identified three groups of patients according to response status: early responders (22.9%), later responders (32.0%), and nonresponders (45.1%). RNA sequencing was performed in blood obtained at weeks 0, 2, and 8. RNA expression was modeled using growth models, and differences in the longitudinal changes in expression according to response were investigated using multiple regression models. The expression of RNAs related to response was investigated in the brains of depressed individuals, as well as in neuronal cells in vitro. We identified four RNAs (CERCAM, DARS-AS1, FAM228B, HBEGF) whose change over time was independently associated with a response status. For all except HBEGF, responders showed higher expression over time, compared to nonresponders. While the change in all RNAs differentiated early responders from nonresponders, changes in DARS-AS1 and HBEGF also differentiated later responders from nonresponders. Additionally, HBEGF was downregulated in the brains of depressed individuals, and increased in response to escitalopram treatment in vitro. In conclusion, using longitudinal assessments of gene expression, we provide insights into biological processes involved in the intermediate stages of escitalopram response, highlighting several genes with potential utility as biomarkers of antidepressant response.


Assuntos
Transtorno Depressivo Maior , Antidepressivos/uso terapêutico , Biomarcadores , Citalopram/uso terapêutico , Transtorno Depressivo Maior/tratamento farmacológico , Transtorno Depressivo Maior/genética , Expressão Gênica , Humanos , Escalas de Graduação Psiquiátrica , Resultado do Tratamento
9.
Int J Equity Health ; 20(1): 161, 2021 07 12.
Artigo em Inglês | MEDLINE | ID: mdl-34253198

RESUMO

BACKGROUND: The COVID-19 pandemic is expected to have profound mental health impact, including in the Asia Pacific Economic Cooperation (APEC) region. Some populations might be at higher risk of experiencing negative mental health impacts and may encounter increased barriers to accessing mental health care. The pandemic and related restrictions have led to changes in care delivery, including a rapid shift to the use of e-mental health and digital technologies. It is therefore essential to consider needs and opportunities for equitable mental health care delivery to the most at-risk populations. This rapid scoping review: 1) identifies populations in the APEC region that are at higher risk of the negative mental health impacts of COVID-19, 2) identifies needs and gaps in access to standard and e-mental health care among these populations, and 3) explores the potential of e-mental health to address these needs. METHODS: We conducted a rapid scoping review following the PRISMA Extension for Scoping Reviews (PRISMA-ScR). We searched Medline, Embase and PsychInfo databases and Google Scholar using a search strategy developed in consultation with a biomedical librarian. We included records related to mental health or psychosocial risk factors and COVID-19 among at-risk groups; that referred to one or more APEC member economies or had a global, thus generalizable, scope; English language papers, and papers with full text available. RESULTS: A total of 132 records published between December 2019 and August 2020 were included in the final analysis. Several priority at-risk populations, risk factors, challenges and recommendations for standard and e-mental health care were identified. Results demonstrate that e-mental health care can be a viable option for care delivery but that specific accessibility and acceptability considerations must be considered. Options for in-person, hybrid or "low-tech" care must also remain available. CONCLUSIONS: The COVID-19 pandemic has highlighted the urgent need for equitable standard and e-mental health care. It has also highlighted the persistent social and structural inequities that contribute to poor mental health. The APEC region is vast and diverse; findings from the region can guide policy and practice in the delivery of equitable mental health care in the region and beyond.


