Nonpsychotic Major Depression Research Articles

Resting-state EEG dynamic functional connectivity distinguishes non-psychotic major depression, psychotic major depression and schizophrenia.

This study aims to identify dynamic patterns within the spatiotemporal feature space that are specific to nonpsychotic major depression (NPMD), psychotic major depression (PMD), and schizophrenia (SCZ). The study also evaluates the effectiveness of machine learning algorithms based on these network manifestations in differentiating individuals with NPMD, PMD, and SCZ. A total of 579 participants were recruited, including 152 patients with NPMD, 45 patients with PMD, 185 patients with SCZ, and 197 healthy controls (HCs). A dynamic functional connectivity (DFC) approach was employed to estimate the principal FC states within each diagnostic group. Incremental proportions of data (ranging from 10% to 100%) within each diagnostic group were used for variability testing. DFC metrics, such as proportion, mean duration, and transition number, were examined among the four diagnostic groups to identify disease-related neural activity patterns. These patterns were then used to train a two-layer classifier for the four groups (HC, NPMD, PMD, and SCZ). The four principal brain states (i.e., states 1,2,3, and 4) identified by the DFC approach were highly representative within and across diagnostic groups. Between-group comparisons revealed significant differences in network metrics of state 2 and state 3, within delta, theta, and gamma frequency bands, between healthy individuals and patients in each diagnostic group (p < 0.01, FDR corrected). Moreover, the identified key dynamic network metrics achieved an accuracy of 73.1 ± 2.8% in the four-way classification of HC, NPMD, PMD, and SCZ, outperforming the static functional connectivity (SFC) approach (p < 0.001). These findings suggest that the proposed DFC approach can identify dynamic network biomarkers at the single-subject level. These biomarkers have the potential to accurately differentiate individual subjects among various diagnostic groups of psychiatric disorders or healthy controls. This work may contribute to the development of a valuable EEG-based diagnostic tool with enhanced accuracy and assistive capabilities.

Ketamine versus ECT for Nonpsychotic Treatment-Resistant Major Depression

BackgroundElectroconvulsive therapy (ECT) and subanesthetic intravenous ketamine are both currently used for treatment-resistant major depression, but the comparative effectiveness of the two treatments remains uncertain.MethodsWe conducted an open-label, randomized, noninferiority trial involving patients referred to ECT clinics for treatment-resistant major depression. Patients with treatment-resistant major depression without psychosis were recruited and assigned in a 1:1 ratio to receive ketamine or ECT. During an initial 3-week treatment phase, patients received either ECT three times per week or ketamine (0.5 mg per kilogram of body weight over 40 minutes) twice per week. The primary outcome was a response to treatment (i.e., a decrease of ≥50% from baseline in the score on the 16-item Quick Inventory of Depressive Symptomatology–Self-Report; scores range from 0 to 27, with higher scores indicating greater depression). The noninferiority margin was −10 percentage points. Secondary outcomes included scores on memory tests and patient-reported quality of life. After the initial treatment phase, the patients who had a response were followed over a 6-month period.ResultsA total of 403 patients underwent randomization at five clinical sites; 200 patients were assigned to the ketamine group and 203 to the ECT group. After 38 patients had withdrawn before initiation of the assigned treatment, ketamine was administered to 195 patients and ECT to 170 patients. A total of 55.4% of the patients in the ketamine group and 41.2% of those in the ECT group had a response (difference, 14.2 percentage points; 95% confidence interval, 3.9 to 24.2; P<0.001 for the noninferiority of ketamine to ECT). ECT appeared to be associated with a decrease in memory recall after 3 weeks of treatment (mean [±SE] decrease in the T-score for delayed recall on the Hopkins Verbal Learning Test–Revised, −0.9±1.1 in the ketamine group vs. −9.7±1.2 in the ECT group; scores range from −300 to 200, with higher scores indicating better function) with gradual recovery during follow-up. Improvement in patient-reported quality-of-life was similar in the two trial groups. ECT was associated with musculoskeletal adverse effects, whereas ketamine was associated with dissociation.ConclusionsKetamine was noninferior to ECT as therapy for treatment-resistant major depression without psychosis. (Funded by the Patient-Centered Outcomes Research Institute; ELEKT-D ClinicalTrials.gov number, NCT03113968.)

