Prescription Trends of Psychotropics in Children and Adolescents with Autism Based on Nationwide Health Insurance Data.

Children with autism are often medicated to manage emotional and behavioral symptoms; yet, data on such pharmacotherapy is insufficient. In this study, we investigated the Korean National Health Insurance Claims Database (NHICD) information related to autism incidence and psychotropic medication use. From the 2010-2012 NHICD, we selected a total of 31,919,732 subjects under 19 years old. To examine the diagnostic incidence, we selected patients who had at least one medical claim containing an 10th revision of International Statistical Classification of Diseases and Related Health Problems (ICD-10) code for pervasive developmental disorder, F84, not diagnosed in the previous 360 days. Psychotropics were categorized into seven classes. Then, we analyzed the data to determine the mean annual diagnostic incidence and psychotropic prescription trends. Diagnostic incidence was 17,606 for the 3 years, with a mean annual incidence per 10,000 population of 5.52. Among them, 5,348 patients were prescribed psychotropics. Atypical antipsychotics were the most commonly used, followed by antidepressants. An older age, male sex, and the availability of medical aid were associated with a higher rate of prescription than observed for a younger age, female sex, and the availability of health insurance. Psychotropic drugs were used for less than one-third of patients newly diagnosed with autism, and prescription differed by sex and age. Increased diagnostic incidence is associated with an increased prescription of psychotropic drugs. Therefore, medication-related safety data and policies for psychotropic drugs in autism should be prepared.

Automatic stress-relieving music recommendation system based on photoplethysmography-derived heart rate variability analysis.

This paper presents an automatic stress-relieving music recommendation system (ASMRS) for individual music listeners. The ASMRS uses a portable, wireless photoplethysmography module with a finger-type sensor, and a program that translates heartbeat signals from the sensor to the stress index. The sympathovagal balance index (SVI) was calculated from heart rate variability to assess the user's stress levels while listening to music. Twenty-two healthy volunteers participated in the experiment. The results have shown that the participants' SVI values are highly correlated with their prespecified music preferences. The sensitivity and specificity of the favorable music classification also improved as the number of music repetitions increased to 20 times. Based on the SVI values, the system automatically recommends favorable music lists to relieve stress for individuals.

Clinical characteristics associated with different strengths of loudness dependence of auditory evoked potentials (LDAEP) in major depressive disorder.

Loudness dependence of auditory evoked potentials (LDAEP), also called as intensity dependence of auditory evoked potentials (IDAP), has been proposed as a potential marker for central serotonergic tone and has been noticed for its possible clinical implications in depression. However, its distributions in major depressive disorder (MDD) and factors affecting it are largely unknown. In this study, we examined its distribution and relationships with various demographic and clinical variables in MDD patients. In 143 MDD patients, the LDAEP was measured using five intensities of auditory stimulus. The influences of ten independent variables (age, gender, education years, marital status, psychiatric family history, age of onset, suicide attempt history, depression severity, later augmentation of mood stabilizer, and smoking status) on the LDAEP strength were examined using univariate analyses and data mining method. The mean (±S.D.) LDAEP was 0.90 (±0.73)µV/10dB (-0.78-3.83µV/10dB). Female gender, smoking, and being married were consistently associated with a weaker LDAEP. In the pathway model, sequential combination of being male, living alone, and older age predicted the strongest LDAEP, whereas female gender, older age, and smoking predicted the weakest LDAEP. These variables need to be considered when interpreting the LDAEP.