Search

Background: Opiate misuse has reached epidemic levels. Prevention efforts depend on distinguishing opiate users from abusers. The current study compared opioid users who died by natural cases, accidents, and suicide using psychological autopsy methods. Groups were compared on substance use characteristics, treatment history, experiences of negative life events, and circumstances at the time of death., Methods: Substance use and suicide risk were evaluated using psychological autopsy methods in 63 decedents with positive toxicology for opiates at death divided into three groups: adults dying by suicide (n = 19), accident (n = 19), and natural causes (n = 25). Groups were compared on several dependent measures, using chi-square analyses to examine categorical variables and one-way analyses of variance (ANOVA) to examine continuous variables., Results: Individuals who died by suicide were similar in many ways to adults who died by an accidental overdose. However, suicide completers were more likely to have struggled with severe depression, and previously attempted suicide, whereas the accidental overdose sample was more likely to display a chronic pattern of severe drug abuse., Conclusions: The current study helps to distinguish between opiate users who are at risk for death by an accidental or intentional overdose. In the ongoing opiate crisis, clinicians must understand the risk of overdose and the nuances of accidental behaviors compared to purposeful ones. Signs of suicidal planning, relevant psychopathology, and ongoing life stress may be useful points of intervention for stopping the increasing number of deaths among opiate users., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Background: Opioid Use Disorder (OUD), defined as a physical or psychological reliance on opioids, is a public health epidemic. Identifying adults likely to develop OUD can help public health officials in planning effective intervention strategies. The aim of this paper is to develop a machine learning approach to predict adults at risk for OUD and to identify interactions between various characteristics that increase this risk., Methods: In this approach, a data set was curated using the responses from the 2016 edition of the National Survey on Drug Use and Health (NSDUH). Using this data set, tree-based classifiers (decision tree and random forest) were trained, while employing downsampling to handle class imbalance. Predictions from the tree-based classifiers were also compared to the results from a logistic regression model. The results from the three classifiers were then interpreted synergistically to highlight individual characteristics and their interplay that pose a risk for OUD., Results: Random forest predicted adults at risk for OUD with remarkable accuracy, with the average area under the Receiver-Operating-Characteristics curve (AUC) over 0.89, even though the prevalence of OUD was only about 1 %. It showed a slight improvement over logistic regression. Logistic regression identified statistically significant characteristics, while random forest ranked the predictors in order of their contribution to OUD prediction. Early initiation of marijuana (before 18 years) emerged as the dominant predictor. Decision trees revealed that early marijuana initiation especially increased the risk if individuals: (i) were between 18-34 years of age, or (ii) had incomes less than $49,000, or (iii) were of Hispanic and White heritage, or (iv) were on probation, or (v) lived in neighborhoods with easy access to drugs., Conclusions: Machine learning can accurately predict adults at risk for OUD, and identify interactions among the factors that pronounce this risk. Curbing early initiation of marijuana may be an effective prevention strategy against opioid addiction, especially in high risk groups., Competing Interests: Declaration of Competing Interest The author does not have any conflicts of interest to report., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Objective: In 2017, an academic health center in Chicago launched the multidisciplinary Substance Use Intervention Team (SUIT) to address opioid misuse across 18 inpatient units and in a new outpatient addiction medicine clinic. This report assesses the first 5 months of implementation and associations with patient health and healthcare utilization., Methods: Patient demographic and screening data were extracted from the administrative data warehouse of the electronic health record (EHR) infrastructure. Distribution of sample characteristics for positive initial screens for opioid misuse was tested against those of all patients screened using a 2-tailed test of proportions (P < 0.05). A second analysis compared length of stay and 30-day readmissions within a cohort of patients with a secondary diagnosis of substance use disorder., Results: Between November, 2017 and March, 2018, 76% of 15,054 unique patients were screened, 578 had positive scores on the Alcohol Use Disorders Identification Test and Drug Abuse Screening Test, 131 had positive scores for opioid misuse, and 52 patients initiated medication treatment. Patients with a secondary diagnosis of substance use disorder who received a SUIT consult (n = 161), compared with those who did not (n = 612), had a shorter average length of stay (5.91 vs 6.73 days) and lower 30-day readmission rate (13.6% vs 15.7%)., Conclusion: Leveraging the EHR to conduct standardized screenings and treatment has helped identify an at-risk population-disproportionately younger, black, and male-and treat new cases of opioid and substance misuse. The intervention indicates trends toward a shortened length of stay, reduced 30-day readmissions, and has linked patients to outpatient care.

