Integration of valence and conflict processing through cellular-field interactions in human subgenual cingulate during emotional face processing in treatment-resistant depression.

The subgenual anterior cingulate cortex (sgACC) has been identified as a key brain area involved in various cognitive and emotional processes. While the sgACC has been implicated in both emotional valuation and emotional conflict monitoring, it is still unclear how this area integrates multiple functions. We characterized both single neuron and local field oscillatory activity in 14 patients undergoing sgACC deep brain stimulation for treatment-resistant depression. During recording, patients were presented with a modified Stroop task containing emotional face images that varied in valence and congruence. We further analyzed spike-field interactions to understand how network dynamics influence single neuron activity in this area. Most single neurons responded to both valence and congruence, revealing that sgACC neuronal activity can encode multiple processes within the same task, indicative of multifunctionality. During peak neuronal response, we observed increased spectral power in low frequency oscillations, including theta-band synchronization (4-8 Hz), as well as desynchronization in beta-band frequencies (13-30 Hz). Theta activity was modulated by current trial congruency with greater increases in spectral power following non-congruent stimuli, while beta desynchronizations occurred regardless of emotional valence. Spike-field interactions revealed that local sgACC spiking was phase-locked most prominently to the beta band, whereas phase-locking to the theta band occurred in fewer neurons overall but was modulated more strongly for neurons that were responsive to task. Our findings provide the first direct evidence of spike-field interactions relating to emotional cognitive processing in the human sgACC. Furthermore, we directly related theta oscillatory dynamics in human sgACC to current trial congruency, demonstrating it as an important regulator during conflict detection. Our data endorse the sgACC as an integrative hub for cognitive emotional processing through modulation of beta and theta network activity.

Functional brain network features specify DBS outcome for patients with treatment resistant depression.

Deep brain stimulation (DBS) has shown therapeutic benefits for treatment resistant depression (TRD). Stimulation of the subcallosal cingulate gyrus (SCG) aims to alter dysregulation between subcortical and cortex. However, the 50% response rates for SCG-DBS indicates that selection of appropriate patients is challenging. Since stimulation influences large-scale network function, we hypothesized that network features can be used as biomarkers to inform outcome. In this pilot project, we used resting-state EEG recorded longitudinally from 10 TRD patients with SCG-DBS (11 at baseline). EEGs were recorded before DBS-surgery, 1-3 months, and 6 months post surgery. We used graph theoretical analysis to calculate clustering coefficient, global efficiency, eigenvector centrality, energy, and entropy of source-localized EEG networks to determine their topological/dynamical features. Patients were classified as responders based on achieving a 50% or greater reduction in Hamilton Depression (HAM-D) scores from baseline to 12 months post surgery. In the delta band, false discovery rate analysis revealed that global brain network features (segregation, integration, synchronization, and complexity) were significantly lower and centrality of subgenual anterior cingulate cortex (ACC) was higher in responders than in non-responders. Accordingly, longitudinal analysis showed SCG-DBS increased global network features and decreased centrality of subgenual ACC. Similarly, a clustering method separated two groups by network features and significant correlations were identified longitudinally between network changes and depression symptoms. Despite recent speculation that certain subtypes of TRD are more likely to respond to DBS, in the SCG it seems that underlying brain network features are associated with ability to respond to DBS. SCG-DBS increased segregation, integration, and synchronizability of brain networks, suggesting that information processing became faster and more efficient, in those patients in whom it was lower at baseline. Centrality results suggest these changes may occur via altered connectivity in specific brain regions especially ACC. We highlight potential mechanisms of therapeutic effect for SCG-DBS.

Accelerated sequential bilateral theta-burst stimulation in major depression: an open trial.