Assuntos
COVID-19/psicologia , Necessidades e Demandas de Serviços de Saúde , Transtornos Mentais/terapia , Pandemias , Telemedicina , Ásia/epidemiologia , COVID-19/epidemiologia , Humanos , Transtornos Mentais/epidemiologia , Ilhas do Pacífico/epidemiologia , Fatores de Risco
10.
Psychoneuroendocrinology ; 132: 105348, 2021 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-34229186

RESUMO

Dysfunction of the hypothalamic-pituitary-adrenal (HPA) axis is considered one of the mechanisms underlying the development of major depressive disorder (MDD), but the exact nature of this dysfunction is unknown. We investigated the relationship between hypothalamus volume (HV) and blood-derived DNA methylation in MDD. We obtained brain MRI, clinical and molecular data from 181 unmedicated MDD and 90 healthy control (HC) participants. MDD participants received a 16-week standardized antidepressant treatment protocol, as part of the first Canadian Biomarker Integration Network in Depression (CAN-BIND) study. We collected bilateral HV measures via manual segmentation by two independent raters. DNA methylation and RNA sequencing were performed for three key HPA axis-regulating genes coding for the corticotropin-binding protein (CRHBP), glucocorticoid receptor (NR3C1) and FK506 binding protein 5 (FKBP5). We used elastic net regression to perform variable selection and assess predictive ability of methylation variables on HV. Left HV was negatively associated with duration of current episode (ρ = -0.17, p = 0.035). We did not observe significant differences in HV between MDD and HC or any associations between HV and treatment response at weeks 8 or 16, overall depression severity, illness duration or childhood maltreatment. We also did not observe any differentially methylated CpG sites between MDD and HC groups. After assessing functionality by correlating methylation levels with RNA expression of the respective genes, we observed that the number of functionally relevant CpG sites differed between MDD and HC groups in FKBP5 (χ2 = 77.25, p < 0.0001) and NR3C1 (χ2 = 7.29, p = 0.007). Cross-referencing functionally relevant CpG sites to those that were highly ranked in predicting HV in elastic net modeling identified one site from FKBP5 (cg03591753) and one from NR3C1 (cg20728768) within the MDD group. Stronger associations between DNA methylation, gene expression and HV in MDD suggest a novel putative molecular pathway of stress-related sensitivity in depression. Future studies should consider utilizing the epigenome and ultra-high field MR data which would allow the investigation of HV sub-fields.

11.
Hum Brain Mapp ; 42(15): 4940-4957, 2021 Oct 15.
Artigo em Inglês | MEDLINE | ID: mdl-34296501

RESUMO

There is a growing interest in examining the wealth of data generated by fusing functional and structural imaging information sources. These approaches may have clinical utility in identifying disruptions in the brain networks that underlie major depressive disorder (MDD). We combined an existing software toolbox with a mathematically dense statistical method to produce a novel processing pipeline for the fast and easy implementation of data fusion analysis (FATCAT-awFC). The novel FATCAT-awFC pipeline was then utilized to identify connectivity (conventional functional, conventional structural and anatomically weighted functional connectivy) changes in MDD patients compared to healthy comparison participants (HC). Data were acquired from the Canadian Biomarker Integration Network for Depression (CAN-BIND-1) study. Large-scale resting-state networks were assessed. We found statistically significant anatomically-weighted functional connectivity (awFC) group differences in the default mode network and the ventral attention network, with a modest effect size (d < 0.4). Functional and structural connectivity seemed to overlap in significance between one region-pair within the default mode network. By combining structural and functional data, awFC served to heighten or reduce the magnitude of connectivity differences in various regions distinguishing MDD from HC. This method can help us more fully understand the interconnected nature of structural and functional connectivity as it relates to depression.

12.
Commun Biol ; 4(1): 903, 2021 07 22.
Artigo em Inglês | MEDLINE | ID: mdl-34294869

RESUMO

One of the biggest challenges in treating depression is the heterogeneous and qualitative nature of its clinical presentations. This highlights the need to find quantitative molecular markers to tailor existing treatment strategies to the individual's biological system. In this study, high-resolution metabolic phenotyping of urine and plasma samples from the CAN-BIND study collected before treatment with two common pharmacological strategies, escitalopram and aripiprazole, was performed. Here we show that a panel of LDL and HDL subfractions were negatively correlated with depression in males. For treatment response, lower baseline concentrations of apolipoprotein A1 and HDL were predictive of escitalopram response in males, while higher baseline concentrations of apolipoprotein A2, HDL and VLDL subfractions were predictive of aripiprazole response in females. These findings support the potential of metabolomics in precision medicine and the possibility of identifying personalized interventions for depression.