Prevalence and risk factors of psychotic symptoms in middle-aged patients with first-episode drug-naïve major depressive disorder: A large-scale cross-sectional study

BackgroundPsychotic symptoms are common in patients with major depressive disorder (MDD). However, few studies have assessed the incidence of comorbid psychotic symptoms in first-episode drug naïve (FEDN) MDD patients. The present study aimed to evaluate the prevalence and risk factors of psychotic symptoms in a large sample of middle-aged Chinese patients with FEDN MDD. Methods813 middle-aged (age range 35 to 65 years) outpatients with FEDN MDD were recruited. The 17-item Hamilton Rating Scale for Depression (HAMD), the 14-item Hamilton Anxiety Rating Scale (HAMA), and the positive subscales of the Positive and Negative Syndrome Scale (PANSS) were used to assess patient anxiety, depression and psychotic symptoms, respectively. ResultsThe prevalence of psychotic symptoms in middle-aged patients with FEND MDD was 10.95 %. Multivariate logistic regression analysis showed that HAMA score, HAMD score, TSH, TC and BMI levels were significant predictors of psychotic symptoms in MDD middle-aged patients. The HAMA score and HAMD score predicted psychotic symptoms for both male and female middle-aged patients with MDD, while higher TSH, TC and BMI levels were correlated with psychotic symptoms only in female MDD patients. Furthermore, combining the HAMA score, HAMD score, and TSH could differentiate between psychotic major depression (PMD) and nonpsychotic major depression (NPMD) in middle-aged patients. ConclusionsPsychotic symptoms among middle-aged patients with MDD can be identified by integrating clinical and biological variables as early as possible during the first time see a doctor.

Intravenous Ketamine-induced Affective Switch in a Patient of Major Depressive Disorder with Suicidal Ideation: A Case Report

In treatment-resistant unipolar and bipolar depression, there is increasing evidence to support the fast, although the short-lived antidepressant effect of ketamine, a non-competitive glutamate N-methyl-D-aspartate receptor antagonist. Ketamine has been shown to cause transient mood elevation or euphoria, dissociative symptoms and psychotomimetic effects when administered in unipolar or bipolar depression. Still, it has not been shown to cause an affective switch resulting in persistent hypomania/mania or a manic-like state. We report the case of a 47-year-old man who developed a switch to mania while receiving a sub-anaesthetic dosage of ketamine intravenously for his third episode of recurrent, non-psychotic severe major depression with suicidal ideation. This case indicates that a polarity switch should be acknowledged as a possible side effect when using ketamine for depression.

A Machine-Learning-Algorithm-Based Prediction Model for Psychotic Symptoms in Patients with Depressive Disorder.

Psychotic symptoms are rarely concurrent with the clinical manifestations of depression. Additionally, whether psychotic major depression is a subtype of major depression or a clinical syndrome distinct from non-psychotic major depression remains controversial. Using data from the Research on Asian Psychotropic Prescription Patterns for Antidepressants, we developed a machine-learning-algorithm-based prediction model for concurrent psychotic symptoms in patients with depressive disorders. The advantages of machine learning algorithms include the easy identification of trends and patterns, handling of multi-dimensional and multi-faceted data, and wide application. Among 1171 patients with depressive disorders, those with psychotic symptoms were characterized by significantly higher rates of depressed mood, loss of interest and enjoyment, reduced energy and diminished activity, reduced self-esteem and self-confidence, ideas of guilt and unworthiness, psychomotor agitation or retardation, disturbed sleep, diminished appetite, and greater proportions of moderate and severe degrees of depression compared to patients without psychotic symptoms. The area under the curve was 0.823. The overall accuracy was 0.931 (95% confidence interval: 0.897–0.956). Severe depression (degree of depression) was the most important variable in the prediction model, followed by diminished appetite, subthreshold (degree of depression), ideas or acts of self-harm or suicide, outpatient status, age, psychomotor retardation or agitation, and others. In conclusion, the machine-learning-based model predicted concurrent psychotic symptoms in patients with major depression in connection with the “severity psychosis” hypothesis.