Background: Approaches are needed to better delineate the continuum of opioid misuse that occurs in hospitalized patients. A prognostic enrichment strategy with latent class analysis (LCA) may facilitate treatment strategies in subtypes of opioid misuse. We aim to identify subtypes of patients with opioid misuse and examine the distinctions between the subtypes by examining patient characteristics, topic models from clinical notes, and clinical outcomes., Methods: This was an observational study of inpatient hospitalizations at a tertiary care center between 2007 and 2017. Patients with opioid misuse were identified using an operational definition applied to all inpatient encounters. LCA with eight class-defining variables from the electronic health record (EHR) was applied to identify subtypes in the cohort of patients with opioid misuse. Comparisons between subtypes were made using the following approaches: (1) descriptive statistics on patient characteristics and healthcare utilization using EHR data and census-level data; (2) topic models with natural language processing (NLP) from clinical notes; (3) association with hospital outcomes., Findings: The analysis cohort was 6,224 (2.7% of all hospitalizations) patient encounters with opioid misuse with a data corpus of 422,147 clinical notes. LCA identified four subtypes with differing patient characteristics, topics from the clinical notes, and hospital outcomes. Class 1 was categorized by high hospital utilization with known opioid-related conditions (36.5%); Class 2 included patients with illicit use, low socioeconomic status, and psychoses (12.8%); Class 3 contained patients with alcohol use disorders with complications (39.2%); and class 4 consisted of those with low hospital utilization and incidental opioid misuse (11.5%). The following hospital outcomes were the highest for each subtype when compared against the other subtypes: readmission for class 1 (13.9% vs. 10.5%, p<0.01); discharge against medical advice for class 2 (12.3% vs. 5.3%, p<0.01); and in-hospital death for classes 3 and 4 (3.2% vs. 1.9%, p<0.01)., Conclusions: A 4-class latent model was the most parsimonious model that defined clinically interpretable and relevant subtypes for opioid misuse. Distinct subtypes were delineated after examining multiple domains of EHR data and applying methods in artificial intelligence. The approach with LCA and readily available class-defining substance use variables from the EHR may be applied as a prognostic enrichment strategy for targeted interventions., Competing Interests: The authors have declared that no competing interests exist.

Objective: Psychiatric comorbidities are highly prevalent among individuals affected by substance use disorders and those with non-substance-related addictive disorders such as gambling disorder. More recently, the frequent co-occurrence of substance use disorders and attention-deficit hyperactivity disorder (ADHD) has received particular attention. The aim of our study was to identify patterns of psychiatric comorbidity and to examine associations between patient group and ADHD status with class membership. Methods: Participants were patients with opioid use disorder enrolled in opioid maintenance treatment (OMT), either recruited from the community ( n  = 142; M age = 35.8 years; 38.7% female) or prison ( n  = 133; M age = 35.7 years; 21.8% female), and patients undergoing treatment for problem gambling (PrG; n  = 80; M age = 43.1 years; 20% female). To enable direct comparisons, the following instruments were applied: Mini International Neuropsychiatric Interview, Adult ADHD self-report scale, Wender Utah Rating Scale, and European Addiction Severity Index. We used a latent class analysis (LCA) to identify psychiatric comorbidity patterns and a multinomial logistic regression to examine associations between patient group, ADHD status, age, and gender with class membership. Results: The LCA resulted in a three-class solution: (1) a class of individuals with a relatively low probability of current psychiatric comorbidities, except for a high probability of substance use disorders; (2) a class with markedly increased probabilities of current and recurrent psychiatric comorbidities, especially for major depression; and (3) a class with very low probabilities of psychiatric comorbidities, except for moderate probabilities of substance use disorders and antisocial personality disorder. Both OMT patients recruited from the community and those in prison were less likely than PrG patients to be assigned to the most burdened class with respect to psychiatric comorbidity (class 2). Further, both individuals with ADHD in childhood and those with adult ADHD were more likely members of class 2. Conclusions: PrG patients seem to be at an even higher risk for psychiatric comorbidities compared to OMT patients. Raising awareness among practitioners for the high prevalence of psychiatric comorbidities among patients with gambling disorder and individuals with ADHD is crucial to initiate adequate treatment and to improve response.