13.
J Psychiatr Res ; 140: 267-281, 2021 08.
Artigo em Inglês | MEDLINE | ID: mdl-34119912

RESUMO

The utility of cannabinoids and cannabinoid-based products (CBPs) as a pharmacological aid to treat psychiatric disorders in adulthood is still poorly understood despite a number of comprehensive general reviews discussing the topic. With a focus on randomized controlled trial (RCT) data, this review and meta-analysis aimed to aggregate and evaluate all current high-quality (Level-1) research that specifically assessed the effectiveness of a CBP on a diagnosed adult psychiatric disorder. The following databases, from their inception to September 2020, were included in the search: Academic Search Premier, PubMed, Ovid MEDLINE®, Web of Science™, PsycARTICLES, PsycINFO, CINAHL (Nursing and Allied Health), and Scopus. Risk of bias for each study was individually assessed using the revised Cochrane tool. Of the 2397 papers identified, thirty-one RCTs met criteria for inclusion: ten trials focused on treating cannabis use disorder, six on schizophrenia, five on opioid/tobacco use disorder, three on anxiety disorders, two on Tourette's disorder, two on anorexia nervosa, and one trial each for attention-deficit/hyperactivity disorder, posttraumatic stress disorder, and obsessive compulsive disorder. This review finds limited evidence for the effectiveness of CBPs to acutely treat a narrow range of psychiatric symptoms. We report no evidence supporting the mid- to long-range effectiveness of any currently available CBP. In general, quality of the evidence was assessed as low- to moderate. Importantly, none of the studies discussed in this review presently endorse the use of cannabis flower as a method of treatment for any recognized psychiatric disorder. Larger, hypothesis driven RCTs are required prior to making further therapeutic recommendations.


Assuntos
Transtorno do Deficit de Atenção com Hiperatividade , Canabinoides , Transtornos de Estresse Pós-Traumáticos , Síndrome de Tourette , Adulto , Transtornos de Ansiedade , Humanos , Ensaios Clínicos Controlados Aleatórios como Assunto
14.
PLoS One ; 16(6): e0253023, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34181661

RESUMO

OBJECTIVES: Antidepressants are first-line treatments for major depressive disorder (MDD), but 40-60% of patients will not respond, hence, predicting response would be a major clinical advance. Machine learning algorithms hold promise to predict treatment outcomes based on clinical symptoms and episode features. We sought to independently replicate recent machine learning methodology predicting antidepressant outcomes using the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) dataset, and then externally validate these methods to train models using data from the Canadian Biomarker Integration Network in Depression (CAN-BIND-1) dataset. METHODS: We replicated methodology from Nie et al (2018) using common algorithms based on linear regressions and decision trees to predict treatment-resistant depression (TRD, defined as failing to respond to 2 or more antidepressants) in the STAR*D dataset. We then trained and externally validated models using the clinical features found in both datasets to predict response (≥50% reduction on the Quick Inventory for Depressive Symptomatology, Self-Rated [QIDS-SR]) and remission (endpoint QIDS-SR score ≤5) in the CAN-BIND-1 dataset. We evaluated additional models to investigate how different outcomes and features may affect prediction performance. RESULTS: Our replicated models predicted TRD in the STAR*D dataset with slightly better balanced accuracy than Nie et al (70%-73% versus 64%-71%, respectively). Prediction performance on our external methodology validation on the CAN-BIND-1 dataset varied depending on outcome; performance was worse for response (best balanced accuracy 65%) compared to remission (77%). Using the smaller set of features found in both datasets generally improved prediction performance when evaluated on the STAR*D dataset. CONCLUSION: We successfully replicated prior work predicting antidepressant treatment outcomes using machine learning methods and clinical data. We found similar prediction performance using these methods on an external database, although prediction of remission was better than prediction of response. Future work is needed to improve prediction performance to be clinically useful.