P317. Differentiating Major Depression With and Without Psychotic Symptoms Based on Resting-State EEG

Major depression with and without psychotic symptoms show some differences in clinical characteristics and treatment. So far, a few studies have conducted the diagnostic classification of major depression based on EEG, but few have focused on the classification between the psychotic (PMD) and non-psychotic major depression (NMD).

Life-Satisfaction, Engagement and Social Support: Do they Predict Depression Severity, Suicide Ideation, and History of Attempt in Late-life Depression?

<h3>Introduction</h3> Older adults are at the highest risk for death by suicide in almost all countries in the world. Certain protective factors, such as objective and subjective social support, have long been stated as protective factors for suicidal behavior in the elderly. Trait-level mindfulness, and life satisfaction and engagement have also been stated to be protective factors against suicide, however, their relationship with risk for suicide in late life has yet to be examined. We examined the effects of a combination of these protective factors in late life in a high suicide risk sample of depressed older adults. Specifically, we examined the effects of these protective factors on depression severity, presence and severity of suicidal ideation, and history of suicidal behavior. <h3>Methods</h3> Participants included 297 adults aged 55+ (mean age: 64.2, range: 55-90, 56.6% female, 84.5% White). We contrasted depressed participants (unipolar non-psychotic major depression as diagnosed by the Structured Clinical Interview for DSM Disorders) who had a history of suicide attempt (N=92) with depressed non-attempters (N=138) who had no history of suicidal behavior but may or may not have had ideation. In addition, 67 healthy controls (no lifetime history of psychiatric illness) served as a benchmark comparison group. We used the Beck Scale for Suicidal Ideation to measure the severity of suicidal ideation, and the Hamilton Depression Rating Scale to measure depression severity. We used a combination of 6 self-report scales (Flourishing Scale, Interpersonal Support Evaluation List [Tangible, Belonging, Self-esteem, and Appraisal support subscores], Mindfulness Attention Awareness Scale, Satisfaction with Life Survey, Life Engagement Test and the Social Network Index [network diversity, number of people in social networks, embedded networks subscores]). All variables were scaled and then averaged to calculate one overall protective factor value to represent levels of mindfulness, satisfaction and engagement with life, objective and subjective social support, and subjective well-being. We used this protective factor as the predictor variable and conducted binomial logistic regression to assess its relationship with presence of ideation and past attempt, and linear regression models for its relationship with depression and ideation severity. <h3>Results</h3> The overall protective factor value significantly predicted depression severity (p=0.003) and likelihood of ideation (p=0.030) but did not predict ideation severity (p=0.136) or likelihood of past suicide attempt (p=0.954). <h3>Conclusions</h3> Previously identified factors that have been associated with psychological resilience in late life may, in fact, be more predictive of depression severity and presence of ideation than severity of ideation or suicide attempt. Thus, interventions to decrease suicidal behavior in late-life depression may need to go beyond focusing on traditionally stated social support or life-satisfaction/engagement measures and consider other factors such as personality and cognitive capacity. <h3>This research was funded by</h3> NIMH R01-MH085651-10

The Neglected Role of Psychotherapy for Treatment-Resistant Depression.

The Neglected Role of Psychotherapy for Treatment-Resistant Depression.

