Electroconvulsive therapy (ECT) is a highly therapeutic and cost-effective treatment for severe and/or treatment-resistant major depression. However, because of the varied clinical practices, there is a great deal of heterogeneity in how ECT is delivered and documented. This represents both an opportunity to study how differences in implementation influence clinical outcomes and a challenge for carrying out coordinated quality improvement and research efforts across multiple ECT centers. The National Network of Depression Centers, a consortium of 26+ US academic medical centers of excellence providing care for patients with mood disorders, formed a task group with the goals of promoting best clinical practices for the delivery of ECT and to facilitate large-scale, multisite quality improvement and research to advance more effective and safe use of this treatment modality. The National Network of Depression Centers Task Group on ECT set out to define best practices for harmonizing the clinical documentation of ECT across treatment centers to promote clinical interoperability and facilitate a nationwide collaboration that would enable multisite quality improvement and longitudinal research in real-world settings. This article reports on the work of this effort. It focuses on the use of ECT for major depressive disorder, which accounts for the majority of ECT referrals in most countries. However, most of the recommendations on clinical documentation proposed herein will be applicable to the use of ECT for any of its indications.

Background Magnetic seizure therapy (MST) is a novel convulsive therapy that has been shown to have antidepressant efficacy comparable to electroconvulsive therapy (ECT) with fewer cognitive side effects. However, the cardiovascular (CVS) effects of high frequency MST in comparison to ECT have not been investigated. Materials and Methods Forty-five patients with depression received 6 treatment sessions of 100 Hz MST versus 6 bifrontal ECT treatments in a nonrandomized comparative clinical design. Data on CVS function including heart rate (HR), systolic blood pressure (SBP), diastolic blood pressure (DBP), and rate pressure product (RPP) were collected at baseline (T0), after the induction of anesthesia but before the electrical stimulation (T1), during convulsion (T2), 2 minutes after cessation of motor seizure (T3), 5 minutes after cessation of motor seizure (T4), and 10 minutes after cessation of motor seizure (T5). Comparisons were made with baseline data and between MST and ECT groups. Results There were statistically significant elevations in the maximum HR, SBP, DBP, and RPP in patients receiving ECT compared with MST both in the initial and sixth treatments (all P < 0.05). Particularly, at T2, the ECT group had significantly higher HR, SBP, DBP, and RPP than those in MST group both in initial and sixth treatment (all P < 0.001). At the sixth treatment, the ECT group had significantly higher SBP, DBP, and RPP during the treatment than in the MST group (all P < 0.001). Limitations The anesthetic choices for this study may limit the generalizability of our findings. The sample size was relatively small. Conclusions Compared with ECT, high-frequency MST has fewer CVS side effects and may be a safer option for depression patients with CVS disorders.

OBJECTIVE: The aim of this study was to catalog and evaluate response biomarkers correlated with autism spectrum disorder (ASD) symptoms to improve clinical trials. METHODS: A systematic review of MEDLINE, Embase, and Scopus was conducted in April 2020. Seven criteria were applied to focus on original research that includes quantifiable response biomarkers measured alongside ASD symptoms. Interventional studies or human studies that assessed the correlation between biomarkers and ASD-related behavioral measures were included. RESULTS: A total of 5,799 independent records yielded 280 articles for review that reported on 940 biomarkers, 755 of which were unique to a single publication. Molecular biomarkers were the most frequently assayed, including cytokines, growth factors, measures of oxidative stress, neurotransmitters, and hormones, followed by neurophysiology (e.g., EEG and eye tracking), neuroimaging (e.g., functional MRI), and other physiological measures. Studies were highly heterogeneous, including in phenotypes, demographic characteristics, tissues assayed, and methods for biomarker detection. With a median total sample size of 64, almost all of the reviewed studies were only powered to identify biomarkers with large effect sizes. Reporting of individual-level values and summary statistics was inconsistent, hampering mega- and meta-analysis. Biomarkers assayed in multiple studies yielded mostly inconsistent results, revealing a "replication crisis." CONCLUSIONS: There is currently no response biomarker with sufficient evidence to inform ASD clinical trials. This review highlights methodological imperatives for ASD biomarker research necessary to make definitive progress: consistent experimental design, correction for multiple comparisons, formal replication, sharing of sample-level data, and preregistration of study designs. Systematic "big data" analyses of multiple potential biomarkers could accelerate discovery.

