Antidepressants in the acute treatment of post-traumatic stress disorder in adults: a systematic review and meta-analysis.

Currently, there are few pharmacotherapy options for clinicians treating post-traumatic stress disorder (PTSD), and antidepressants are usually the medication of choice. This meta-analysis aimed to review the efficacy of antidepressants in the acute treatment of PTSD in adults while investigating the contribution of study design and placebo response to the findings of these studies. Randomized, double-blind, placebo-controlled clinical trials that compared antidepressants with placebo for acute treatment of PTSD were selected. Standardized mean difference (SMD) in change in Clinician-Administered PTSD Scale scores were pooled after examining for heterogeneity. A random-effects meta-analysis was performed. Twenty-nine antidepressant-placebo comparisons, involving 4575 subjects, were analyzed. The SMD among all studies was 0.25, a small to medium effect size, lower than that in studies of antidepressants in adult major depressive disorder. The SMDs for low and high mean placebo responses, were 0.27 and 0.22, respectively. The overall SMD for paroxetine studies was in the moderate range (0.43) and that for sertraline studies was in the small range (0.12). Our findings suggest that antidepressants have modest efficacy in alleviating PTSD symptoms. Patient-level meta-analyses are required to further explore the potential clinical relevance of sertraline for PTSD.

Comparative effectiveness research trial for antidepressant incomplete and non-responders with treatment resistant depression (ASCERTAIN-TRD) a randomized clinical trial.

Further research is needed to help improve both the standard of care and the outcome for patients with treatment-resistant depression. A particularly critical evidence gap exists with respect to whether pharmacological or non-pharmacological augmentation is superior to antidepressant switch, or vice-versa. The objective of this study was to compare the effectiveness of augmentation with aripiprazole or repetitive transcranial magnetic stimulation versus switching to the antidepressant venlafaxine XR (or duloxetine for those not eligible to receive venlafaxine) for treatment-resistant depression. In this multi-site, 8-week, randomized, open-label study, 278 subjects (196 females and 82 males, mean age 45.6 years (SD 15.3)) with treatment-resistant depression were assigned in a 1:1:1 fashion to treatment with either of these three interventions; 235 subjects completed the study. 260 randomized subjects with at least one post-baseline Montgomery-Asberg Depression Rating (MADRS) assessment were included in the analysis. Repetitive transcranial magnetic stimulation (score change (standard error (se)) = -17.39 (1.3) (p = 0.015) but not aripiprazole augmentation (score change (se) = -14.9 (1.1) (p = 0.069) was superior to switch (score change (se) = -13.22 (1.1)) on the MADRS. Aripiprazole (mean change (se) = -37.79 (2.9) (p = 0.003) but not repetitive transcranial magnetic stimulation augmentation (mean change (se) = -42.96 (3.6) (p = 0.031) was superior to switch (mean change (se) = -34.45 (3.0)) on the symptoms of depression questionnaire. Repetitive transcranial magnetic stimulation augmentation was shown to be more effective than switching antidepressants in treatment-resistant depression on the study primary measure. In light of these findings, clinicians should consider repetitive transcranial magnetic stimulation augmentation early-on for treatment-resistant depression.Trial registration: ClinicalTrials.gov, NCT02977299.

Pharmacotherapy: Ketamine and Esketamine.

Ketamine and esketamine have rapid-onset antidepressant effects and may be considered for the management of treatment-resistant depression. Intranasal esketamine has regulatory approval in the United States and European Union. Intravenous ketamine is often administered off-label as an antidepressant, though no standard operating procedures exist. Repeated administrations and the use of a concurrent standard antidepressant may maintain antidepressant effects of ketamine/esketamine. Possible adverse effects of ketamine and esketamine include psychiatric, cardiovascular, neurologic and genitourinary effects, and the potential for abuse. The long-term safety and efficacy of ketamine/esketamine as antidepressants require further study.

Rapidity of Symptom Improvement With Intranasal Esketamine for Major Depressive Disorder: A Systematic Review and Meta-Analysis.