P.0694 Pharmacological approach to psychotic depression: a retrospective study of antidepressant and antipsychotic use in a psychiatry ward

Recent data suggests that psychotic major depression (PMD) may be a discrete disorder distinguishable from nonpsychotic major depression (NPMD), and that patients with PMD may be more similar to individuals with schizophrenia than individuals with NPMD. The insula is a brain region in which morphometric changes have been associated with psychotic symptom severity in schizophrenia and affective psychosis. It was hypothesized that insular volumes would be reduced in PMD compared to NPMD and controls, and insular volumes would correlate with psychosis but not depression severity. Insular gray matter volumes were measured in PMD and NPMD patients and matched healthy controls using magnetic resonance images and manual morphometry. Clinical measures of illness severity were obtained to determine their relationship with insular volume. Posterior insular volumes were significantly reduced in PMD compared to HC. There were also significant group-by-gender interactions for total, anterior and posterior insular volumes. Using Pearson product-moment correlations, anterior insular volumes did not correlate with depression severity. Left anterior insular volume was significantly correlated with total and positive symptom psychosis severity in the PMD group. Atypical insular morphometry may be related to the inability to distinguish between internally and externally generated sensory inputs characteristic of psychosis.

Neural Substrates of Psychotic Depression: Findings From the Global ECT-MRI Research Collaboration.

Psychotic major depression (PMD) is hypothesized to be a distinct clinical entity from nonpsychotic major depression (NPMD). However, neurobiological evidence supporting this notion is scarce. The aim of this study is to identify gray matter volume (GMV) differences between PMD and NPMD and their longitudinal change following electroconvulsive therapy (ECT). Structural magnetic resonance imaging (MRI) data from 8 independent sites in the Global ECT-MRI Research Collaboration (GEMRIC) database (n = 108; 56 PMD and 52 NPMD; mean age 71.7 in PMD and 70.2 in NPMD) were analyzed. All participants underwent MRI before and after ECT. First, cross-sectional whole-brain voxel-wise GMV comparisons between PMD and NPMD were conducted at both time points. Second, in a flexible factorial model, a main effect of time and a group-by-time interaction were examined to identify longitudinal effects of ECT on GMV and longitudinal differential effects of ECT between PMD and NPMD, respectively. Compared with NPMD, PMD showed lower GMV in the prefrontal, temporal and parietal cortex before ECT; PMD showed lower GMV in the medial prefrontal cortex (MPFC) after ECT. Although there was a significant main effect of time on GMV in several brain regions in both PMD and NPMD, there was no significant group-by-time interaction. Lower GMV in the MPFC was consistently identified in PMD, suggesting this may be a trait-like neural substrate of PMD. Longitudinal effect of ECT on GMV may not explain superior ECT response in PMD, and further investigation is needed.

Clinical characteristics and sociodemographic features of psychotic major depression

BackgroundPsychotic major depression (PMD) is a subtype of depression with a poor prognosis. Previous studies have failed to find many differences between patients with PMD and those with non-psychotic major depression (NMD) or schizophrenia (SZ). We compared sociodemographic factors (including season of conception) and clinical characteristics between patients with PMD, NMD, and schizophrenia. Our aim was to provide data to help inform clinical diagnoses and future etiology research.MethodsThis study used data of all patients admitted to Shandong Mental Health Center from June 1, 2016 to December 31, 2017. We analyzed cases who had experienced an episode of PMD (International Classification of Diseases, Tenth Revision codes F32.3, F33.3), NMD (F32.0–2/9, F33.0–2/9), and SZ (F20–20.9). Data on sex, main discharge diagnosis, date of birth, ethnicity, family history of psychiatric diseases, marital status, age at first onset, education, allergy history, and presence of trigger events were collected. Odds ratios (OR) were calculated using logistic regression analyses. Missing values were filled using the k-nearest neighbor method.ResultsPMD patients were more likely to have a family history of psychiatric diseases in their first-, second-, and third-degree relatives ([OR] 1.701, 95% confidence interval [CI] 1.019–2.804) and to have obtained a higher level of education (OR 1.451, 95% CI 1.168–1.808) compared with depression patients without psychotic features. Compared to PMD patients, schizophrenia patients had lower education (OR 0.604, 95% CI 0.492–0.741), were more often divorced (OR 3.087, 95% CI 1.168–10.096), had a younger age of onset (OR 0.934, 95% CI 0.914–0.954), less likely to have a history of allergies (OR 0.604, 95% CI 0.492–0.741), and less likely to have experienced a trigger event 1 year before first onset (OR 0.420, 95% CI 0.267–0.661). Season of conception, ethnicity, and sex did not differ significantly between PMD and NMD or schizophrenia and PMD.ConclusionsPMD patients have more similarities with NMD patients than SZ patients in terms of demographic and clinical characteristics. The differences found between PMD and SZ, and PMD and NMD correlated with specificity of the diseases. Furthermore, allergy history should be considered in future epidemiological studies of psychotic disorders.