Opioid analgesics, as commonly prescribed medications used for relieving pain in patients, are especially prevalent in US these years. However, an increasing amount of opioid misuse and abuse have caused lots of consequences. Researchers and clinicians have attempted to discover the factors leading to opioid long-term use, dependence, and abuse, but only limited incidents are understood from previous works. Motivated by recent successes of deep learning and the abundant amount of electronic health records, we apply state-of-the-art deep and recurrent neural network models on a dataset of more than one hundred thousand opioid users. Our models are shown to achieve robust and superior results on classifying opioid users, and are able to extract key factors for different opioid user groups. This work is also a good demonstration on adopting novel deep learning methods for real-world health care problems.

A panel of nine experts applied multi-criteria decision analysis (MCDA) to determine the relative overall harm to users and harms to others of street heroin (injected and smoked) and eleven non-medically used prescription opioids. The experts assessed harm scores for each of the 13 opioids on each of 20 harm criteria, weighted the criteria and explored the resulting weighted harm scores for each opioid. Both forms of heroin scored very high: overall harm score of 99 for injected heroin and 72 for smoked heroin on a scale of 0-100. The main feature that distinguishes both forms of street heroin use is that their harm to others is more than five times that of the other eleven opioids. The overall harm score of fentanyl (including injection of fentanyl extracted from patches) and diamorphine (medically prescribed form of heroin) was 54 and 51, respectively, whereas that of orally used opioids ranged from 32 (pethidine) to 11 (codeine-containing pharmaceuticals). Injected street heroin, fentanyl and diamorphine emerged as most harmful to users, with the latter two very low in harm to others. Pethidine, methadone, morphine and oxycodone are also low in harm to others, while moderate in harm to users. We conclude that the overall harms of non-medically used prescription opioids are less than half that of injected street heroin. These data may give a basis for precautionary regulatory measures that should be considered if the rising trend in non-medical use of prescription opioids were to become evident in the UK., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Background: Assessments of DSM-IV and DSM-5 criteria with sample populations of opioid users are limited. This study aimed to determine the number of latent classes in opioid users and assessment of the proposed revisions to the DSM-5 opioid use disorder (OUD) criteria., Methods: Data came from the 2011 Iranian National Mental Health Survey (IranMHS) on 7,886 participants aged 15-64 years living in Iran. We used the Composite International Diagnostic Interview (CIDI) version 2.1 in all respondents who indicated using opioids at least 5 times in the previous 12 months (n = 236)., Results: A three-class model provided the best fit of all the models tested. Classes showed a spectrum of severity that was compatible with the DSM-5 classification. 'Legal problems' and 'desire to cut down' showed poor discrimination between classes. The weighted prevalence of OUD using DSM-5 was 20.7% higher than with DSM-IV., Conclusions: RESULTS support the grouping based on severity of symptoms, combining abuse and dependence into a single diagnosis, omitting legal problems, and addition of craving as a new criterion., (© 2015 S. Karger AG, Basel.)

As the nontherapeutic use of prescription medications escalates, serious associated consequences have also increased. This makes it essential to estimate misuse, abuse, and related events (MAREs) in the development and postmarketing adverse event surveillance and monitoring of prescription drugs accurately. However, classifications and definitions to describe prescription drug MAREs differ depending on the purpose of the classification system, may apply to single events or ongoing patterns of inappropriate use, and are not standardized or systematically employed, thereby complicating the ability to assess MARE occurrence adequately. In a systematic review of existing prescription drug MARE terminology and definitions from consensus efforts, review articles, and major institutions and agencies, MARE terms were often defined inconsistently or idiosyncratically, or had definitions that overlapped with other MARE terms. The Analgesic, Anesthetic, and Addiction Clinical Trials, Translations, Innovations, Opportunities, and Networks (ACTTION) public-private partnership convened an expert panel to develop mutually exclusive and exhaustive consensus classifications and definitions of MAREs occurring in clinical trials of analgesic medications to increase accuracy and consistency in characterizing their occurrence and prevalence in clinical trials. The proposed ACTTION classifications and definitions are designed as a first step in a system to adjudicate MAREs that occur in analgesic clinical trials and postmarketing adverse event surveillance and monitoring, which can be used in conjunction with other methods of assessing a treatment's abuse potential., (Copyright © 2013 International Association for the Study of Pain. All rights reserved.)

