Early effects predict trajectories of response to esketamine in treatment-resistant depression.

BACKGROUND: The efficacy of esketamine in treatment-resistant depression (TRD) has been confirmed. However, its administration is expensive and restrictive, with limited knowledge on how long the treatment should be continued. Predicting the treatment outcome would benefit patients and alleviate the global treatment cost. We aimed to define distinct trajectories of treatment response and assess their predictability. METHODS: In this longitudinal study, two independent samples of patients with unipolar or bipolar TRD were treated with esketamine in real-world settings. Depression severity was assessed using the Montgomery-Åsberg Depression Rating Scale (MADRS) before each esketamine administration. Latent class analyses were used to define trajectories of response. RESULTS: In the original sample (N = 50), we identified two classes whose trajectories depicted response and non-response, respectively. The model was validated in the confirmatory sample (N = 55). Class membership was influenced by a few baseline characteristics such as concomitant benzodiazepine medication, number of depressive episodes or polarity. On the other hand, after only two esketamine administrations, the MADRS score predicted the 90-day trajectory of response with an accuracy of 80 %. LIMITATIONS: This observational study is not placebo-controlled. Therefore, its results and their generalizability need to be confirmed in experimental settings. CONCLUSIONS: After the first administrations of esketamine, the MADRS score has a good capacity to predict the most plausible trajectory of response. While thresholds and their predictive values need to be confirmed, this finding suggests that clinicians could base on MADRS scores their decision to discontinue treatment because of poor remaining chances of treatment response.

Depressive-, Cognitive- or Stroke-Related Risk Factors of Post-Stroke Depression: Which One Could Better Help Clinicians and Patients?

PURPOSE: Post-stroke depression (PSD) affects one third of stroke survivors, with multiple severe negative consequences. We aim to assess the weight of four different types of clinical risk factors for PSD. PATIENTS AND METHODS: We conducted a prospective cohort study in a stroke centre. After stroke, patients were assessed for cognitive performances, psychiatric standardized questionnaires and socio-demographic features. They were called three months after and assessed for major depressive episode using DSM criteria. RESULTS: PSD was diagnosed in 8 of the 59 (13.6%) patients enrolled in the study. After multivariate analysis, only "previous history of depressive episode" remained a significant predictive factor for PSD, the model explaining 19% of the total variance (OR=18.0; p=0.002). Patients with a previous history of depression had a 10-fold increased risk for PSD. CONCLUSION: Previous history of depression is confirmed as a strong risk factor for PDS and allow the identification of an at-risk sub-group of patients.

Risky decision-making in suicide attempters, and the choice of a violent suicidal means: an updated meta-analysis.

BACKGROUND: Studies showed disadvantageous decision-making in suicide attempters. The present meta-analysis aims to examine the stability of these findings and related questions. METHODS: EMBASE and Pubmed databases were searched for studies published between 01/01/2000 and 01/01/2020 with an additional search through bibliographical references. English or French articles published in peer-reviewed journals, reporting quantitative task-based measures of decision-making in suicide attempters were included: 3,582 records were identified, 33 full-text articles screened, and 21 articles finally included. RESULTS: All studies were conducted in mood disorders; 18 used the Iowa Gambling Task (IGT) and 3 the Cambridge Gamble Task (CGT). With the IGT, suicide attempters showed riskier choices than patient controls (Hedges' g=-0.28 95%CI (-0.44 - -0.12)) and healthy controls (g=-0.54 (-0.83 - -0.25)) with no significant difference between control groups. The difference between suicide attempters and patient controls was not related to age group, mood disorder type, author, or research center while an effect of time of publication was found (p=0.006). Poorer performance was also found in suicide attempters compared to patient controls when using the CGT (g=-0.57 95%CI (-0.82 - -0.31)). Suicide attempters who used a violent means showed poorer IGT performance than those who used a non-violent means (3 studies). LIMITATION: Limited number of studies outside mood disorders. No data to calculate a gender effect. CONCLUSION: The present meta-analysis confirmed riskier decision-making in suicide attempters. Although group differences appear to be of modest effect size in general, they were particularly marked in the subgroup of those who used a violent suicidal means.

A meta-analysis of poststroke depression risk factors comparing depressive-related factors versus others.

OBJECTIVES: Poststroke depression (PSD) is a public health issue, affecting one-third of stroke survivors, and is associated with multiple negative consequences. Reviews tried to identify PSD risk factors with discrepant results, highlighting the lack of comparability of the analyzed studies. We carried out a meta-analysis in order to identify clinical risk factors that can predict PSD. DESIGN: PubMed and Web of Science were searched for papers. Only papers with a strictly defined Diagnostic and Statistical Manual of Mental Disorders depression assessment, at least 2 weeks after stroke, were selected. Two authors independently evaluated potentially eligible studies that were identified by our search and independently extracted data using standardized spreadsheets. Analyses were performed using MetaWin®, the role of each variable being given as a risk ratio (RR). RESULTS: Eighteen studies were included in the meta-analysis. Identified risk factors for PSD with RR significantly above 1 were previous history of depression (RR 2.19, confidence interval (CI) 1.52-3.15), disability (RR 2.00, CI 1.58-2.52), previous history of stroke (RR 1.68, CI 1.06-2.66), aphasia (RR 1.47, CI 1.13-1.91), and female gender (RR 1.35, CI 1.14-1.61). Fixed effects model leads to identification of two more risk factors: early depressive symptoms with an RR of 2.32 (CI 1.43-3.79) and tobacco consumption (RR 1.40, CI 1.09-1.81). Time bias was found for alcohol consumption. Sample size was significantly involved to explain the role of "alcohol consumption" and "cognitive impairment." CONCLUSION: Five items were significantly predictive of PSD. It might be of clinical interest that depressive-related risk factors (such as past depressive episodes) were having the largest impact.