Theta burst stimulation (TBS) is approved and widely used in the treatment of treatment resistant-major depression. More recently, accelerated protocols delivering multiple treatments per day have been shown to be efficacious and potentially enhance outcomes compared to once daily protocols. Meanwhile, bilateral treatment protocols have also been increasingly tested to enhance outcomes. Here, we examined the efficacy and safety of accelerated bilateral TBS in major depressive disorder (MDD). In this open label pilot study, 25 patients with MDD (60%: women; mean age (SD): 45.24 (12.22)) resistant to at least one antidepressant, received bilateral TBS, consisting of 5 sequential bilateral intermittent TBS (iTBS) (600 pulses) and continuous TBS (cTBS) (600 pulses) treatments delivered to the left and right dorsolateral prefrontal cortex (DLPFC), respectively, daily for 5 days at 120% resting motor threshold. Outcome measures were post-treat treatment changes at day 5 and 2-weeks in Hamilton Depression Rating Scale (HDRS-17) scores and response (≥ 50% reduction from the baseline scores) and remission (≤ 7) rates. There was a significant reduction in HDRS scores at day 5 (p < 0.001) and 2-weeks post treatment (p < 0.001). The response rates increased from 20% at day 5 to 32% at 2-weeks post treatment suggesting delayed clinical effects. However, reduction in symptom scores between two post treatment endpoints was non-significant. 60% of patients could not tolerate the high intensity stimulation. No major adverse events occurred. Open label uncontrolled study with small sample size. These preliminary findings suggest that accelerated bilateral TBS may be clinically effective and safe for treatment resistant depression. Randomized sham-controlled trials are needed to establish the therapeutic role of accelerated bilateral TBS in depression.Trial registration: ClinicalTrials.gov, NCT10001858.

Competencies for Repetitive Transcranial Magnetic Stimulation in Postgraduate Medical Education: Expert Consensus Using a Modified Delphi Process.

BACKGROUND: Repetitive transcranial magnetic stimulation (rTMS) is recommended in Canadian guidelines as a first-line treatment for major depressive disorder. With the shift towards competency-based medical education, it remains unclear how to determine when a resident is considered competent in applying knowledge of rTMS to patient care. Given inconsistencies between postgraduate training programmes with regards to training requirements, defining competencies will improve the standard of care in rTMS delivery. OBJECTIVE: The goal of this study was to develop competencies for rTMS that can be implemented into a competency-based training curriculum in postgraduate training programmes. METHODS: A working group drafted competencies for postgraduate psychiatry trainees. Fourteen rTMS experts from across Canada were invited to participate in the modified Delphi process. RESULTS: Ten experts participated in all three rounds of the modified Delphi process. A total of 20 items reached a consensus. There was improvement in the Cronbach's alpha over the rounds of modified Delphi process (Cronbach's alpha increased from 0.554 to 0.824) suggesting improvement in internal consistency. The intraclass correlation coefficient (ICC) increased from 0.543 to 0.805 suggesting improved interrater agreement. CONCLUSIONS: This modified Delphi process resulted in expert consensus on competencies to be acquired during postgraduate medical education programmes where a learner is training to become competent as a consultant and/or practitioner in rTMS treatment. This is a field that still requires development, and it is expected that as more evidence emerges the competencies will be further refined. These results will help the development of other curricula in interventional psychiatry.

High-resolution virtual brain modeling personalizes deep brain stimulation for treatment-resistant depression: Spatiotemporal response characteristics following stimulation of neural fiber pathways.

Over the past 15 years, deep brain stimulation (DBS) has been actively investigated as a groundbreaking therapy for patients with treatment-resistant depression (TRD); nevertheless, outcomes have varied from patient to patient, with an average response rate of ∼50%. The engagement of specific fiber tracts at the stimulation site has been hypothesized to be an important factor in determining outcomes, however, the resulting individual network effects at the whole-brain scale remain largely unknown. Here we provide a computational framework that can explore each individual's brain response characteristics elicited by selective stimulation of fiber tracts. We use a novel personalized in-silico approach, the Virtual Big Brain, which makes use of high-resolution virtual brain models at a mm-scale and explicitly reconstructs more than 100,000 fiber tracts for each individual. Each fiber tract is active and can be selectively stimulated. Simulation results demonstrate distinct stimulus-induced event-related potentials as a function of stimulation location, parametrized by the contact positions of the electrodes implanted in each patient, even though validation against empirical patient data reveals some limitations (i.e., the need for individual parameter adjustment, and differential accuracy across stimulation locations). This study provides evidence for the capacity of personalized high-resolution virtual brain models to investigate individual network effects in DBS for patients with TRD and opens up novel avenues in the personalized optimization of brain stimulation.