Relationships Among History of Psychosis, Cognition and Functioning in Later-Life Remitted Major Depression

ObjectiveThis study tested the hypotheses that, in older adults with remitted major depression, a history of psychotic features and poorer neuropsychological performance would be independently associated with poorer everyday functioning, but that neuropsychological performance would explain more of the variance in functioning than history of psychotic features. MethodsThis cross-sectional study included 73 patients aged 50 years or older with remitted psychotic major depression or nonpsychotic major depression. The dependent variables were subjective and objective measures of function. The independent variables were history of psychotic features during one or more major depressive episodes in the previous 10 years and neuropsychological performance. Linear regression models examined the association of independent variables with function, controlling for pertinent covariates. Effect sizes were calculated for the magnitude of difference in function between the patient participants and an age- and gender-matched nonpsychiatric group, and distribution of functioning scores were compared between groups. ResultsIn separate models, history of psychotic features and poorer processing speed, executive function, and verbal learning were independently associated with poorer participant-reported functioning and performance-based functioning. However, the association of psychotic features with functioning was no longer statistically significant when tested in the same models as neuropsychological measures. Effect sizes of the difference in functioning between patients and the nonpsychiatric group were significantly larger for the remitted psychotic than the remitted nonpsychotic depression group; functioning scores were more heterogeneous in the remitted psychotic depression group. ConclusionPatients with remitted psychotic depression exhibit greater, and clinically important, impairment in everyday functioning than those with remitted nonpsychotic depression. Neuropsychological impairment appears to contribute to this relationship.

Relationship of psychotic symptoms with childhood abuse and psychological resilience in patients with depression

Objective To explore relationship of psychotic symptoms with childhood abuse and psychological resilience in patients with depression. Methods According to whether the psychotic symptoms exist, 160 patients with depression were divided into psychotic major depression (PMD group, n=80) and nonpsychotic major depression (NMD group, n=80). All patients were assessed with general information questionnaire, the childhood trauma questionnaire(CTQ)and the Conner-Davidson resilience scale(CD-RISC). Using logistic regression analysis to explore the influencing factors of psychiatric symptoms in depressive patients. Results There were significant differences in the emotional abuse ((17.80±2.78), (10.14±1.46)), the physical abuse ((16.98±3.21), (8.31±1.24)), the sexual abuse ((8.74±1.87), (7.85±1.71)), the emotional neglect ((21.46±1.95), (15.71±2.12)) and total score of childhood abuse ((81.98±9.88), (54.10±4.36)) between the two group (F=68.88, 70.91, 2.91, 45.93, 77.28, all P<0.01). There were significant differences in the resilience (F=4.47, P<0.01), the power (F=5.59, P<0.01), the optimism (F=2.35, P=0.033) and total score of psychological resilience (F=7.23, P<0.01) between the two group.Logistic regression analysis showed that attack in early age(B=2.57, P=0.024, OR(95%CI)=13.07(1.01-169.54))was a risk factor for psychotic symptoms in patients with depression.No experience of childhood abuse (B=-1.95, P=0.003, OR(95%CI)=0.14(0.04-0.52)), the higher psychological resilience level(B=-2.54, P<0.01, OR(95%CI)=0.08(0.02-0.27)), mild to moderate depression (B=-1.33, P=0.013, OR(95%CI)=0.27(0.09-0.76))were protective factors of psychotic symptoms in patients with depression. Conclusion Psychological resilience may be the protective factor for psychotic symptoms in patients with depression while childhood abuse may be a risk factor. Key words: Depression; Psychotic symptoms; Childhood abuse; Psychological resilience

Machine-learning based brain age estimation in major depression showing no evidence of accelerated aging