15.
Personal Ment Health ; 2021 May 18.
Artigo em Inglês | MEDLINE | ID: mdl-34008342

RESUMO

Exposure to stressful life events and individual differences in the personality trait neuroticism are important risk factors that interact to predict major depressive disorder (MDD). Less is known about their effect on treatment response in depression. Here, we examine whether stressful life events experienced prior to and during treatment interact with neuroticism to predict response to 16-week pharmacotherapy for MDD. Participants included 159 outpatients with MDD who were initially treated with 8 weeks of escitalopram. Those who responded to the initial treatment continued on escitalopram monotherapy, whereas non-responders received 8 weeks of adjunctive aripiprazole. Personality was assessed using the NEO-Five Factor Inventory, and stressful life events were assessed using the Life Events and Difficulties Schedule, a rigorous contextual interview that includes independent ratings of threatening life events. High baseline neuroticism was associated with a lower likelihood of response when patients experienced one or more negative life events before treatment. Secondary analyses indicated that this effect was specific to neuroticism, and not better accounted for by its self-criticism or negative affect facets. Our results suggest that assessing personality and stressful life events at baseline can help clinicians assess which patients will respond to antidepressant therapy and which may need treatment augmentation.

16.
CNS Drugs ; 35(4): 439-450, 2021 04.
Artigo em Inglês | MEDLINE | ID: mdl-33860922

RESUMO

BACKGROUND: Non-response to first-line treatment for major depressive disorder (MDD) is common; for such individuals, quality of life (QoL) impairments can be severe. Identifying predictors of QoL changes may support the management of cases with persistent depressive symptoms despite adequate initial pharmacological/psychological treatment. OBJECTIVE: The present study aimed to explore predictors of domain-specific QoL improvement following adjunctive aripiprazole treatment for inadequate response to initial antidepressant therapy. METHODS: We evaluated secondary QoL outcomes from a CAN-BIND (Canadian Biomarker Integration Network in Depression) study in patients with MDD who did not respond to an initial 8 weeks of escitalopram and received a further 8 weeks of adjunctive aripiprazole (n = 96). Physical, psychological, social, and environmental QoL domains were assessed using the World Health Organization QoL Scale Brief Version (WHOQOL-BREF). Clinician-rated depressive symptoms were assessed using the Montgomery-Åsberg Depression Rating Scale (MADRS). Functioning was measured with the Sheehan Disability Scale (SDS). Satisfaction with medication was assessed with a single item from the Quality of Life Enjoyment and Satisfaction Questionnaire Short Form (Q-LES-Q-SF). Exploratory t-tests were used to describe domain score changes. A hierarchical linear regression was used to explore demographic, clinical, and treatment-related predictors of improvement. RESULTS: Across domains, QoL improved with adjunctive aripiprazole treatment. Satisfaction with medication and MADRS and SDS scores similarly improved. Symptom reduction was a predictor for positive change to physical and psychological QoL; functioning improvements were predictive of increases to all QoL domains. Satisfaction with medication predicted improvements to physical and psychological domains, whereas number of medication trials was a predictor of worsening QoL in the physical domain. CONCLUSION: The final model explained the most variance in psychological (68%) and physical (67%) QoL. Less variance was explained for environmental (43%) and social QoL (33%), highlighting a need for further exploration of predictors in these domains. Strategies such as functional remediation may have potential to support QoL for individuals with persistent depressive symptoms. CLINICAL TRIALS REGISTRY: ClinicalTrials.gov identifier: NCT016557.