Personality changes with subcallosal cingulate deep brain stimulation in patients with treatment-resistant depression.

BACKGROUND: Deep brain stimulation (DBS) is a promising investigational approach for treatment-resistant depression. However, reports suggesting changes in personality with DBS for movement disorders have raised clinical and ethical concerns. We prospectively examined changes in personality dimensions and antidepressant response to subcallosal cingulate (SCC)-DBS for treatment-resistant depression. METHODS: Twenty-two patients with treatment-resistant depression underwent SCC-DBS. We used the NEO Five-Factor Inventory for personality assessment at baseline and every 3 months until 15 months post-DBS. We assessed depression severity monthly using the Hamilton Depression Rating Scale. RESULTS: We found a significant decrease in neuroticism (p = 0.002) and an increase in extraversion (p = 0.001) over time, showing a change toward normative data. Improvement on the Hamilton Depression Rating Scale was correlated with decreases in neuroticism at 6 months (p = 0.001) and 12 months (p < 0.001), and with an increase in extraversion at 12 months (p = 0.01). Changes on the Hamilton Depression Rating Scale over time had a significant covariate effect on neuroticism (p < 0.001) and extraversion (p = 0.001). Baseline openness and agreeableness predicted response to DBS at 6 (p = 0.006) and 12 months (p = 0.004), respectively. LIMITATIONS: Limitations included a small sample size, a lack of sham control and the use of subjective personality evaluation. CONCLUSION: We observed positive personality changes following SCC-DBS, with reduced neuroticism and increased extraversion related to clinical improvement in depression, suggesting a state effect. As well, pretreatment levels of openness and agreeableness may have predicted subsequent response to DBS. The NEO Five-Factor Inventory assessment may have a role in clinical decision-making and prognostic evaluation in patients with treatment-resistant depression who undergo SCC-DBS.

Treatment-resistant major depressive disorder: Canadian expert consensus on definition and assessment.

BACKGROUND: Treatment-resistant depression (TRD) is a debilitating chronic mental illness that confers increased morbidity and mortality, decreases the quality of life, impairs occupational, social, and offspring development, and translates into increased costs on the healthcare system. The goal of this study is to reach an agreement on the concept, definition, staging model, and assessment of TRD. METHODS: This study involved a review of the literature and a modified Delphi process for consensus agreement. The Appraisal of Guidelines for Research & Evaluation II guidelines were followed for the literature appraisal. Literature was assessed for quality and strength of evidence using the grading, assessment, development, and evaluations system. Canadian national experts in depression were invited for the modified Delphi process based on their prior clinical and research expertize. Survey items were considered to have reached a consensus if 80% or more of the experts supported the statement. RESULTS: Fourteen Canadian experts were recruited for three rounds of surveys to reach a consensus on a total of 27 items. Experts agreed that a dimensional definition for treatment resistance was a useful concept to describe the heterogeneity of this illness. The use of staging models and clinical scales was recommended in evaluating depression. Risk factors and comorbidities were identified as potential predictors for treatment resistance. CONCLUSIONS: TRD is a meaningful concept both for clinical practice and research. An operational definition for TRD will allow for opportunities to improve the validity of predictors and therapeutic options for these patients.

Quality of Life Impacts of Bright Light Treatment, Fluoxetine, and the Combination in Patients with Nonseasonal Major Depressive Disorder: A Randomized Clinical Trial.