Deaths involving prescription and illicit opioids are on the rise, which is an issue of increasing concern to health care professionals, policymakers, and the public. However, because medical examiners, coroners, and other practitioners do not use uniform standards and case definitions in classifying such drug-related deaths, the incidence and prevalence data are challenging to analyze and difficult to interpret, and thus form a poor basis for crafting effective responses. To address this situation, the Substance Abuse and Mental Health Services Administration convened a Consensus Panel and charged it with devising uniform standards and case definitions that can assist medical examiners, coroners, public health officials, and others in consistently distinguishing between deaths that were caused by a certain opioids and deaths in which such a drug was detected but was not a major cause of or contributor to the death. The consensus statement presented here incorporates the panel's recommendations in four key areas.

The aim was to analyze the relationship between Cloninger's dimensions and Personality Disorders (PD) (with DSM-IV criteria) in opiate dependents. The study was Cross-sectional. The sampling of 196 patients with opiate dependence was consecutive. All were receiving treatment in an inpatient detoxification unit. Cloninger's Temperament and Character Inventory (TCI), International Personality Disorders Examination (IPDE) and a Substance Use Questionnaire were used. Character's dimensions as Self-directness and Cooperation were related with PD when scored low. Opposite to Cloninger descriptions, high scores of Self-transcendence were related with presence of PD. Related to temperamental dimensions, cluster A was related with low scores of Reward Dependence (RD) and cluster C with high scores of Harm Avoidance (HA). Otherwise, in cluster B, while Borderline PD had high scores of Novelty Seeking (as high HA), the Antisocial PD only were related to low scores of RD. RD dimension seems useful to differ from presence or absence of Antisocial PD, also when alcohol consumption is considered. Cloninger's Model of Personality is useful in drug dependents for the definition of the different PD, as well as for probable PD's aggregation. This model also helps to create subtypes in opiate dependents as the antisocial or type II.

The purpose of this study was to advance our understanding of nonmedical use of prescription medications by identifying the distinguishing characteristics of 2 subtypes of adolescent nonmedical users of prescription opioids that have been previously described. A Web-based, self-administered survey was completed by 2,597 7th-12th grade students. Sensation-seeking nonmedical users were best characterized by rule breaking and aggressive behaviors and possible substance dependence. Medical users and nonmedical self-treating users were best characterized by somatic complaints, anxiety and depressive symptoms, and history of sexual victimization.

Aims: To identify and validate homogeneous subtypes of opioid use and related behaviors., Design: Family-based and case-control genetic studies of opioid and/or cocaine dependence., Settings: Clinical and general community samples from Connecticut, Massachusetts, Pennsylvania and South Carolina., Participants: A total of 4061 individuals (2003 individuals from 835 families and 2058 unrelated individuals) recruited to participate in genetic studies., Measurements: The computer-assisted Semi-Structured Assessment for Drug Dependence and Alcoholism (SSADDA) was used to assess participants' demographics, medical history, substance use behaviors and disorders and other psychiatric disorders., Findings: Five homogeneous subtypes were identified, which differed on opioid-related measures, demographics and prevalence rates of substance use and psychiatric disorders. Heritability estimates for the two most severely affected subtypes exceeded 0.60., Conclusions: An empirical approach based on opioid use and related behaviors can yield homogeneous subtypes that could be of value in gene finding for opioid dependence., (© 2011 The Authors, Addiction © 2011 Society for the Study of Addiction.)