Objective: Rapid-acting treatment options are needed for major depressive disorder (MDD). The objective of this systematic review and meta-analysis was to estimate the magnitude of the treatment effect for intranasal esketamine over placebo at 24 hours after the first dose and at endpoint.Data Sources: PubMed, abstracts of major psychiatric meetings, and ClinicalTrials.gov were searched up to November 2020 with no language constraints, cross-referencing the term intranasal with esketamine and randomized.Study Selection: Of 27 studies reviewed, 8 articles, with a total of 1,437 patients with MDD, met study criteria and were included in the meta-analysis.Data Extraction: Randomized, double-blind clinical trials comparing adjunctive treatment of standard antidepressants with intranasal esketamine for MDD, using intranasal placebo augmentation as a comparator, were selected.Results: Estimates of the standardized mean difference (SMD) in change scores were pooled after examining for homogeneity using the test statistic proposed by DerSimonian and Laird. Findings of the random effects model were presented. Augmentation of standard antidepressants with intranasal esketamine resulted in greater Montgomery-Asberg Depression Rating Scale (MADRS) score reduction than adjunctive intranasal placebo at 24 hours. Across the trials, the SMD was 0.34 (95% CI = 0.11 to 0.46, P < .0001) with a 2.9-point greater mean MADRS score reduction following intranasal esketamine versus active control plus intranasal saline. A similar finding was evident at endpoint.Conclusions: This updated systematic review and meta-analysis found that augmentation of antidepressants with intranasal esketamine was statistically and clinically more effective in reducing depression severity than augmentation with placebo, at both 24 hours and study endpoint. Future studies are needed to evaluate dose-response relationship for esketamine.

Effect of Concomitant Benzodiazepines on the Antidepressant Effects of Ketamine: Findings From the RAPID Intravenous Ketamine Study.

Objective: Ketamine is a novel and rapidly acting treatment for major depressive disorder (MDD). Benzodiazepines are commonly coprescribed with antidepressants in MDD. This study sought to examine data from a randomized clinical trial that compared a single infusion of intravenous (IV) ketamine to midazolam placebo in treatment-resistant depression (DSM-IV-TR MDD) and to assess whether the use of concomitant oral benzodiazepines differentially affected treatment response to ketamine versus midazolam.Methods: This trial ran from December 2015 to December 2016. Subjects who were taking oral benzodiazepines (n = 44) were compared to those who were not (n = 55). A significant treatment-by-benzodiazepine effect could be interpreted as a possible moderator of differential treatment response to ketamine versus midazolam. Benzodiazepine use was examined as both a binary and a continuous predictor, to assess the impact of dosage.Results: Benzodiazepine users did not differ from non-users on the original study's primary outcome measure, score on the 6-item Hamilton Depression Rating Scale (HDRS-6), at baseline, but the former had more severe anxiety. When oral benzodiazepine use was modeled as a binary predictor, benzodiazepine use did not impact differential treatment response. However, when benzodiazepine dosage was considered, there was a significant impact of benzodiazepine use on differential treatment response. Oral benzodiazepines significantly impacted HDRS-6 (P = .018) and Clinical Global Impressions-Severity of Illness scale (CGI-S; P = .008) scores at day 1 (24 hours post treatment); effects were nonsignificant for all day 3 outcomes. Among ketamine subjects, higher doses of benzodiazepines were associated with less improvement in depression scores at day 1.Conclusions: Concomitant oral benzodiazepines at higher doses may attenuate the antidepressant effects of IV ketamine at day 1 but not day 3 post-infusion.Trial Registration: ClinicalTrials.gov identifier: NCT01920555.

Efficacy and Safety of Ketamine vs Electroconvulsive Therapy Among Patients With Major Depressive Episode: A Systematic Review and Meta-analysis.