OBJECTIVE: Bright light therapy is increasingly recommended (alone or in combination with antidepressant medication) to treat symptoms of nonseasonal major depressive disorder (MDD). However, little is known about its impacts on quality of life (QoL), a holistic, patient-valued outcome. METHODS: This study utilizes secondary outcome data from an 8-week randomized, controlled, double blind trial comparing light monotherapy (n = 32), fluoxetine monotherapy (n = 30), and the combination of these (n = 27) to placebo (n = 30). QoL was assessed using the Quality of Life Enjoyment and Satisfaction Questionnaire Short Form (Q-LES-Q-SF). Treatment-related differences in QoL improvements were assessed using a repeated measures analysis of variance. The influence of potential predictors of QoL (demographic variables and change in depressive symptoms) were investigated via hierarchical linear regression. RESULTS: Q-LES-Q-SF scores significantly improved across all treatment conditions; however, no significant differences were observed between treatment arms. QoL remained poor relative to community norms by the end of the trial period: Across conditions, 70.6% of participants had significantly impaired QoL at the 8-week assessment. Reduction in depressive scores was a significant predictor of improved QoL, with the final model accounting for 54% of variance in QoL change scores. CONCLUSION: The findings of this study emphasize that improvement in QoL and reduction in depressive symptoms in MDD, while related, cannot be taken to be synonymous. Adjunctive therapies may be required to address unmet QoL needs in patients with MDD receiving antidepressant or light therapies. Further research is required to explore additional predictors of QoL in order to better refine treatments for MDD.

Automatic classification of major depression disorder using arterial spin labeling MRI perfusion measurements.

AIM: Neuroimaging-based multivariate pattern-recognition methods have been successfully used to develop diagnostic algorithms to distinguish patients with major depressive disorder (MDD) from healthy controls (HC). We developed and evaluated the accuracy of a multivariate classification method for the differentiation of MDD and HC using cerebral blood flow (CBF) features measured by non-invasive arterial spin labeling (ASL) MRI. METHODS: Twenty-two medication-free patients with the diagnosis of MDD based on DSM-IV criteria and 22 HC underwent pseudo-continuous 3-D-ASL imaging to assess CBF. Using an atlas-based approach, regional CBF was determined in various brain regions and used together with sex and age as classification features. A linear kernel support vector machine was used for feature ranking and selection as well as for the classification of patients with MDD and HC. Permutation testing was used to test for significance of the classification results. RESULTS: The automatic classifier based on CBF features showed a statistically significant accuracy of 77.3% (P = 0.004) with a specificity of 80% and sensitivity of 75% for classification of MDD versus HC. The features that contributed to the classification were sex and regional CBF of the cortical, limbic, and paralimbic regions. CONCLUSION: Machine-learning models based on CBF measurements are capable of differentiating MDD from HC with high accuracy. The use of larger study cohorts and inclusion of other imaging measures may improve the performance of the classifier to achieve the accuracy required for clinical application.

The 5-HTTLPR and BDNF polymorphisms moderate the association between uncinate fasciculus connectivity and antidepressants treatment response in major depression.

Symptom improvement in depression due to antidepressant treatment is highly variable and clinically unpredictable. Linking neuronal connectivity and genetic risk factors in predicting antidepressant response has clinical implications. Our investigation assessed whether indices of white matter integrity, serotonin transporter-linked polymorphism (5-HTTLPR) and brain-derived neurotrophic factor (BDNF) val66met polymorphism predicted magnitude of depression symptom change following antidepressant treatment. Fractional anisotropy (FA) was used as an indicator of white matter integrity and was assessed in the uncinate fasciculus and superior longitudinal fasciculus using tract-based spatial statistics (TBSS) and probabilistic tractography. Forty-six medication-free patients with major depressive disorder participated in a diffusion tensor imaging scan prior to completing an 8-week treatment regime with citalopram or quetiapine XR. Indexed improvements in Hamilton Depression Rating Scale score from baseline to 8-week endpoint were used as an indicator of depression improvement. Carriers of the BDNF met allele exhibited lower FA values in the left uncinate fasciculus relative to val/val individuals [F(1, 40) = 7.314, p = 0.009]. Probabilistic tractography identified that higher FA in the left uncinate fasciculus predicted percent change in depression severity, with BDNF moderating this association [F(3, 30) = 3.923, p = 0.018]. An interaction between FA in the right uncinate fasciculus and 5-HTTLPR also predicted percent change in depression severity [F(5, 25) = 5.315, p = 0.002]. Uncorrected TBSS results revealed significantly higher FA in hippocampal portions of the cingulum bundle in responders compared to non-responders (p = 0.016). The predictive value of prefrontal and amygdala/hippocampal WM connectivity on antidepressant treatment response may be influenced by 5-HTTLPR and BDNF polymorphisms in MDD.

The influence of 5-HTTLPR and Val66Met polymorphisms on cortical thickness and volume in limbic and paralimbic regions in depression: a preliminary study.