Aims: To examine the structure of illicit opioid abuse and dependence within an opioid dependent sample and its relationship to other clinical variables., Design, Setting and Participants: A cross-sectional study of 1511 opioid dependent individuals recruited through opioid pharmacotherapy clinics in the Sydney area, Australia., Measurements: A face-to-face structured interview covering substance use and dependence, psychiatric history, child maltreatment, family background, adult violence and criminal history. Dimensional, latent class and factor mixture models were fit to the opioid abuse and dependence data. Classes were then compared on a range of demographic and clinical covariates., Findings: A two-class, one-factor model provided the best fit of all the models tested. The two classes differed with respect to endorsement probabilities on a range of abuse and dependence criteria, and also with respect to the odds of other drug dependence diagnoses, antisocial personality disorder and non-fatal opioid overdose. Within-class severity was associated with similar variables: other drug dependence, borderline personality disorder and opioid overdose., Conclusion: In an in-treatment, opioid-dependent sample, there appears to be two classes of individuals exhibiting distinct patterns of abuse and dependence criteria endorsement and to differ on externalizing but not internalizing disorders. This study provides preliminary evidence that the proposed DSM-V opioid use disorder distinction between moderate and severely dependent people is valid. Class one participants were not only more severely dependent, but had greater odds for opioid overdoses, other drug dependence and antisocial personality disorder., (© 2010 The Authors, Addiction © 2010 Society for the Study of Addiction.)

Background: For the emerging DSM-V, it has been recommended that dimensional and categorical methods be used simultaneously in diagnostic classification; however, little is known about this combined approach for abuse and dependence., Method: Using data (n=37 708) from the 2007 National Survey on Drug Use and Health (NSDUH), DSM-IV criteria for prescription opioid abuse and dependence among non-prescribed opioid users (n=3037) were examined using factor analysis (FA), latent class analysis (LCA, categorical), item response theory (IRT, dimensional), and factor mixture (hybrid) approaches., Results: A two-class factor mixture model (FMM) combining features of categorical latent classes and dimensional IRT estimates empirically fitted more parsimoniously to abuse and dependence criteria data than models from FA, LCA and IRT procedures respectively. This mixture model included a severely affected group (7%) with a comparatively moderate to high probability (0.32-0.88) of endorsing all abuse and dependence criteria items, and a less severely affected group (93%) with a low probability (0.003-0.16) of endorsing all criteria. The two empirically defined groups differed significantly in the pattern of non-prescribed opioid use, co-morbid major depression, and substance abuse treatment use., Conclusions: A factor mixture model integrating categorical and dimensional features of classification fits better to DSM-IV criteria for prescription opioid abuse and dependence in adults than a categorical or dimensional approach. Research is needed to examine the utility of this mixture classification for substance use disorders and treatment response.

Addiction is a feared consequence of long-term opioid treatment of chronic pain patients. The ICD-10 and DSM-IV diagnostic addiction criteria may not be appropriate in these patients. Therefore Portenoy's criteria (PC) were launched. The aim was to estimate the prevalence of addiction, to investigate whether PC were applicable and to compare these criteria with the ICD-10 criteria. The study was cross-sectional and included 253 patients with chronic pain at a tertiary pain centre. Patients were screened for addiction by a physician and a nurse. The addiction prevalence was 14.4% according to ICD-10 and 19.3% according to PC. A significant difference between the prevalence of addiction according to ICD-10 and to PC was found. The inter-rater reliability was 0.95 for ICD-10 and 0.93 for PC. The sensitivity of PC was 0.85 and the specificity was 0.96. According to PC patients classified as addicted were treated with significantly higher opioid doses, drank more alcohol, smoked more tobacco, used benzodiazepines and had higher levels of depression. According to ICD-10 patients classified as addicted used higher doses of opioids, drank more alcohol and had higher scores of anxiety and depression. High opioid doses, concomitant use of alcohol and younger age were risk factors. The risk profile for PC was different to ICD-10 by adding risk factors as concomitant use of benzodiazepines, having depression and low educational level. PC seems to be appropriate for diagnosing addiction in opioid treated pain patients and seems to be more sensitive and specific than ICD-10 criteria., (Copyright © 2010 European Federation of International Association for the Study of Pain Chapters. Published by Elsevier Ltd. All rights reserved.)

Unlabelled: Two strategies should greatly improve pain management while minimizing opioid abuse. The first strategy involves the systematic implementation in every clinical practice of "universal precautions," a set of procedures that help physicians implement opioid therapy in a safe and controlled manner. These procedures include: 1) carefully assessing the patient's risk for opioid abuse; 2) selecting the most appropriate opioid therapy; 3) regularly monitoring the patient to evaluate the efficacy and tolerability of the treatment and to detect possible aberrant behaviors; and 4) mapping out solutions if abuse and/or addiction is detected, or in case of treatment failure. The second strategy involves the use of opioid formulations designed to deter or prevent product tampering and abuse. Results of clinical trials of new formulations of existing opioids (including oxycodone, morphine, and hydromorphone) suggest the potential for reduced abuse liability and, if approved, will be evaluated after launch for reduced real-world abuse. Integration of these formulations in clinical practices based on universal precautions should help further minimize the risk of opioid abuse while fostering appropriate prescribing to patients with indications for opioid therapy., Perspective: Undertreated pain and prescription opioid abuse remain important public health problems. In the absence of strong empirical evidence, common sense dictates that a universal-precautions approach-a systematic and easily adopted process that clinicians can quickly put into practice-is advised to promote safe opioid prescribing. Abuse- and tamper-resistant opioid formulations are emerging tools that may enhance safe opioid prescribing; further research and postmarketing analysis will clarify their utility and role in clinical practice.