Importance: Whether ketamine is as effective as electroconvulsive therapy (ECT) among patients with major depressive episode remains unknown. Objective: To systematically review and meta-analyze data about clinical efficacy and safety for ketamine and ECT in patients with major depressive episode. Data Sources: PubMed, MEDLINE, Cochrane Library, and Embase were systematically searched using Medical Subject Headings (MeSH) terms and text keywords from database inception through April 19, 2022, with no language limits. Two authors also manually and independently searched all relevant studies in US and European clinical trial registries and Google Scholar. Study Selection: Included were studies that involved (1) a diagnosis of depression using standardized diagnostic criteria, (2) intervention/comparator groups consisting of ECT and ketamine, and (3) depressive symptoms as an efficacy outcome using standardized measures. Data Extraction and Synthesis: Data extraction was completed independently by 2 extractors and cross-checked for errors. Hedges g standardized mean differences (SMDs) were used for improvement in depressive symptoms. SMDs with corresponding 95% CIs were estimated using fixed- or random-effects models. The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline was followed. Main Outcomes and Measures: Efficacy outcomes included depression severity, cognition, and memory performance. Safety outcomes included serious adverse events (eg, suicide attempts and deaths) and other adverse events. Results: Six clinical trials comprising 340 patients (n = 162 for ECT and n = 178 for ketamine) were included in the review. Six of 6 studies enrolled patients who were eligible to receive ECT, 6 studies were conducted in inpatient settings, and 5 studies were randomized clinical trials. The overall pooled SMD for depression symptoms for ECT when compared with ketamine was -0.69 (95% CI, -0.89 to -0.48; Cochran Q, P = .15; I2 = 39%), suggesting an efficacy advantage for ECT compared with ketamine for depression severity. Significant differences were not observed between groups for studies that assessed cognition/memory or serious adverse events. Both ketamine and ECT had unique adverse effect profiles (ie, ketamine: lower risks for headache and muscle pain; ECT: lower risks for blurred vision, vertigo, diplopia/nystagmus, and transient dissociative/depersonalization symptoms). Limitations included low to moderate methodological quality and underpowered study designs. Conclusions and Relevance: Findings from this systematic review and meta-analysis suggest that ECT may be superior to ketamine for improving depression severity in the acute phase, but treatment options should be individualized and patient-centered.

How Resilient Are Deep Learning Models in Medical Image Analysis? The Case of the Moment-Based Adversarial Attack (Mb-AdA).

In the past years, deep neural networks (DNNs) have become popular in many disciplines such as computer vision (CV). One of the most important challenges in the CV area is Medical Image Analysis (MIA). However, adversarial attacks (AdAs) have proven to be an important threat to vision systems by significantly reducing the performance of the models. This paper proposes a new black-box adversarial attack, which is based οn orthogonal image moments named Mb-AdA. Additionally, a corresponding defensive method of adversarial training using Mb-AdA adversarial examples is also investigated, with encouraging results. The proposed attack was applied in classification and segmentation tasks with six state-of-the-art Deep Learning (DL) models in X-ray, histopathology and nuclei cell images. The main advantage of Mb-AdA is that it does not destroy the structure of images like other attacks, as instead of adding noise it removes specific image information, which is critical for medical models' decisions. The proposed attack is more effective than compared ones and achieved degradation up to 65% and 18% in terms of accuracy and IoU for classification and segmentation tasks, respectively, by also presenting relatively high SSIM. At the same time, it was proved that Mb-AdA adversarial examples can enhance the robustness of the model.

Omics Data and Data Representations for Deep Learning-Based Predictive Modeling.

Medical discoveries mainly depend on the capability to process and analyze biological datasets, which inundate the scientific community and are still expanding as the cost of next-generation sequencing technologies is decreasing. Deep learning (DL) is a viable method to exploit this massive data stream since it has advanced quickly with there being successive innovations. However, an obstacle to scientific progress emerges: the difficulty of applying DL to biology, and this because both fields are evolving at a breakneck pace, thus making it hard for an individual to occupy the front lines of both of them. This paper aims to bridge the gap and help computer scientists bring their valuable expertise into the life sciences. This work provides an overview of the most common types of biological data and data representations that are used to train DL models, with additional information on the models themselves and the various tasks that are being tackled. This is the essential information a DL expert with no background in biology needs in order to participate in DL-based research projects in biomedicine, biotechnology, and drug discovery. Alternatively, this study could be also useful to researchers in biology to understand and utilize the power of DL to gain better insights into and extract important information from the omics data.

International pooled patient-level meta-analysis of ketamine infusion for depression: In search of clinical moderators.