17.
Psychiatry Res Neuroimaging ; 312: 111289, 2021 06 30.
Artigo em Inglês | MEDLINE | ID: mdl-33910139

RESUMO

Identifying biomarkers of serious mental illness, such as altered white matter microstructure, can aid in early diagnosis and treatment. White matter microstructure was assessed using constrained spherical deconvolution of diffusion imaging data in a sample of 219 youth (age 12-25 years, 64.84% female) across 8 sites. Participants were classified as healthy controls (HC; n = 47), familial risk for serious mental illness (n = 31), mild-symptoms (n = 37), attenuated syndromes (n = 66), or discrete disorder (n = 38) based on clinical assessments. Fractional anisotropy (FA) and mean diffusivity (MD) values were derived for the whole brain white matter, forceps minor, anterior cingulate, anterior thalamic radiations (ATR), inferior fronto-occipital fasciculus, superior longitudinal fasciculus (SLF), and uncinate fasciculus (UF). Linear mixed effects models showed a significant effect of age on MD of the left ATR, left SLF, and left UF, and a significant effect of group on FA for all tracts examined. For most tracts, the discrete disorder group had significantly lower FA than other groups, and the attenuated syndromes group had higher FA compared to HC, with few differences between the remaining groups. White matter differences in MDD are most evident in individuals following illness onset, as few significant differences were observed in the risk phase.


Assuntos
Transtornos Mentais , Substância Branca , Adolescente , Adulto , Anisotropia , Criança , Imagem de Difusão por Ressonância Magnética , Imagem de Tensor de Difusão , Feminino , Humanos , Masculino , Transtornos Mentais/diagnóstico por imagem , Substância Branca/diagnóstico por imagem , Adulto Jovem
18.
Pharmacopsychiatry ; 54(5): 225-231, 2021 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-33652477

RESUMO

INTRODUCTION: Many individuals with major depressive disorder (MDD) do not respond to initial antidepressant monotherapy. Adjunctive aripiprazole is recommended for treatment non-response; however, the impacts on quality of life (QoL) for individuals who receive this second-line treatment strategy have not been described. METHODS: We evaluated secondary QoL outcomes in patients with MDD (n=179). After 8 weeks of escitalopram, non-responders (<50% decrease in clinician-rated depression) were treated with adjunctive aripiprazole for 8 weeks (n=97); responders continued escitalopram (n=82). A repeated-measures ANOVA evaluated change in Quality of Life Enjoyment and Satisfaction Short Form scores. QoL was described relative to normative benchmarks. RESULTS: Escitalopram responders experienced the most QoL improvements in the first treatment phase. For non-responders, QoL improved with a large effect during adjunctive aripiprazole treatment. At the endpoint, 47% of patients achieving symptomatic remission still had impaired QoL. DISCUSSION: Individuals who were treated with adjunctive aripiprazole after non-response to escitalopram experienced improved QoL, but a substantial degree of QoL impairment persisted. Since QoL deficits may predict MDD recurrence, attention to ways to support this outcome is required.

19.
CNS Drugs ; 35(3): 291-304, 2021 03.
Artigo em Inglês | MEDLINE | ID: mdl-33683582

RESUMO

BACKGROUND: Cognitive deficits are detectable in major depressive disorder (MDD). The cognitive impact of antidepressants remains unclear, as does the cognitive effects of aripiprazole in MDD, a commonly used adjunct with putative pro-cognitive properties. OBJECTIVES: In this multi-centre, open-label study, cognitive changes associated with escitalopram monotherapy and adjunctive aripiprazole were examined. METHODS: Acutely depressed participants with MDD (n = 209) received 8 weeks of escitalopram. Non-responders received an additional 8 weeks of adjunctive aripiprazole (ESC-ARI, n = 88), while responders (ESC-CONT, n = 82) continued escitalopram monotherapy (n = 39 lost to attrition). ESC-ARI, ESC-CONT and matched healthy participants (n = 112) completed the Central Nervous System Vital Signs cognitive battery at baseline, 8 and 16 weeks. Linear mixed models compared participants with MDD cognitive trajectories with healthy participants. RESULTS: Participants with MDD displayed poorer baseline global cognition (assessed via the Neurocognitive Index), composite memory and psychomotor speed vs healthy participants. There were no statistically significant changes in participants with MDD receiving escitalopram monotherapy from baseline to week 8 in the neurocognitive index, reaction time, complex attention, cognitive flexibility, memory or psychomotor speed. Overall symptom severity changes were not associated with cognitive changes. The ESC-CONT group displayed no significant cognitive changes from weeks 8 to 16; reaction time worsened in the ESC-ARI group (p = 0.008) from weeks 8 to 16, independent of symptom change. CONCLUSIONS: Escitalopram monotherapy in acute MDD did not result in significant cognitive improvements. We provide novel evidence that escitalopram continuation in responders does not adversely affect cognition, but adjunctive aripiprazole in escitalopram non-responders worsens reaction time. Treatments targeting cognitive dysfunction are needed in MDD. CLINICALTRIALS. GOV IDENTIFIER: NCT01655706; 2 August, 2012.