Background: Social media holds exciting promise for advancing mental health research recruitment, however, the extent and efficacy to which these platforms are currently in use are underexplored. Objective: A systematic review was conducted to characterize the current use and efficacy of social media in recruiting participants for mental health research. Method: A literature review was performed using MEDLINE, EMBASE, and PsychINFO. Only non-duplicative manuscripts written in the English language and published between 1/1/2004–3/31/2019 were selected for further screening. Data extracted included study type and design, participant inclusion criteria, social media platform, advertising strategy, final recruited sample size, recruitment location, year, monetary incentives, comparison to other recruitment methods if performed, and final cost per participant. Results: A total of 176 unique studies that used social media for mental health research recruitment were reviewed. The majority of studies were cross-sectional (62.5%) in design and recruited adults. Facebook was overwhelmingly the recruitment platform of choice (92.6%), with the use of paid advertisements being the predominant strategy (60.8%). Of the reviewed studies, substance abuse (43.8%) and mood disorders (15.3%) were the primary subjects of investigation. In 68.3% of studies, social media recruitment performed as well as or better than traditional recruitment methods in the number and cost of final enrolled participants. The majority of studies used Facebook for recruitment at a median cost per final recruited study participant of $19.47. In 55.6% of the studies, social media recruitment was the more cost-effective recruitment method when compared to traditional methods (e.g., referrals, mailing). Conclusion: Social media appears to be an effective and economical recruitment tool for mental health research. The platform raises methodological and privacy concerns not covered in current research regulations that warrant additional consideration.

Introduction: Focal brain stimulation has potential as a treatment for posttraumatic stress disorder (PTSD). In this review, we aim to inform selection of focal brain stimulation targets for treating PTSD by examining studies of the functional neuroanatomy of PTSD and treatment response. We first briefly review data on brain stimulation interventions for PTSD. Although published data suggest good efficacy overall, the neurobiological rationale for each stimulation target is not always clear. Methods: Therefore, we assess pre- and post-treatment (predominantly psychotherapy) functional neuroimaging studies in PTSD to determine which brain changes seem critical to treatment response. Results of these studies are presented within a previously proposed functional neural systems model of PTSD. Results: While not completely consistent, research suggests that downregulating the fear learning and threat and salience detection circuits (i.e., amygdala, dorsal anterior cingulate cortex and insula) and upregulating the emotion regulation and executive function and contextual processing circuits (i.e., prefrontal cortical regions and hippocampus) may mediate PTSD treatment response. Conclusion: This literature review provides some justification for current focal brain stimulation targets. However, the examination of treatment effects on neural networks is limited, and studies that include the stimulation targets are lacking. Further, additional targets, such as the cingulate, medial prefrontal cortex, and inferior parietal lobe, may also be worth investigation, especially when considering how to achieve network level changes. Additional research combining PTSD treatment with functional neuroimaging will help move the field forward by identifying and validating novel targets, providing better rationale for specific treatment parameters and personalizing treatment for PTSD.

The coronavirus disease of 2019 or COVID-19 was first identified in Hubei Province in China in November of 2019 and quickly spread to become a global pandemic. The virus, SARS-Coronavirus-2, is particularly virulent in the elderly who can develop symptoms and become mortally ill within days of contracting the virus. The virus is easily transmitted by droplets (e.g., sneezing and coughing) and communal living settings such as personal care homes can be vulnerable to the spread of the virus. Identifying patients early in the disease process is important to providing appropriate medical interventions. To date, most of the medical literature, including Center for Disease Control guidelines, has relied on three necessary symptoms in making the diagnosis of COVID-19: fever, cough, and shortness of breath. We present four cases of elderly patients who developed altered mental status as their presenting symptom without associated fever or respiratory symptoms.