Molecular biological findings indicate that affective disorders are associated with processes akin to accelerated aging of the brain. The use of the BrainAGE (brain age estimation gap) framework allows machine-learning based detection of a gap between age estimated from high-resolution MRI scans an chronological age, and thus an indicator of systems-level accelerated aging. We analysed 3T high-resolution structural MRI scans in 38 major depression patients (without co-morbid axis I or II disorders) and 40 healthy controls using the BrainAGE method to test the hypothesis of accelerated aging in (non-psychotic) major depression. We found no significant difference (or trend) for elevated BrainAGE in this pilot sample. Unlike previous findings in schizophrenia (and partially bipolar disorder), unipolar depression per se does not seem to be associated with accelerated aging patterns across the brain. However, given the limitations of the sample, further study is needed to test for effects in subgroups with comorbidities, as well as longitudinal designs.

Glucose-6-phosphate dehydrogenase activity in bipolar disorder and schizophrenia: Relationship to mitochondrial impairment

Glucose-6-phosphate dehydrogenase (G6PD) is the first and rate-limiting enzyme of the pentose phosphate pathway that is essential to maintaining cellular redox balance. G6PD is especially plentiful in brain, and its deficiency has been linked to mood and psychotic disorders. We measured G6PD activity spectrophotometrically in four groups of 15 parietal somatosensory association cortex [Brodmann area (BA) 7] tissue samples (N = 60) from individuals with bipolar disorder (BPD); nonpsychotic unipolar major depression (UPD); schizophrenia (SCZ), and controls without psychiatric illness (CON). We report for the first time brain G6PD activity levels in these disorders. G6PD activity did not differ by brain group. In BPD and SCZ brains, however, it correlated significantly and inversely with percent of hexokinase 1 (HK1) in the tissue homogenate mitochondrial fraction as determined previously in another set of tissue samples obtained from the same brains and brain region. The correlation in SCZ brains lost statistical significance after controlling for brain pH. This finding indicates a positive relationship in BPD brains between G6PD activity and HK1 mitochondrial detachment, an indicator of mitochondrial impairment associated with increased mitochondrial generation of reactive oxygen species. We speculate that this relationship could be evidence that G6PD activity is proportionate to and may be a compensatory response to oxidative stress in the BA7 region of BPD brains. Future research should focus on clarifying the relationships among G6PD activity, markers of oxidative stress, brain pH, and evidence of mitochondrial impairment, particularly HK1 mitochondrial detachment, in brains of individuals with G6PD deficiency, BPD and SCZ.

THE ASSOCIATIONS AMONG HISTORY OF PSYCHOSIS, NEUROPSYCHOLOGICAL PERFORMANCE, AND FUNCTIONING IN REMITTED LATER-LIFE MAJOR DEPRESSION

