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Intravenous (IV) ketamine and FDA-approved intranasal (IN) esketamine are increasingly used for treatment-resistant depression (TRD). Preliminary studies have suggested a synergistic effect of ketamine and lamotrigine, although the data are inconclusive. Herein, we report the response to serial ketamine/esketamine treatment among patients with TRD with or without lamotrigine therapy. In this historical cohort study, we included adult patients with TRD who received serial IV racemic ketamine (0.5 mg/kg over 40−100 min) or IN esketamine (56/84 mg) treatments. A change in depressive symptoms was assessed using the 16-item Quick Inventory of Depressive Symptomatology self-report (QIDS-SR) scale. There were no significant differences in response or remission rates among the patients on or not on lamotrigine during the ketamine/esketamine treatments. For a percent change in the QIDS-SR from baseline, no interaction was found between the lamotrigine groups and treatment number (p = 0.70), nor the overall effect of the group (p = 0.38). There was a trend towards lower dissociation (based on the CADSS score) among current lamotrigine users, especially in patients who received IV ketamine. A major limitation is the limited number of patients taking lamotrigine (n = 13). This preliminary study provides insufficient evidence that continuing lamotrigine therapy attenuates the antidepressant effect of repeated ketamine/esketamine; however, there seems to be a signal toward attenuating dissociation with lamotrigine in patients receiving serial ketamine treatments. Further observational studies or randomized controlled trials are needed to replicate these findings.

Abstract There is increasing interest in individualizing treatment selection for more than 25 regulatory approved treatments for major depressive disorder (MDD). Despite an inconclusive efficacy evidence base, antidepressants (ADs) are prescribed for the depressive phase of bipolar disorder with oftentimes an inadequate treatment response and or clinical concern for mood destabilization. This study explored the relationship between antidepressant response in MDD and antidepressant-associated treatment emergent mania (TEM) in bipolar disorder (BD). We conducted a genome-wide association study (GWAS) and polygenic score analysis of TEM and tested its association with a subset of BD-I patients treated with SSRIs or SNRIs. Our results did not identify any genome-wide significant variants although, we found that a higher polygenic score (PGS) for antidepressant response in MDD was associated with higher odds of TEM in BD. Future studies with larger transdiagnostic cohorts treated with antidepressants are encouraged to identify a neurobiological mechanism associated with a spectrum of depression improvement (response- emergent mania).

Objectives Agitation is the most common behavioral symptom of Alzheimer disease (AD) affecting approximately 40% to 60% of the AD population, yet there are no Food and Drug Administration–approved therapies for the myriad of behavioral or psychological symptoms of dementia. There is growing evidence from naturalistic studies that electroconvulsive therapy (ECT) is a safe and effective treatment for agitation in AD patients who are refractory to pharmacotherapy and behavioral interventions. Despite the existing evidence, ECT remains underused because of stigma, lack of education, and concerns regarding adverse cognitive effects. Randomized controlled clinical trials of ECT are an opportunity to provide high-quality evidence of ECT as a safe and efficacious treatment for agitation in the AD population. We describe the methods for the Electroconvulsive Therapy in Alzheimer's Dementia study, which uses a novel, simulated ECT (S-ECT) control group to conduct a single-blind efficacy study of ECT for the treatment of agitation and aggression in individuals with moderate to severe AD. Methods We discuss the rationale, study design, methodology, ethical and practical challenges, and management strategies in using an S-ECT group as the comparator arm in this randomized controlled trial of ECT in AD-related treatment refractory agitation and aggression. Conclusions Validation of the safety and efficacy of ECT in patients with advanced AD with refractory agitation and aggression is necessary. This can be accomplished through creative formulation of S-ECT groups that effectively maintain the blind while providing scientific integrity.

AbstractBackgroundBipolar disorder (BD) and borderline personality disorder (BPD) share overlapping phenomenology and are frequently misdiagnosed. This study investigated the diagnostic accuracy of the Mood Disorder Questionnaire (MDQ) and McLean Screening Instrument for Borderline Personality Disorder (MSI) in a clinical inpatient setting and whether individual screening items could differentiate BD from BPD.Methods757 sequential inpatients admitted to a Mood Disorder Unit completed both the MDQ and MSI. Screen positive for the MDQ was defined as ≥7/13 symptoms endorsed with concurrence and at least moderate impact. Screen positive for the MSI was defined as a score of ≥7. The clinical discharge summary diagnosis completed by a board‐certified psychiatrist was used as the reference standard to identify concordance rates of a positive screen with clinical diagnosis. Individual items predicting one disorder and simultaneously predicting absence of other disorder by odds ratio (OR>and <1) were identified.ResultsBoth screening instruments were more specific than sensitive (MDQ 83.7%/ 67.8%, MSI 73.2% / 63.3%). MDQ individual items (elevated mood, grandiosity, increased energy, pressured speech, decreased need for sleep, hyperactivity) were significant predictors of BD diagnosis and non‐predictors of BPD diagnosis. Whereas MSI subitem, self‐harm behaviors/suicidal attempts predicted BPD in the absence of BD; distrust and irritability were additional predictors of BPD.ConclusionWhile this study is limited by the lack of structured diagnostic interview, these data provide differential symptoms to discriminate BD and BPD. Further work with larger datasets and more rigorous bioinformatics machine learning methodology is encouraged to continue to identify distinguishing features of these two disorders to guide diagnostic precision and subsequent treatment recommendations.