BACKGROUND: Structural brain abnormalities have been investigated in multi-genetic and complex disorders such as major depressive disorder (MDD). Among the various candidate genes implicated in MDD, the brain-derived neurotrophic factor (BDNF) Val66Met polymorphism and 5-HT transporter gene linked polymorphism (5-HTTLPR) have garnered the most attention due to their putative roles in neural plasticity and antidepressant response. However, relatively few studies have assessed the influence of these polymorphysims on cortical thickness or brain volume in para-limbic and limbic regions in MDD, which was the aim of this study. METHODS: Forty-three adults with MDD and 15 healthy controls (HC) underwent structural magnetic resonance imaging (MRI). Cortical thickness was assessed in frontal, cingulate and temporal regions. Volumetric measures were carried out in the thalamus, caudate, putamen, pallidum, hippocampus and amygdala. Participants were genotyped to determine their 5-HTTLPR (tri-allelic) and Val66Met polymorphisms. RESULTS: In the combined sample (MDD + HC), smaller right pallidum volumes were found in LA/S (LA/S & LA/LG) heterozygotes compared to S/S (S/S, LG/S & LG/LG) homozygotes, though the effect was modest. In the MDD group, larger left thalamus and putamen volumes were observed in LA/LA homozygotes. No Val66Met or 5-HTTLPR genotype effects existed on cortical thickness and no main effects of the Val66Met polymorphism were observed. CONCLUSION: Our preliminary results suggest that the 5-HTTLPR polymorphism is associated with morphometric changes in regions known to play an important role in emotional and reward processing in depression. A larger sample size is required to replicate these findings and to potentially reveal subtle morphometric changes.

Amygdala responses to quetiapine XR and citalopram treatment in major depression: the role of 5-HTTLPR-S/Lg polymorphisms.

OBJECTIVES: Genotype and drug pharmacology may contribute to variations in brain response to antidepressants. We examined the impact of two antidepressants with differential actions on serotonin transporter and the 5-HHTLPR-S/Lg polymorphisms on amygdala responses in major depressive disorder (MDD). METHODS: Caucasians with MDD were given either citalopram or quetiapine extended release for 8 weeks. Patients were genotyped for 5-HTTLPR. Clinical efficacy was assessed using the Hamilton Depression Rating Scale. fMRI responses to negative emotional faces were acquired at baseline, week 1 and week 8. The outcome measure was change in amygdala responses at week 8. RESULTS: Citalopram had no effect on amygdala responses in MDD patients with S/Lg alleles at weeks 1 and 8 compared with baseline, whereas it induced changes in amygdala responses in LL homozygotes. By contrast, quetiapine decreased amygdala responses at both time points in S/Lg carriers, and changes in amygdala responses at week 8 correlated with a reduction in depression scores. The small number of LL homozygotes in quetiapine group was a limitation. Efficacy of both treatments was comparable. CONCLUSIONS: These preliminary data suggest that pharmacological mechanisms and genetics need to be considered in the development of neuroimaging markers for the evaluation of antidepressant treatments.

Influence of age of onset on limbic and paralimbic structures in depression.

AIM: Major depressive disorder (MDD) onset during childhood/adolescence is associated with a greater illness burden and distinct clinical profile. However, limited research exists on the effect of age of MDD onset on volumetric abnormalities in para/limbic structures during adulthood. METHODS: Subgenual anterior cingulate cortex (sgACC), hippocampus and caudate nucleus volumes were measured by manual tracing in depressed individuals (n = 45) and healthy controls (HC; n = 19). Volumetric comparisons were carried out between HC and MDD patients divided into those with pediatric (≤ 18 years; n = 17) and adult onset (≥ 19 years; n = 28). RESULTS: The adult MDD-onset group had smaller sgACC volumes than the pediatric-onset and HC groups (age, sex controlled). No differences in caudate and hippocampus volumes existed. sgACC and hippocampal volumes were inversely correlated with depression severity. CONCLUSIONS: Surprisingly, pediatric MDD-onset was not associated with more pronounced sgACC, hippocampus and caudate volume reductions. Nevertheless, age of illness onset appears to be a meaningful dimension of study in efforts to understand the neurobiological heterogeneity of MDD.