Introduction Observational studies report that people with psychotic major depressive disorder (PMD) have poorer functional outcome than those with non-psychotic major depression (NPMD), but this finding could be explained by less robust recovery and residual symptoms in PMD. In addition, neuropsychological performance is worse in those with PMD than NPMD, both acutely and in remission. The aim of this study was to examine the relative contributions of a history of psychosis and neuropsychological performance to impaired everyday function in patients with remitted later-life major depressive disorder (MDD). We hypothesized that, in later-life patients with MDD, a history of psychotic features and poorer neuropsychological function would be independently associated with poorer everyday functioning, but that poorer neuropsychological performance would be more strongly associated with poorer functioning compared to history of psychosis. In order to place the results in a broader context, we examined everyday functioning in an age- and gender-matched non-psychiatric comparison group. Methods This cross-sectional design study included 73 patients aged 50 years and older with a history of MDD (n = 51 with NPMD and n = 22 with PMD) in sustained remission and 42 non-psychiatric comparison subjects. Sociodemographic, clinical, neuropsychological, and functional data were collected by an investigator blind to the history of psychotic features. Everyday functioning, the dependent variable, was divided into general functioning (measured by participant-report) and IADL performance (measured by observer-rated assessment). The independent variables were i) history of psychosis and ii) neuropsychological performance in the domains of processing speed, memory, and executive function. Relationships between each independent variable and functioning were analyzed using multiple linear regression models. The relative contribution of history of psychosis and neuropsychological performance to functioning was analyzed using multiple regression models with history of psychosis entered in the first step and the neuropsychological variable in the second step. All models included covariates that were potential confounders. We also calculated effect sizes for the difference in functioning between MDD and non-psychiatric comparison participants. Results Patients with PMD exhibited substantial deficits in measures of processing speed and, to a lesser extent, executive function, compared to NPMD patients and to population norms. History of psychosis was independently related to poorer IADL performance (β = 0.262, t = 3.03, p = 0.004) and general functioning (β = -0.29, t = -2.46, p = 0.017). Poorer performance on measures of processing speed (β = -0.468, t = -4.99, p In comparison to non-psychiatric subjects, the effect size of functional impairment in patients with remitted PMD was large (Cohen's d for IADL function = 0.80; Cohen's d for general functioning = 0.97), whereas the impairment was small to moderate in remitted NPMD (Cohen's d for IADL function = 0.10; Cohen's d for general functioning = 0.64). Conclusions Later-life remitted PMD is associated with poorer everyday functioning compared to NPMD, with clinically-significant deficits. However, this relationship is no longer significant when neuropsychological function, especially processing speed, is accounted for. This study advances previous literature by including only patients with rigorously-defined sustained remission and measuring functioning comprehensively using both participant-report and performance-based measures. We will discuss future directions of these research findings, including examining neurobiological correlates of processing speed deficits in remitted PMD. This research was funded by This study was funded by the University Health Network Centre for Mental Health's research grant ($14,000)

Prediction of remission in pharmacotherapy of untreated major depression: development and validation of multivariable prediction models.

Depression is increasingly recognized as a chronic and relapsing disorder. However, an important minority of patients who start treatment for their major depressive episode recover to euthymia. It is clinically important to be able to predict such individuals. The study is a secondary analysis of a recently completed pragmatic megatrial examining first- and second-line treatments for hitherto untreated episodes of non-psychotic unipolar major depression (n = 2011). Using the first half of the cohort as the derivation set, we applied multiply-imputed stepwise logistic regression with backward selection to build a prediction model to predict remission, defined as scoring 4 or less on the Patient Health Quetionnaire-9 at week 9. We used three successively richer sets of predictors at baseline only, up to week 1, and up to week 3. We examined the external validity of the derived prediction models with the second half of the cohort. In total, 37.0% (95% confidence interval 34.8-39.1%) were in remission at week 9. Only the models using data up to week 1 or 3 showed reasonable performance. Age, education, length of episode and depression severity remained in the multivariable prediction models. In the validation set, the discrimination of the prediction model was satisfactory with the area under the curve of 0.73 (0.70-0.77) and 0.82 (0.79-0.85), while the calibration was excellent with non-significant goodness-of-fit χ2 values (p = 0.41 and p = 0.29), respectively. Patients and clinicians can use these prediction models to estimate their predicted probability of achieving remission after acute antidepressant therapy.

Diagnostic differences in verbal learning strategies and verbal memory in patients with mood disorders and psychotic disorders

A better understanding of verbal learning strategies can offer insight to the difference in verbal memory performance and learning between patients with schizophrenia and schizoaffective disorders, non-psychotic major depression, and psychotic major depression. To date, a comparison of the use of verbal learning strategies and verbal memory performance amongst these specific diagnostic groups has not been investigated. This study examined differences in verbal learning and memory between psychotic major depression (n = 31), nonpsychotic major depression (n = 30), and schizophrenia spectrum disorders (n = 17) disorders. Verbal learning and memory were assessed through the use of the California Verbal Learning Test-II (CVLT-II). Correlations and multiple regression analyses were conducted to analyze differences in verbal learning and memory amongst these groups. There were no significant differences in the use of Semantic Clustering. Diagnostic differences were observed in the use of Serial and Subjective Clustering. The psychotic major depression group utilized Serial Clustering strategy significantly less than the nonpsychotic major depression group. Learning strategies significantly predicted learning and recall. These findings lend support to the hypothesis that learning strategies predict verbal memory performance across diagnostic groups. The present study contains useful information on diagnostic differences in verbal learning and memory, and a framework by which treatment could be tailored to enhance learning specific to these diagnostic groups.

