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Objective: Patients receiving medication for opioid use disorder (MOUD) may continue using nonprescribed drugs or have trouble with medication adherence, and it is difficult to predict which patients will continue to do so. In this study, we develop and validate an automated risk-modeling framework to predict opioid abstinence and medication adherence at a patient's next attended appointment and evaluate the predictive performance of machine-learning algorithms versus logistic regression. Methods: Urine drug screen and attendance records from 40,005 appointments drawn from 2742 patients at a multilocation office-based MOUD program were used to train logistic regression, logistic ridge regression, and XGBoost models to predict a composite indicator of treatment adherence (opioid-negative and norbuprenorphine-positive urine, no evidence of urine adulteration) at next attended appointment. Results: The XGBoost model had similar accuracy and discriminative ability (accuracy, 88%; area under the receiver operating curve, 0.87) to the two logistic regression models (accuracy, 88%; area under the receiver operating curve, 0.87). The XGBoost model had nearly perfect calibration in independent validation data; the logistic and ridge regression models slightly overestimated adherence likelihood. Historical treatment adherence, attendance rate, and fentanyl-positive urine at current appointment were the strongest contributors to treatment adherence at next attended appointment. Discussion: There is a need for risk prediction tools to improve delivery of MOUD. This study presents an automated and portable risk-modeling framework to predict treatment adherence at each patient's next attended appointment. The XGBoost algorithm appears to provide similar classification accuracy to logistic regression models; however, XGBoost may offer improved calibration of risk estimates compared with logistic regression. [ABSTRACT FROM AUTHOR]

This study describes the characteristics of 67 young heroin users, interviewed using a semistructured qualitative questionnaire (QQ) as part of a larger study of 18- to 25-year-old heroin users seeking detoxification with buprenorphine at a drug treatment center in Baltimore. This new generation of heroin users has a different demographic profile compared to older heroin users in this area. Our data, supported by data from another clinic and from the Maryland State Alcohol and Drug Abuse Administration, seem to indicate that the younger heroin users in treatment settings are predominantly White, with a high proportion of women, often living in the suburbs. Based on responses to the QQ, all subjects initiated heroin use intranasally, usually in a group setting; 75% had subsequently gone on to use intravenously. The typical young heroin user in Baltimore Metropolitan area appears to be a young White man or woman from a middle/working-class background, with exposure to drug use among close contacts while growing up, experimenting with gateway drugs with peers before proceeding first to intranasal, and then intravenous heroin use, engaging in criminal activities to support the habit, repeatedly seeking help with assistance from family, but failing to sustain abstinence due to continued exposure to drug using peers and a poorly implemented plan of aftercare. Further research should focus on efforts to engage peer groups and families in order to improve treatment outcomes in young heroin users. Keywords: Heroin, young adult, qualitative characteristics, INTRODUCTION Heroin use among young people has been a growing cause for concern since the 1990s. According to the National Household Survey on Drug Abuse (NHSDA), there was a significant [...]

Eating disorders in British Asians were investigated using the Leicestershire Eating Disorders Service. The case records of 24 Asians living in Leicestershire was examined during the study period. Empirical results show that anorexia nervosa and bulimia nervosa are common among British Asians. The rate of presentation of people of Asian descent was lower than that of the white population. It was also found that Asian women with eating disorders were referred less often than their male counterparts.

Abstract Background Benzodiazepines (BZD) misuse is a serious public health problem, especially among opiate-dependent patients with anxiety enrolled in methadone program because it puts patients at higher risk of life-threatening multiple drug overdoses. Both elevated anxiety and BZD misuse increase the risk for ex-addicts to relapse. However, there is no recent study to assess how serious the problem is and what factors are associated with BZD misuse. This study estimates the prevalence of BZD misuse in a methadone program, and provides information on the characteristics of BZD users compared to non-users. Methods An anonymous survey was carried out at a methadone program in Baltimore, MD, and all patients were invited to participate through group meetings and fliers around the clinic on a voluntary basis. Of the 205 returned questionnaires, 194 were complete and entered into final data analysis. Those who completed the questionnaire were offered a $5 gift card as an appreciation. Results 47% of the respondents had a history of BZD use, and 39.8% used BZD without a prescription. Half of the BZD users (54%) started using BZD after entering the methadone program, and 61% of previous BZD users reported increased or resumed use after entering methadone program. Compared to the non-users, BZD users were more likely to be White, have prescribed medication for mental problems, have preexistent anxiety problems before opiate use, and had anxiety problems before entering methadone program. They reported more mental health problems in the past month, and had higher scores in anxiety state, depression and perceived stress (p < .05). Conclusions Important information on epidemiology of BZD misuse among methadone-maintenance patients suggests that most methadone programs do not address co-occurring anxiety problems, and methadone treatment may trigger onset or worsening of BZD misuse. Further study is needed to explore how to curb misuse and abuse of BZD in the addiction population, and provide effective treatments targeting simultaneously addiction symptoms, anxiety disorders and BZD misuse.

The cone electrode first developed by P.R. Kennedy paved headway in the area of cortical prostheses. While effective, to date, no optimization of the materials, length, diameter or controlling neurotrophic effects have been extensively quantified for such systems. This paper describes an in-vitro model system for the study of neurite outgrowth using PC-12 cells and an array of polyimide microtubes. Our aim is to obtain preliminary design specifications for the eventual optimization of in-vivo neurotrophic electrodes. We performed preliminary characterization of the number and average lengths of PC-12 neurites that penetrated into the tubes mounted within a standard Petri dish. To describe system performance, we observed an increase in the average number of neurites that grew into the tubes over a period of days. We also observed an increase in the average length of the neurites (with a 95% confidence) between day 3 and day 4 of between 14.97 microm and 62.27 microm. In addition, we measured a length change (with a 95% confidence) between day 4 and day 6 of 93.51 microm and 145.45 microm. These results will soon be augmented by quantification of neurites using a photo lithographically patterned glass microgroove system.