Depression is disabling and highly prevalent. Intravenous (IV) ketamine displays rapid-onset antidepressant properties, but little is known regarding which patients are most likely to benefit, limiting personalized prescriptions. We identified randomized controlled trials of IV ketamine that recruited individuals with a relevant psychiatric diagnosis (e.g., unipolar or bipolar depression; post-traumatic stress disorder), included one or more control arms, did not provide any other study-administered treatment in conjunction with ketamine (although clinically prescribed concurrent treatments were allowable), and assessed outcome using either the Montgomery-Åsberg Depression Rating Scale or the Hamilton Rating Scale for Depression (HRSD-17). Individual patient-level data for at least one outcome was obtained from 17 of 25 eligible trials [pooled n = 809]. Rates of participant-level data availability across 33 moderators that were solicited from these 17 studies ranged from 10.8% to 100% (median = 55.6%). After data harmonization, moderators available in at least 40% of the dataset were tested sequentially, as well as with a data-driven, combined moderator approach. Robust main effects of ketamine on acute [~24-hours; ß*(95% CI) = 0.58 (0.44, 0.72); p < 0.0001] and post-acute [~7 days; ß*(95% CI) = 0.38 (0.23, 0.54); p < 0.0001] depression severity were observed. Two study-level moderators emerged as significant: ketamine effects (relative to placebo) were larger in studies that required a higher degree of previous treatment resistance to federal regulatory agency-approved antidepressant medications (≥2 failed trials) for study entry; and in studies that used a crossover design. A comprehensive data-driven search for combined moderators identified statistically significant, but modest and clinically uninformative, effects (effect size r ≤ 0.29, a small-medium effect). Ketamine robustly reduces depressive symptoms in a heterogeneous range of patients, with benefit relative to placebo even greater in patients more resistant to prior medications. In this largest effort to date to apply precision medicine approaches to ketamine treatment, no clinical or demographic patient-level features were detected that could be used to guide ketamine treatment decisions.Review Registration: PROSPERO Identifier: CRD42021235630.

Biometrics: Going 3D.

Biometrics have been used to identify humans since the 19th century. Over time, these biometrics became 3D. The main reason for this was the growing need for more features in the images to create more reliable identification models. This work is a comprehensive review of 3D biometrics since 2011 and presents the related work, the hardware used and the datasets available. The first taxonomy of 3D biometrics is also presented. The research was conducted using the Scopus database. Three main categories of 3D biometrics were identified. These were face, hand and gait. The corresponding percentages for these categories were 74.07%, 20.37% and 5.56%, respectively. The face is further categorized into facial, ear, iris and skull, while the hand is divided into fingerprint, finger vein and palm. In each category, facial and fingerprint were predominant, and their respective percentages were 80% and 54.55%. The use of the 3D reconstruction algorithms was also determined. These were stereo vision, structure-from-silhouette (SfS), structure-from-motion (SfM), structured light, time-of-flight (ToF), photometric stereo and tomography. Stereo vision and SfS were the most commonly used algorithms with a combined percentage of 51%. The state of the art for each category and the available datasets are also presented. Finally, multimodal biometrics, generalization of 3D reconstruction algorithms and anti-spoofing metrics are the three areas that should attract scientific interest for further research. In addition, the development of devices with 2D/3D capabilities and more publicly available datasets are suggested for further research.

Hand-Crafted and Learned Feature Aggregation for Visual Marble Tiles Screening.

An important factor in the successful marketing of natural ornamental rocks is providing sets of tiles with matching textures. The market price of the tiles is based on the aesthetics of the different quality classes and can change according to the varying needs of the market. The classification of the marble tiles is mainly performed manually by experienced workers. This can lead to misclassifications due to the subjectiveness of such a procedure, causing subsequent problems with the marketing of the product. In this paper, 24 hand-crafted texture descriptors and 20 Convolution Neural Networks were evaluated towards creating aggregated descriptors resulting from the combination of one hand-crafted and one Convolutional Neural Network at a time. A marble tile dataset designed for this study was used for the evaluation process, which was also released publicly to further enable the research for similar studies (both on texture and dolomitic ornamental marble tile analysis). This was done to automate the classification of the marble tiles. The best performing feature descriptors were aggregated together in order to achieve an objective classification. The resulting model was embodied into an automatic screening machine designed and constructed as a part of this study. The experiments showed that the aggregation of the VGG16 and SILTP provided the best results, with an AUC score of 0.9944.