20.
JAMA Netw Open ; 4(3): e210963, 2021 03 01.
Artigo em Inglês | MEDLINE | ID: mdl-33710288

RESUMO

Importance: Major depressive episodes in bipolar disorder are common and debilitating. Repetitive transcranial magnetic stimulation is well established in the treatment of major depressive disorder, and the intermittent theta burst stimulation (iTBS) protocol is replacing conventional protocols because of noninferiority and reduced delivery time. However, iTBS has not been adequately studied in bipolar disorder and, therefore, its efficacy is uncertain. Objective: To determine whether iTBS to the left dorsolateral prefrontal cortex (LDLPFC) is safe and efficacious in the treatment of acute bipolar depression. Design, Setting, and Participants: This study was a double-blind, 4-week, randomized clinical trial of iTBS targeting the LDLPFC. Two Canadian academic centers recruited patients between 2016 and 2020. Adults with bipolar disorder type I or type II experiencing an acute major depressive episode were eligible if they had not benefited from a first-line treatment for acute bipolar depression recommended by the Canadian Network for Mood and Anxiety Treatments and were currently treated with a mood stabilizer, an atypical antipsychotic, or their combination. Seventy-one participants were assessed for eligibility, and 37 were randomized to daily sham iTBS or active iTBS using a random number sequence, stratified according to current pharmacotherapy. Data analysis was performed from April to September 2020. Interventions: Four weeks of daily active iTBS (120% resting motor threshold) or sham iTBS to the LDLPFC. Nonresponders were eligible for 4 weeks of open-label iTBS. Main Outcomes and Measures: The primary outcome was the change in score on the Montgomery-Asberg Depression Rating Scale from baseline to study end. Secondary outcomes included clinical response, remission, and treatment-emergent mania or hypomania. Results: The trial was terminated for futility after 37 participants (23 women [62%]; mean [SD] age, 43.86 [13.87] years; age range, 20-68 years) were randomized, 19 to sham iTBS and 18 to active iTBS. There were no significant differences in Montgomery-Asberg Depression Rating Scale score changes (least squares mean difference between groups, -1.36 [95% CI, -8.92 to 6.19; P = .91] in favor of sham iTBS), and rates of clinical response were low in both the double-blind phase (3 of 19 participants [15.8%] in the sham iTBS group and 3 of 18 participants [16.7%] in the active iTBS group) and open-label phase (5 of 21 participants [23.8%]). One active iTBS participant had a treatment emergent hypomania, and a second episode occurred during open-label treatment. Conclusions and Relevance: iTBS targeting the LDLPFC is not efficacious in the treatment of acute bipolar depression in patients receiving antimanic or mood stabilizing agents. Additional research is required to understand how transcranial magnetic stimulation treatment protocols differ in efficacy between unipolar and bipolar depression. Trial Registration: ClinicalTrials.gov Identifier: NCT02749006.


Assuntos
Transtorno Bipolar/terapia , Estimulação Magnética Transcraniana/métodos , Adulto , Idoso , Método Duplo-Cego , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Córtex Pré-Frontal , Resultado do Tratamento , Adulto Jovem
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA
...