Multimodal imaging measures in the prediction of clinical response to deep brain stimulation for refractory depression: A machine learning approach.

OBJECTIVES: This study compared machine learning models using unimodal imaging measures and combined multi-modal imaging measures for deep brain stimulation (DBS) outcome prediction in treatment resistant depression (TRD). METHODS: Regional brain glucose metabolism (CMRGlu), cerebral blood flow (CBF), and grey matter volume (GMV) were measured at baseline using 18F-fluorodeoxy glucose (18F-FDG) positron emission tomography (PET), arterial spin labelling (ASL) magnetic resonance imaging (MRI), and T1-weighted MRI, respectively, in 19 patients with TRD receiving subcallosal cingulate (SCC)-DBS. Responders (n = 9) were defined by a 50% reduction in HAMD-17 at 6 months from the baseline. Using an atlas-based approach, values of each measure were determined for pre-selected brain regions. OneR feature selection algorithm and the naïve Bayes model was used for classification. Leave-out-one cross validation was used for classifier evaluation. RESULTS: The performance accuracy of the CMRGlu classification model (84%) was greater than CBF (74%) or GMV (74%) models. The classification model using the three image modalities together led to a similar accuracy (84%0 compared to the CMRGlu classification model. CONCLUSIONS: CMRGlu imaging measures may be useful for the development of multivariate prediction models for SCC-DBS studies for TRD. The future of multivariate methods for multimodal imaging may rest on the selection of complementing features and the developing better models.Clinical Trial Registration: ClinicalTrials.gov (#NCT01983904).

Effects of combined pharmacotherapy and psychotherapy for improving work functioning in major depressive disorder.

BACKGROUND: Major depressive disorder is associated with significant impairment in occupational functioning and reduced productivity, which represents a large part of the overall burden of depression. AIMS: To examine symptom-based and work functioning outcomes with combined pharmacotherapy and psychotherapy treatment of major depressive disorder. METHOD: Employed patients with a DSM-IV diagnosis of major depressive disorder were treated with escitalopram 10-20 mg/day and randomised to: (a) telephone-administered cognitive-behavioural therapy (telephone CBT) (n = 48); or (b) adherence-reminder telephone calls (n = 51). Outcomes included the Montgomery-Åsberg Depression Rating Scale (MADRS), administered by masked evaluators via telephone, and self-rated work functioning scales completed online. (Registered at clinicaltrials.gov: NCT00702598.) RESULTS: After 12 weeks, there were no significant between-group differences in change in MADRS score or in response/remission rates. However, participants in the telephone-CBT group had significantly greater improvement on some measures of work functioning than the escitalopram-alone group. CONCLUSIONS: Combined treatment with escitalopram and telephone-administered CBT significantly improved some self-reported work functioning outcomes, but not symptom-based outcomes, compared with escitalopram alone.

Double-blind optimization of subcallosal cingulate deep brain stimulation for treatment-resistant depression: a pilot study.

BACKGROUND: Deep brain stimulation (DBS) of the subcallosal cingulate (SCC) is reported to be a safe and effective new treatment for treatment-resistant depression (TRD). However, the optimal electrical stimulation parameters are unknown and generally selected by trial and error. This pilot study investigated the relationship between stimulus parameters and clinical effects in SCC-DBS treatment for TRD. METHODS: Four patients with TRD underwent SCC-DBS surgery. In a double-blind stimulus optimization phase, frequency and pulse widths were randomly altered weekly, and corresponding changes in mood and depression were evaluated using a visual analogue scale (VAS) and the 17-item Hamilton Rating Scale for Depression (HAM-D-17). In the open-label postoptimization phase, depressive symptoms were evaluated biweekly for 6 months to determine long-term clinical outcomes. RESULTS: Longer pulse widths (270-450 µs) were associated with reductions in HAM-D-17 scores in 3 patients and maximal happy mood VAS responses in all 4 patients. Only 1 patient showed acute clinical or mood effects from changing the stimulation frequency. After 6 months of open-label therapy, 2 patients responded and 1 patient partially responded. LIMITATIONS: Limitations include small sample size, weekly changes in stimulus parameters, and fixed-order and carry-forward effects. CONCLUSION: Longer pulse width stimulation may have a role in stimulus optimization for SCC-DBS in TRD. Longer pulse durations produce larger apparent current spread, suggesting that we do not yet know the optimal target or stimulus parameters for this therapy. Investigations using different stimulus parameters are required before embarking on large-scale randomized sham-controlled trials.