Digital Watermarking as an Adversarial Attack on Medical Image Analysis with Deep Learning.

In the past years, Deep Neural Networks (DNNs) have become popular in many disciplines such as Computer Vision (CV), and the evolution of hardware has helped researchers to develop many powerful Deep Learning (DL) models to deal with several problems. One of the most important challenges in the CV area is Medical Image Analysis. However, adversarial attacks have proven to be an important threat to vision systems by significantly reducing the performance of the models. This paper brings to light a different side of digital watermarking, as a potential black-box adversarial attack. In this context, apart from proposing a new category of adversarial attacks named watermarking attacks, we highlighted a significant problem, as the massive use of watermarks, for security reasons, seems to pose significant risks to vision systems. For this purpose, a moment-based local image watermarking method is implemented on three modalities, Magnetic Resonance Images (MRI), Computed Tomography (CT-scans), and X-ray images. The introduced methodology was tested on three state-of-the art CV models, DenseNet 201, DenseNet169, and MobileNetV2. The results revealed that the proposed attack achieved over 50% degradation of the model's performance in terms of accuracy. Additionally, MobileNetV2 was the most vulnerable model and the modality with the biggest reduction was CT-scans.

Antidepressants in children and adolescents with major depressive disorder and the influence of placebo response: A meta-analysis.

BACKGROUND: There are few available antidepressants for pediatric Major Depressive Disorder (MDD). The objective of this systematic review and meta-analysis was to review industry-funded studies of antidepressants in children and adolescents with MDD, and to better understand the contribution of study design and placebo response to the findings of these studies. METHODS: Randomized, double-blind, placebo-controlled clinical trials that compared antidepressant with placebo for the acute treatment of MDD in children and/or adolescents were selected. Estimates of the standardized mean difference (SMD) in change in Children's Depression Rating Scale-Revised scores were pooled, after examining for heterogeneity. A random-effects meta-analysis was completed. RESULTS: Thirty-four antidepressant-placebo comparisons, involving 6161 subjects, were included. The SMD among all studies was 0.12 (CI 0.08, 0.17; p < 0.001), a very small effect size, lower than that seen in studies of adults with MDD. When the meta-analysis was limited to studies with a low mean placebo response, the SMD increased to 0.19 and further increased to 0.22 when studies with at least a 50% chance of receiving placebo were included. LIMITATIONS: Many studies focused on older children and younger adolescents. Our findings may not reflect antidepressant efficacy in older adolescents. CONCLUSIONS: The modest SMD identified in this analysis may reflect study design factors and the application of antidepressants developed for adults to pediatric patients. Given the urgent clinical need for more pediatric MDD treatments, the influence of placebo response and the need for drug development tailored to this population should be considered in pediatric MDD trial design.

Behavioral Data Analysis of Robot-Assisted Autism Spectrum Disorder (ASD) Interventions Based on Lattice Computing Techniques.

Recent years have witnessed the proliferation of social robots in various domains including special education. However, specialized tools to assess their effect on human behavior, as well as to holistically design social robot applications, are often missing. In response, this work presents novel tools for analysis of human behavior data regarding robot-assisted special education. The objectives include, first, an understanding of human behavior in response to an array of robot actions and, second, an improved intervention design based on suitable mathematical instruments. To achieve these objectives, Lattice Computing (LC) models in conjunction with machine learning techniques have been employed to construct a representation of a child's behavioral state. Using data collected during real-world robot-assisted interventions with children diagnosed with Autism Spectrum Disorder (ASD) and the aforementioned behavioral state representation, time series of behavioral states were constructed. The paper then investigates the causal relationship between specific robot actions and the observed child behavioral states in order to determine how the different interaction modalities of the social robot affected the child's behavior.

Feature Extraction for Finger-Vein-Based Identity Recognition.