Cost-effectiveness of Electroconvulsive Therapy vs Pharmacotherapy/Psychotherapy for Treatment-Resistant Depression in the United States

Electroconvulsive therapy (ECT) is a highly effective treatment for depression but is infrequently used owing to stigma, uncertainty about indications, adverse effects, and perceived high cost. To assess the cost-effectiveness of ECT compared with pharmacotherapy/psychotherapy for treatment-resistant major depressive disorder in the United States. A decision analytic model integrating data on clinical efficacy, costs, and quality-of-life effects of ECT compared with pharmacotherapy/psychotherapy was used to simulate depression treatment during a 4-year horizon from a US health care sector perspective. Model input data were drawn from multiple meta-analyses, randomized trials, and observational studies of patients with depression. Where possible, data sources were restricted to US-based studies of nonpsychotic major depression. Data were analyzed between June 2017 and January 2018. Six alternative strategies for incorporating ECT into depression treatment (after failure of 0-5 lines of pharmacotherapy/psychotherapy) compared with no ECT. Remission, response, and nonresponse of depression; quality-adjusted life-years; costs in 2013 US dollars; and incremental cost-effectiveness ratios. Strategies with incremental cost-effectiveness ratios of $100 000 per quality-adjusted life-year or less were designated cost-effective. Based on the Sequenced Treatment Alternatives to Relieve Depression trial, we simulated a population with a mean (SD) age of 40.7 (13.2) years, and 62.2% women. Over 4 years, ECT was projected to reduce time with uncontrolled depression from 50% of life-years to 33% to 37% of life-years, with greater improvements when ECT is offered earlier. Mean health care costs were increased by $7300 to $12 000, with greater incremental costs when ECT was offered earlier. In the base case, third-line ECT was cost-effective, with an ICER of $54 000 per quality-adjusted life-year. Third-line ECT remained cost-effective in a range of univariate, scenario, and probabilistic sensitivity analyses. Incorporating all input data uncertainty, we estimate a 74% to 78% likelihood that at least 1 of the ECT strategies is cost-effective and a 56% to 58% likelihood that third-line ECT is the optimal strategy. For US patients with treatment-resistant depression, ECT may be an effective and cost-effective treatment option. Although many factors influence the decision to proceed with ECT, these data suggest that, from a health-economic standpoint, ECT should be considered after failure of 2 or more lines of pharmacotherapy/psychotherapy.

Association of serum BDNF levels with psychotic symptom in chronic patients with treatment-resistant depression in a Chinese Han population

The neurotrophic hypothesis of depression is supported by consistent findings of lower serum BDNF levels in depressed patients. Increasing evidence shows different clinical characteristics of patients with psychotic major depression versus nonpsychotic major depression. However, the possible association between BDNF and psychotic symptoms in depression has not been investigated. We recruited 90 treatment-resistant depression (TRD) patients and 90 gender- and age-matched healthy control subjects and examined serum BDNF in both groups. Patients’ depressive symptoms were assessed using the 17-item Hamilton Depression Rating Scale (HDRS-17), and psychopathological symptoms by the 18-item Brief Psychiatric Rating Scale (BPRS-18). Our results showed that BDNF levels were significantly lower in patients than controls. Correlation analysis revealed a significantly positive correlation between BDNF and the thought disturbance subscale of BPRS-18 (p < 0.05), and a trend toward a significantly positive correlation between BDNF and the BPRS-18 total score (p = 0.06). Stepwise multiple regression analyses confirmed BDNF as the influencing factor for the thought disturbance subscales of the BPRS-18. Our findings suggest that BDNF may be involved in the pathophysiology of TRD, and its associated psychotic symptoms, especially thought disturbance.