Most treatment studies of opioid-dependent populations have focused predominantly on heroin users, despite a recent increase in those dependent upon prescription opioids. A key methodological challenge involved in studying the latter group involves defining the population. Specifically, researchers must decide whether to include (1) concurrent heroin users and (2) individuals with pain. The multi-site Prescription Opioid Addiction Treatment Study is examining treatments for this population. This paper describes various inclusion criteria considered by the study team related to heroin use and pain. The goal was to recruit a distinct but generalizable population of individuals dependent upon prescription opioids. (Am J Addict 2010;00:1-6).

Objective: To present a critical appraisal of the present definitions of addiction-related terminology that appear in US laws and regulatory policies that apply to the prescription of controlled substances for pain management., Methods: To establish an appropriate context for existing policy definitions, a historical review was conducted of reports from the World Health Organization expert committees on addiction-related concepts, beginning in 1950. In addition, current World Health Organization and American Psychiatric Association diagnostic classification nomenclature were examined. Results from recent criteria-based evaluations of federal and state laws and regulatory policies containing addiction-related terminology also were referenced., Results: Numerous examples are provided to clarify how inaccurate understandings of the nature of addiction, which can be corroborated by archaic definitions in some states' laws, can impact treatment decisions and patient care. Finally, this article discusses terminological and treatment implications of such concepts as "risk mitigation" and "responsible prescribing", which are goals currently emphasized in the pain management field as principal means to reduce addiction to or abuse of prescription opioid medications., Discussion: Although notable improvement has been achieved, policy content in some states has not kept pace with advancements in medical and scientific knowledge about the interface between pain management and addictive disease. Effective translation of addiction-related concepts into clinical practice remains an important objective for promoting public health related to treating pain and reducing non-medical use of opioids.

This paper aimed to determine whether non-fatal opioid overdose and suicide attempts are distinct behaviours by examining the histories of 1500 opioid-dependent individuals. This paper utilised data collected as part of a large retrospective case-control study. Unintentional non-fatal opioid overdoses were more common than suicide attempts (58% vs. 32%). Overall, the correlates associated with a history of attempted suicide only and non-fatal opioid overdose only were different. Drug-related risk behaviours (including high impulsivity, injection of opioids, sedative dependence) were associated with non-fatal opioid overdose; and a history of mental disorders (depression, anxiety disorder, and screening positive for borderline personality disorder (BPD+) were associated with suicide attempts. Additionally, those who reported a history of both behaviours had a more severe clinical profile including excessive drug use, psychological disorders and childhood trauma. The study concluded that non-fatal opioid overdose and attempted suicide are distinct clinically significant problems that require different approaches for prevention. Additionally, if both behaviours are reported a thorough assessment of underlying comorbid problems should be initiated by treatment services.

Background: The intersection of pain, addiction and mental health has not been adequately described. We describe the roles of these three conditions in a chronic pain patient population using opioid analgesics. Aims were to improve our understanding of this population as well as to explore ways of identifying different types of patients., Methods: We conducted a retrospective cohort study in a large integrated group medical practice in Washington State with persons using opioids chronically (n=704). Patient classes were derived with latent class analysis using factors representing DSM-IV opioid abuse and dependence, opioid misuse, pain, anxiety and depression. Regression analyses explored the utility of automated and interview data to distinguish the empirically derived patient groups., Results: Three classes were identified: a Typical group, the substantial majority that had persistent, moderate mental health and pain symptoms; an Addictive Behaviors group with elevated mental health symptoms and opioid problems, but pain similar to the Typical class; and a Pain Dysfunction class with significantly higher pain interference as well as elevated mental health and opioid problems. Prescribed average daily dose of opioids was three times higher for those in the two atypical groups and was strongly associated with class membership after adjusting for other variables., Conclusion: We describe three distinct types of patient classes as well as data elements that could help identify the two atypical types. Further research is needed to confirm these findings and determine the utility of this approach in other clinical settings.