Personal recovery associated with deep brain stimulation for treatment-resistant depression: A constructivist grounded theory study.

WHAT IS KNOWN ON THE SUBJECT?: Major depressive disorder is the most prevalent of all mental illnesses. 10%-20% of patients with depression and 1% of the population overall have treatment-resistant depression (TRD). DBS is an emerging investigational treatment for TRD with documented clinical efficacy and safety. The framework of the recovery model includes both clinical and personal recovery. Personal recovery is a self-process in which hope, empowerment and optimism are embraced to overcome the impact of mental illness on one's sense of self. Although clinical and functional outcomes of DBS for TRD have been well documented in the previous studies, personal recovery as an outcome has been explored only in a handful of studies. WHAT THIS PAPER ADDS TO EXISTING KNOWLEDGE?: This is the first qualitative study exploring personal recovery from DBS treatment specific to the target of subcallosal cingulate cortex in patients with TRD. Since the existing literature on personal recovery in DBS studies is limited, the contribution of this paper is crucial to this field. For individuals who responded to deep brain stimulation clinically, neither participants nor family believed it cured their depression, but rather there was a significant decrease in the severity of symptoms of depression. A holistic-oriented framework (that includes personal recovery) is significant for those individuals with TRD undergoing DBS. Personal and clinical recovery are two different constructs, and individuals may experience one or the other or both. The experience of participants who responded to deep brain stimulation recognized that the recovery from depression is a process of reconstructing self. This process involved a period of adjustment that evoked a deeper self-awareness, re-engagement with daily living and newfound gratitude in living. Individuals transitioned from an emotionally driven life to one where future goals were considered. Supportive relationships were instrumental in this process. WHAT ARE THE IMPLICATIONS FOR PRACTICE?: A deep brain stimulation intervention for treatment-resistant depression offered individuals an opportunity for personal recovery where a reconstruction of self occurred. Personal recovery can be considered as an outcome in conjunction with clinical and functional outcomes in future DBS trials for TRD. The relevance of personal recovery in the prevention of relapses needs further investigation. To advocate for care and services that facilitate the process of recovery from depression, it is important to understand the personal dimensions and experience of recovery that may influence the process. To develop recovery-oriented interventions to help patients and families in recovery post-deep brain stimulation, further understanding of support and negotiating relationships during this life-altering experience is needed. ABSTRACT: Introduction Multiple trials of antidepressant treatments in patients with depression pose a major challenge to the mental health system. Deep brain stimulation (DBS) is an emerging and promising investigational treatment to reduce depressive symptoms in individuals with treatment-resistant depression (TRD). The clinical and functional outcomes of DBS for TRD have been well documented in previous studies; however, studies of personal recovery as an outcome of DBS specific to the target of subcallosal cingulate cortex in patients with TRD are limited. Aim To explore the processes of personal recovery in patients with treatment-resistant depression following subcallosal cingulate-deep brain stimulation. Method Participants were 18 patients with TRD who participated in the subcallosal cingulate (SCC)-DBS trial and 11 family members. They also participated in add-on individual cognitive behavioural therapy during the trial. A qualitative constructivist grounded theory approach was used to conceptualize the personal recovery process of patients and families. Results While every participant and their families' journey were unique following the deep brain stimulation intervention, a theoretical model of Balancing to Establish a Reconstructed Self emerged from the data. The themes underlying the model were (1) Balancing to Establish a Reconstructed Self: A Whole-Body Experience, (2) The Liminal Space in-between: Balancing with Cautious Optimism, (3) Hope: Transitioning from Emotion-Focussed Living to Goal-Oriented Planning and (4) Support: Negotiating Relationships. Discussion This is the first study examining recovery from patients' perspectives as an outcome of SCC-DBS intervention for TRD. The study shows that personal recovery is a gradual and continual process of reconstruction of the self, developing through supportive relationships. Clinical and personal recovery are two distinct constructs, and individuals may experience one or the other or both. Most patients who do respond clinically experience improvement in terms of having optimism and hope. Some patients, however, respond with significant symptom reduction but are not able to achieve personal recovery to experience joy or hope for improved quality of living. Implications for Practice Strategies for personal recovery for both patients and family need to be considered during and post deep brain stimulation intervention. Nurses working with these patients and families may benefit from education, training and support to assess and engage in conversations about their recovery process.