Background: Calls to implement measurement-based care (MBC) in psychiatry are increasing. A recent Cochrane meta-analysis concluded that there is insufficient evidence that routine application of patient reported outcomes (PROs) improves treatment outcomes for common psychiatric disorders. There is a particular paucity of this information in patients with treatment resistant depression (TRD). Methods: A TRD sample (n = 302) and a treatment-naïve sample with major depression (n = 344) were assessed for the level of agreement in depression severity between two PROs (the Beck Depression Inventory, BDI, and the Quick Inventory of Depressive Symptomatology Self-report, QIDS-SR) and two Clinician Rated (CRs) measures (Hamilton Depression Rating Scale, HDRS, and the Montgomery-Asberg Depression Rating Scale, MADRS). Results: Correlations between CR and PRO total scores in the TRD sample ranged from 0.57 (HDRS-QIDS-SR) to 0.68 (MADRS-BDI), reflecting a moderate-to-strong relationship between assessment tools. Correlations in the treatment naïve sample were non-significantly lower for most comparisons, ranging from 0.51 (HDRS-QIDS-SR) to 0.64 (MADRS-BDI). Few predictors of discordance between CRs and PROs were identified, though chronicity of the current episode in treatment-naïve patients was associated with greater agreement. Limitations: Inter-rater reliability of the clinician interviews was conducted separately within the two studies so we could not determine the reliability between the two groups of raters used in the studies. Conclusion: Findings generally supported acceptably high levels of agreement between patient and clinician ratings of baseline depression severity. More work is needed to determine the extent to which PROs can improve outcomes in MBC for depression and, more specifically, TRD.

Schizophrenia is a complex neuropsychiatric syndrome with a heterogeneous genetic, neurobiological, and phenotypic profile. Currently, no objective biological measures-that is, biomarkers-are available to inform diagnostic or treatment decisions. Neuroimaging is well positioned for biomarker development in schizophrenia, as it may capture phenotypic variations in molecular and cellular disease targets, or in brain circuits. These mechanistically based biomarkers may represent a direct measure of the pathophysiological underpinnings of the disease process and thus could serve as true intermediate or surrogate endpoints. Effective biomarkers could validate new treatment targets or pathways, predict response, aid in selection of patients for therapy, determine treatment regimens, and provide a rationale for personalized treatments. In this review, the authors discuss a range of mechanistically plausible neuroimaging biomarker candidates, including dopamine hyperactivity, N-methyl-d-aspartate receptor hypofunction, hippocampal hyperactivity, immune dysregulation, dysconnectivity, and cortical gray matter volume loss. They then focus on the putative neuroimaging biomarkers for disease risk, diagnosis, target engagement, and treatment response in schizophrenia. Finally, they highlight areas of unmet need and discuss strategies to advance biomarker development.

Background: Acylcarnitines have important functions in mitochondrial energetics and β-oxidation, and have been implicated to play a significant role in metabolic functions of the brain. This retrospective study examined whether plasma acylcarnitine profiles can help biochemically distinguish the three phenotypic subtypes of major depressive disorder (MDD): core depression (CD+), anxious depression (ANX+), and neurovegetative symptoms of melancholia (NVSM+). Methods: Depressed outpatients (n = 240) from the Mayo Clinic Pharmacogenomics Research Network were treated with citalopram or escitalopram for eight weeks. Plasma samples collected at baseline and after eight weeks of treatment with citalopram or escitalopram were profiled for short-, medium- and long-chain acylcarnitine levels using AbsoluteIDQ®p180-Kit and LC-MS. Linear mixed effects models were used to examine whether acylcarnitine levels discriminated the clinical phenotypes at baseline or eight weeks post-treatment, and whether temporal changes in acylcarnitine profiles differed between groups. Results: Compared to ANX+, CD+ and NVSM+ had significantly lower concentrations of short- and long-chain acylcarnitines at both baseline and week 8. In NVSM+, the medium- and long-chain acylcarnitines were also significantly lower in NVSM+ compared to ANX+. Short-chain acylcarnitine levels increased significantly from baseline to week 8 in CD+ and ANX+, whereas medium- and long-chain acylcarnitines significantly decreased in CD+ and NVSM+. Conclusions: In depressed patients treated with SSRIs, β-oxidation and mitochondrial energetics as evaluated by levels and changes in acylcarnitines may provide the biochemical basis of the clinical heterogeneity of MDD, especially when combined with clinical characteristics.