Editorial Message and Issue Highlights–Vol. 15, No. 5–6, May-June 2018

| May 1, 2018 | 0 Comments

Dear Colleagues:

Welcome to the May–June 2018 issue of Innovations in Clinical Neuroscience (ICNS). We start the issue with a timely review article by Touma and Scarff titled, “Valbenazine and Deutetrabenazine for Tardive Dyskinesia (TD).” Here, the authors discuss the two drugs, which were recently approved by the United States Food and Drug Administration (FDA) for the treatment of TD. The authors describe the drugs’ unique mechanisms of action as well as the evidence supporting their efficacy, tolerability, dosing, drug interactions, and precautions.

Next, in the article titled “Combination Phentermine–Topiramate Extended Release for the Treatment of Binge Eating Disorder: An Open-Label, Prospective Study,” Guerdjikova et al present preliminary data regarding the usefulness of the combination of phentermine and topiramate extended release (phentermine–topiramate [Qsymia®, Vivus, Inc.]) for treatment of binge eating disorder (BED) associated with obesity or overweight. The researchers report that phentermine–topiramate treatment was associated with significant reductions in weight, body mass index, binge eating episode frequency and measures of global clinical severity, eating disorder psychopathology, and obsessive-compulsive symptoms among their very small patient sample. The authors acknowledge that controlled studies with larger patient samples are needed to confirm these preliminary results.

Following this, Sheehan et al present data on the effects of lisdexamfetamine dimesylate (LDX [Vyvanse®, Shire US Inc.]) on functional impairment among adults with moderate-to-severe binge eating disorder (BED), which was an exploratory endpoint of two randomized, controlled Phase III trials studying the effect of LDX treatment on symptoms of moderate-to-severe BED. Using the Sheehan Disability Scale (SDS) to measure functional impairment, the authors reportedly observed significant reductions in SDS total score, SDS domain scores, and in the number of days of underproductivity while at work/school among study participants in the LDX group compared to placebo. The authors acknowledge several limitations to their study, including the lack of clinical validation of SDS in the assessment of functional disability among individuals with BED (though the SDS has been validated and used to assess functional disability in other patient populations).

Next, in a case report titled “Delirium and Psychotic Symptoms Associated with Hyperglycemia in a Patient with Poorly controlled Type 2 Diabetes Mellitus,” Lopes and Pereira describe a case of an elderly woman with no previous history of delirium or psychosis who presented with recently observed behavioral changes, including disorganization, confusion, agitation, irritability and impulsivity, insomnia, social isolation, and illogical thinking with delusional ideas of persecution. After thorough physical and biochemical examinations, the authors concluded that the exhibited symptoms were directly associated with hyperglycemia due to the patient’s poorly controlled Type 2 diabetes mellitus. The authors discuss differential diagnoses and treatment options, as well as the pathophysiological mechanisms that might lead to the onset of delirium in the context of hyperglycemia.

Following this, in the article title, “Development of a Behavioral Health Stigma Measure and Application of Machine Learning for Classification,” Tokmic et al present the results of their study that assessed the potential for using machine learning as a tool to analyze patterns of social stigma toward individuals with mental health disorders. Using self-reported data collected from 1,904 participants, the authors describe how a classification predictive model of stigma was designed using a decision tree as the data mining tool. The authors then evaluated the ability of the machine learning-based classification algorithm to accurately measure the presence of mental illness stigma among study participants. The authors report that sufficient inter-rater reliability with a predictive accuracy of 92.4 percent was achieved using their algorithm. They acknowledge several limitations to their work, including the lack of heterogeneity among their sample of participants. They propose that this tool could be used to track stigma over time, which might help healthcare decision-makers address social stigma and improve patient outcomes for those with mental illness.

Next, in the article, “Atrial Fibrillation and Injected Aripiprazole: A Case Report,” by  Stefatos et al, the authors describe the case of a middle-aged man with schizoaffective disorder who developed acute atrial fibrillation (AF) several days after an intramuscular injection of a large dose of long-acting aripiprazole after low oral doses had been well-tolerated. The authors discuss differential diagnoses, risk factors, and treatment options.

Finally, in the Risk Management article titled, “Lessons to Be Learned: A Review of Post-suicide Malpractice Lawsuits,” McNary describes risk management strategies to assist clinicians in providing good clinical care and guarding against the most frequent types of allegations, including those against clinicians following patient suicide or attempted suicide.

We hope you enjoy this very diverse issue of ICNS. As always, we welcome your feedback and submissions.


Amir Kalali, MD

Editor, Innovations in Clinical Neuroscience


Category: Current Issue, Editor's Message: Issue Highlights

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