Objectives: This study describes the development of a systematic approach to the analysis of Internet chatter as a means of monitoring potentially abusable opioid analgesics., Methods: Message boards dedicated to drug abuse were selected using specific inclusion criteria. Threaded discussions containing 48,293 posts were captured. A coding system was created to compare content of posts related to 3 opioid analgesics: Kadian, Vicodin, and OxyContin., Results: The number of posts containing mentions of the target drugs were significantly different [OxyContin (1813)>Vicodin (940)>Kadian (27), P<0.001]. Analyses revealed that these differences were not simply a reflection of the availability of each product (ie, number of prescriptions written). Reliability tests indicated that the content coding system achieved good interrater reliability coefficients (average kappa across all categories=0.76, range=0.52 to 1.0). Content analysis of a sample of 234 randomly selected posts indicated that the proportion of Internet posts endorsing abuse of Kadian was statistically significantly less than OxyContin (45.5% vs. 68.4%, P=0.036, not adjusted for multiple comparisons)., Discussion: These results suggest that a systematic approach to postmarketing surveillance of Internet chatter related to pharmaceutical products is feasible and yields reliable information about the quantity of discussion of specific products and qualitative information regarding the nature of the discussions. Kadian was associated with fewer Internet mentions than either OxyContin or Vicodin. This investigation stands as a first attempt to establish systematic methods for conducting Internet surveillance.

To characterize sleep disorders in methadone maintenance treatment (MMT) patients, we evaluated sleep quality of 101 non-selective patients from our MMT clinic in Israel between July, 2003 and July, 2004 by using the self-report questionnaire Pittsburgh Sleep Quality Index (PSQI). Patients' urine tests were analyzed for methadone metabolite, opiates, benzodiazepine, cocaine, cannabis and amphetamines. Their urine results for drug abuse throughout the months prior to filling in the questionnaire and their maintenance methadone doses were recorded. Drug abuse was defined by at least one positive urine test. Methadone serum levels were available in 55 patients, assessed by Gas Chromatography Mass Spectroscopy. The patients' self-reported chronic pain questionnaires and their diagnosed psychiatric disorders were analyzed. Out of the 101 study patients, 78.2% were male, 52.5% had psychiatric disorders, 46.5% reported having chronic pain and 46.5% had positive urine for benzodiazepine. The mean daily methadone dose was 157+/-52.9 mg. The mean PSQI score was 9+/-4.8 (75.2% had scores >5 indicating "poor sleepers"). PSQI scores were higher in patients with positive urine for benzodiazepine, chronic pain and psychiatric disorders and they correlated with years of opiate abuse before admission to MMT, and with the methadone dose (r=0.48, p<0.0005). The latter two also correlated with each other. The PSQI was not correlated with duration in MMT, gender, age, abuse of opiates, cannabis or cocaine. We concluded that sleep disorders should be evaluated and treated among MMT patients, particularly in those with psychiatric disorders, benzodiazepine abuse, chronic pain and high methadone dose.

Objective: There are similarities between alcoholics and opioid addicts and an overlap between both diagnostic groups. We tested the hypothesis that the type I and II classification, well established in male alcoholism, could also be relevant in a population of male opioid addicts., Methods: A sample of 100 hospitalized adult opioid dependent men were studied with the help of an extended semi-structured clinical interview, considering four classification criteria sets devised by Cloninger et al. (1981, 1982), von Knorring et al. (1985, 1987), Buydens-Branchey et al. (1989) and Babor et al. (1992)., Results: The two types of classification could be confirmed with all four criteria sets. In at least three of four analyses, 52 patients were allocated to the same larger cluster C1, and 25 patients to a smaller cluster C2. These two groups were compared with each other with the help of the stepwise discriminant analysis. Seven variables were identified which excellently discriminate between the groups: The C2 patient is younger, has a history of therapy because of depression and a history of severe suicide attempts, also abuses benzodiazepines and becomes violent while intoxicated. His father suffers from alcoholism and received treatment because of depression. The C1 patient lacks these characteristics., Conclusions: The hypothesis was confirmed, showing that the two types of classification for male opioid addicts is feasible. A depressive type of male opioid dependent patient was identified. Early identification of patients of this type is clinically important.