This paper aims to provide a brief review of the feature extraction methods applied for finger vein recognition. The presented study is designed in a systematic way in order to bring light to the scientific interest for biometric systems based on finger vein biometric features. The analysis spans over a period of 13 years (from 2008 to 2020). The examined feature extraction algorithms are clustered into five categories and are presented in a qualitative manner by focusing mainly on the techniques applied to represent the features of the finger veins that uniquely prove a human's identity. In addition, the case of non-handcrafted features learned in a deep learning framework is also examined. The conducted literature analysis revealed the increased interest in finger vein biometric systems as well as the high diversity of different feature extraction methods proposed over the past several years. However, last year this interest shifted to the application of Convolutional Neural Networks following the general trend of applying deep learning models in a range of disciplines. Finally, yet importantly, this work highlights the limitations of the existing feature extraction methods and describes the research actions needed to face the identified challenges.

The effect of single administration of intravenous ketamine augmentation on suicidal ideation in treatment-resistant unipolar depression: Results from a randomized double-blind study.

This study aimed to assess the effect of a single infusion of intravenous (IV) ketamine on suicidal ideation in patients with treatment-resistant depression (TRD). Patients with TRD were randomized in a double-blind fashion to a single infusion of IV ketamine or IV midazolam placebo. Suicidal ideation was measured using the Montgomery-Asberg Depression Rating Scale (MADRS) suicide item at 3, 5, 7, 14 and 30 days post infusion. Clinically significant suicidal ideation was defined as a MADRS suicide item score ≥2. Forty patients who received IV ketamine and 16 who received IV midazolam had suicide item scores of ≥2 at baseline (IV ketamine group mean 2.90±0.74; IV midazolam group 2.69±0.70). The mean suicide scores of these groups differed significantly from each other on day 30; the IV ketamine group had a lower mean score than controls (2.03±1.59 vs. 3.00±1.41, t-test p = 0.049; Hedges' g 0.71). Among patients with a suicide score of ≥2 at baseline and <2 at day 3, the two groups did not differ significantly on mean scores changes at days 3, 5, 7, 14 or 30. Recurrence of suicidal ideation was extensive in both treatment groups. A single infusion of IV ketamine may reduce suicidal ideation in TRD out to 30 days post infusion, but early anti-suicidal effects appear to diminish rapidly. This post-hoc analysis was not powered to compare different doses of ketamine. A single infusion of IV ketamine might have a role as an adjunct to standard treatments in patients with TRD and suicidal ideation. Trial registration: NCT01920555.

Vortioxetine Versus Placebo for Major Depressive Disorder: A Comprehensive Analysis of the Clinical Trial Dataset.

Objective: To conduct a meta-analysis of studies of vortioxetine in adults with major depressive disorder (MDD).Data Sources: Abstracts were identified using PubMed by cross-referencing vortioxetine with placebo and randomized. No language or publication year restrictions were used.Study Selection: Randomized, double-blind, placebo-controlled clinical trials comparing oral vortioxetine monotherapy with placebo for acute treatment of MDD.Data Extraction: Data were extracted with a pre-coded form, as follows: number of patients randomized, treatment group, Montgomery-Asberg Depression Rating Scale (MADRS) response and remission rates, and mean change in scores from baseline and standard errors for the MADRS, Hamilton Anxiety Rating Scale (HARS), and Digit Symbol Substitution Test (DSST).Results: 7,269 subjects randomized to vortioxetine (n = 3,630) or placebo (n = 3,639) from 17 studies were included. The probability of receiving placebo did not predict difference in change in MADRS scores between vortioxetine and placebo (estimate = 4.1, P = .54). The standardized mean difference (SMD) (95% CI) for change in MADRS score for vortioxetine overall versus placebo was 0.33 (0.24 to 0.41) and was 0.24 (0.08 to 0.39), 0.33 (0.19 to 0.47), 0.26 (-0.06 to 0.58), and 0.44 (0.27 to 0.62) for 5-mg, 10-mg, 15-mg, and 20-mg doses, respectively. Greater difference in efficacy between drug and placebo was observed in studies with a low rather than a high placebo response rate.Conclusions: Vortioxetine is more effective than placebo in improving depression, anxiety, and cognition. Less informative or uninformative studies obscured the true treatment effect.

Synthesizing the Evidence for Ketamine and Esketamine in Treatment-Resistant Depression: An International Expert Opinion on the Available Evidence and Implementation.