The CANMAT task force recommendations for the management of patients with mood disorders and comorbid medical conditions: diagnostic, assessment, and treatment principles.

BACKGROUND: Medical comorbidity is commonly encountered in individuals with major depressive disorder (MDD) and bipolar disorder (BD). The presence of medical comorbidity has diagnostic, prognostic, treatment, and etiologic implications underscoring the importance of timely detection and treatment. METHODS: A selective review of relevant articles and reviews published in English-language databases (1968 to April 2011) was conducted. Studies describing epidemiology, temporality of onset, treatment implications, and prognosis were selected for review. RESULTS: A growing body of evidence from epidemiologic, clinical, and biologic studies suggests that the relationship between medical illness and mood disorder is bidirectional in nature. It provides support for the multiplay of shared and specific etiologic factors interlinking these conditions. CONCLUSIONS: This article describes the complex interactions between medical illness and mood disorders and provides a meaningful approach to their comorbid clinical diagnosis and management.

The Canadian Network for Mood and Anxiety Treatments (CANMAT) task force recommendations for the management of patients with mood disorders and select comorbid medical conditions.

BACKGROUND: Medical comorbidity in patients with mood disorders has become an increasingly important clinical and global public health issue. Several specific medical conditions are associated with an increased risk of mood disorders, and conversely, mood disorders are associated with increased morbidity and mortality in patients with specific medical disorders. METHODS: To help understand the bidirectional relationship and to provide an evidence-based framework to guide the treatment of mood disorders that are comorbid with medical illness, we have reviewed relevant articles and reviews published in English-language databases (to April 2011) on the links between mood disorders and several common medical conditions, evaluating the efficacy and safety of pharmacologic and psychosocial treatments. The medical disorders most commonly encountered in adult populations (ie, cardiovascular disease, cerebrovascular disease, cancer, human immunodeficiency virus, hepatitis C virus, migraine, multiple sclerosis, epilepsy, and osteoporosis) were chosen as the focus of this review. RESULTS: Emerging evidence suggests that depression comorbid with several medical disorders is treatable and failure to treat depression in medically ill patients may have a negative effect on medical outcomes. CONCLUSIONS: This review summarizes the available evidence and provides treatment recommendations for the management of comorbid depression in medically ill patients.

Managing medical and psychiatric comorbidity in individuals with major depressive disorder and bipolar disorder.

BACKGROUND: Most individuals with mood disorders experience psychiatric and/or medical comorbidity. Available treatment guidelines for major depressive disorder (MDD) and bipolar disorder (BD) have focused on treating mood disorders in the absence of comorbidity. Treating comorbid conditions in patients with mood disorders requires sufficient decision support to inform appropriate treatment. METHODS: The Canadian Network for Mood and Anxiety Treatments (CANMAT) task force sought to prepare evidence- and consensus-based recommendations on treating comorbid conditions in patients with MDD and BD by conducting a systematic and qualitative review of extant data. The relative paucity of studies in this area often required a consensus-based approach to selecting and sequencing treatments. RESULTS: Several principles emerge when managing comorbidity. They include, but are not limited to: establishing the diagnosis, risk assessment, establishing the appropriate setting for treatment, chronic disease management, concurrent or sequential treatment, and measurement-based care. CONCLUSIONS: Efficacy, effectiveness, and comparative effectiveness research should emphasize treatment and management of conditions comorbid with mood disorders. Clinicians are encouraged to screen and systematically monitor for comorbid conditions in all individuals with mood disorders. The common comorbidity in mood disorders raises fundamental questions about overlapping and discrete pathoetiology.