Comparative profiles of men and women with opioid dependence: results from a national multisite effectiveness trial.

BACKGROUND: Accumulating evidence indicates important gender differences in substance use disorders. Little is known, however, about gender differences and opioid use disorders. OBJECTIVES: To compare demographic characteristics, substance use severity, and other associated areas of functioning (as measured by the Addiction Severity Index-Lite (ASI-Lite)) among opioid-dependent men and women participating in a multisite effectiveness trial. METHODS: Participants were 892 adults screened for the National Institute on Drug Abuse Clinical Trials Network investigation of the effectiveness of two buprenorphine tapering schedules. RESULTS: The majority of men and women tested positive for oxycodone (68% and 65%, respectively) and morphine (89% each). More women than men tested positive for amphetamines (4% vs. 1%, p < .01), methamphetamine (11% vs. 4%, p < .01), and phencyclidine (8% vs. 4%, p = .02). More men than women tested positive for methadone (11% vs. 6%, p = .05) and marijuana (22% vs. 15%, p = .03). Craving for opioids was significantly higher among women (p < .01). Men evidenced higher alcohol (p < .01) and legal (p = .04) ASI composite scores, whereas women had higher drug (p < .01), employment (p < .01), family (p < .01), medical (p < .01), and psychiatric (p < .01) ASI composite scores. Women endorsed significantly more current and past medical problems. CONCLUSIONS: Important gender differences in the clinical profiles of opioid-dependent individuals were observed with regard to substance use severity, craving, medical conditions, and impairment in associated areas of functioning. The findings enhance understanding of the characteristics of treatment-seeking men and women with opioid dependence, and may be useful in improving identification, prevention, and treatment efforts for this challenging and growing population.

The maximum-likelihood strategy for determining transcranial magnetic stimulation motor threshold, using parameter estimation by sequential testing is faster than conventional methods with similar precision.

BACKGROUND: The resting motor threshold (rMT) is the basic unit of transcranial magnetic stimulation (TMS) dosing. Traditional methods of determining rMT involve finding a threshold of either visible movement or electromyography (EMG) motor-evoked potentials, commonly approached from above and below and then averaged. This time-consuming method typically uses many TMS pulses. Mathematical programs can efficiently determine a threshold by calculating the next intensity needed based on the prior results. Within our group of experienced TMS researchers, we sought to perform an illustrative study to compare one of these programs, the Maximum-Likelihood Strategy using Parameter Estimation by Sequential Testing (MLS-PEST) approach, to a modification of the traditional International Federation of Clinical Neurophysiology (IFCN) method for determining rMT in terms of the time and pulses required and the rMT value. METHODS: One subject participated in the study. Five researchers determined the same subject's rMT on 4 separate days-twice using EMG and twice using visible movement. On each visit, researchers used both the MLS-PEST and the IFCN methods, in alternating order. RESULTS: The MLS-PEST approach was significantly faster and used fewer pulses to estimate rMT. For EMG-determined rMT, MLS-PEST and IFCN derived similar rMT, whereas for visible movement MLS-PEST rMT was higher than for IFCN. CONCLUSIONS: The MLS-PEST algorithm is a promising alternative to traditional, time-consuming methods for determining rMT. Because the EMG-PEST method is totally automated, it may prove useful in studies using rMT as a quickly changing variable, as well as in large-scale clinical trials. Further work with PEST is warranted.