Replicated international studies have underscored the human and societal costs associated with major depressive disorder. Despite the proven efficacy of monoamine-based antidepressants in major depression, the majority of treated individuals fail to achieve full syndromal and functional recovery with the index and subsequent pharmacological treatments. Ketamine and esketamine represent pharmacologically novel treatment avenues for adults with treatment-resistant depression. In addition to providing hope to affected persons, these agents represent the first non-monoaminergic agents with proven rapid-onset efficacy in major depressive disorder. Nevertheless, concerns remain about the safety and tolerability of ketamine and esketamine in mood disorders. Moreover, there is uncertainty about the appropriate position of these agents in treatment algorithms, their comparative effectiveness, and the appropriate setting, infrastructure, and personnel required for their competent and safe implementation. In this article, an international group of mood disorder experts provides a synthesis of the literature with respect to the efficacy, safety, and tolerability of ketamine and esketamine in adults with treatment-resistant depression. The authors also provide guidance for the implementation of these agents in clinical practice, with particular attention to practice parameters at point of care. Areas of consensus and future research vistas are discussed.

Impact of Supplementation and Nutritional Interventions on Pathogenic Processes of Mood Disorders: A Review of the Evidence.

This narrative review was conducted using searches of the PubMed/Medline and Google Scholar databases from inception to November 2019. Clinical trials and relevant articles were identified by cross-referencing major depressive disorder (and/or variants) with the following terms: folate, homocysteine, S-adenosylmethionine (SAMe), L-acetylcarnitine, alpha-lipoic acid, N-acetylcysteine, L-tryptophan, zinc, magnesium, vitamin D, omega-3 fatty acids, coenzyme Q10, and inositol. Manual reviews of references were also performed using article reference lists. Abnormal levels of folate, homocysteine, and SAMe have been shown to be associated with a higher risk of depression. Numerous studies have demonstrated antidepressant activity with L-methylfolate and SAMe supplementation in individuals with depression. Additionally, the amino acids L-acetylcarnitine, alpha-lipoic acid, N-acetylcysteine, and L-tryptophan have been implicated in the development of depression and shown to exert antidepressant effects. Other agents with evidence for improving depressive symptoms include zinc, magnesium, omega-3 fatty acids, and coenzyme Q10. Potential biases and differences in study designs within and amongst the studies and reviews selected may confound results. Augmentation of antidepressant medications with various supplements targeting nutritional and physiological factors can potentiate antidepressant effects. Medical foods, particularly L-methylfolate, and other supplements may play a role in managing depression in patients with inadequate response to antidepressant therapies.

Predictive inflammatory biomarkers for change in suicidal ideation in major depressive disorder and panic disorder: A 12-week follow-up study.

Previous studies have investigated the role of inflammatory markers in suicidality of patients with major depressive disorder (MDD) or panic disorder (PD). However, few studies have investigated associations between serum inflammatory cytokine levels and suicidality. We hypothesized that MDD and PD status might be significantly associated with serum inflammatory cytokines and that we could predict levels of improvement in suicide ideation intensity using serum inflammatory biomarkers in patients with MDD and PD. For this study, 41 patients with MDD, 52 patients with PD, and 59 healthy control (HC) subjects were enrolled. Psychological measurements and serum inflammatory markers such as interleukin (IL) -6, -10, interferon (IFN)-γ, tumor necrosis factor (TNF)-α, and C reactive protein (CRP) were examined. A total of five visits were completed during 12 weeks. After controlling for confounding factors, log-transformed IL-6 (ln_IL-6) at baseline (MDD: 0.297 ± 0.626; PD: 0.342 ± 0.723; HC: -0.121 ± 0.858; p = 0.007, >0.0017, 0.05/30) and mean ln_IL-6 (MDD: 0.395 ± 0.550, PD: 0.249 ± 0.544, HC: -0.139 ± 0.622, p = 0.002, >0.0017, 0.05/30) levels were trends towards significantly higher in patients with MDD and PD than in HC. In MDD patients, a higher level of basal ln_TNF-α was a significant predictor of ΔSSI (changes in SSI scores between baseline and week 12) even after controlling for changes of depression symptoms and baseline SSI scores (standardized ß = 0.541, p = 0.002 < 0.0028, 0.05/18). In conclusion, we could predict ΔSSI using baseline inflammatory biomarkers for patients with MDD.