This article discusses the implementation of the Drug Evaluation Network System (DENS) version of the Addiction Severity Index (ASI) among substance abuse treatment providers in Los Angeles County. Thirty-two trained and certified treatment professionals from 14 programs participated in focus group interviews about their use of and experiences with the ASI. All 14 programs were currently administering the ASI at the time of the study. Qualitative interviews revealed variation among the programs in terms of when staff administered the ASI and how they used it in clinical care. Although the ASI creates a comprehensive picture of substance-abusing patients and their functioning, the timing of its administration seems to significantly affect the usefulness of the information. The findings illustrate the importance of practicality, flexibility, and ongoing training for the successful implementation of evidence-based practices.

Problematic drug use has received considerable media attention over the past decade. This has raised awareness of the escalation of drug use as well as the complex issues that accompany it. According to the Audit Commission (2002), there were 250,000 known drug users in the UK in 2002 and only half were in treatment. This was considered to be a conservative estimate as not all drug users were willing or able to access treatment.

There is a relatively low prevalence of opioid use in Brazil, particularly involving the non-medical use of codeine and opiate-containing syrups. However, opioid dependence syndrome shows a significant total impact on mortality and morbidity. Over the past 20 years, scientific progress has changed our understanding of the nature of opioid addiction and its various possible treatments. Addiction is a chronic illness treatable if the treatment is well-delivered and tailored to the needs of the particular patient. There is indeed an array of treatments that can effectively reduce drug use, help manage drug cravings, prevent relapses and restore people to productive social functioning. The treatment of drug addiction will be part of long-term, medical, psychological, and social perspectives. This guideline aims at providing guidance to psychiatrists and other mental health professionals who care for patients with opioid dependence syndrome. It comments on the somatic and psychosocial treatment that is used for such patients, and reviews scientific evidences and their strength. Also, the essential historical, epidemiological and neurobiological aspects of opioid dependence are reviewed.

To characterize prescription opioid dependent patients in a methadone maintenance treatment (MMT) program, a detailed retrospective chart review of new admissions (1997-1999, n=178, mean age=34.5+/-0.7 years, 65% male) was conducted. At admission most patients (83%) had been using prescription opioids (+/-heroin). Four groups were identified: 24% had used prescription opioids only; 24% used prescription opioids initially and heroin later; 35% used heroin first and prescription opioids subsequently; and 17% had used heroin only (this group was significantly younger: mean age 26+/-1 years, P=0.0001). Subjects reported regular use of prescription opioids at higher than therapeutic dosages. For example, in the 'prescription opioid only' group the reported mean (+/-S.E.) number of codeine or oxycodone-containing tablets consumed daily was 23 (+/-6) tablets and 21 (+/-3) tablets, respectively. There were no significant differences found amongst the groups in measures of social stability. Those dependent on prescription opioids alone were less likely to use illicit non-opioid drugs or to be associated with injection drug use. Those that used prescription opioids only or initially were more likely to have ongoing pain problems and to be involved in psychiatric treatment. Further research is required to better elucidate the complex relationships between pain, mental health and addiction in order to develop optimal prevention and treatment strategies for prescription opioid dependence.

As a result of new federal regulations released in early 2001 that move the monitoring and evaluation of opioid treatment programs from a government regulation to an accreditation model, program staff members are now being challenged to develop performance measurement systems that improve care and service. Using measurement selection criteria is the first step in developing a performance measurement system as a component of an overall quality management (QM) strategy. Opioid treatment programs can "leapfrog" the development of such systems by using lessons learned from the healthcare quality industry. This article reviews performance measurement definitions, proposes performance measurement selection criteria, and makes a business case for Internet automation and accessibility. Performance measurement sets that are appropriate for opioid treatment programs are proposed, followed by a discussion on how performance measurement can be used within a comprehensive QM program. It is hoped that through development, adoption, and implementation of such a performance measurement program, treatment for clients and their families will continuously improve.

In a 5-year-follow-up study of 350 opiate addicts in contact with a drug help system in Hamburg, 272 clients (78%) were interviewed a second time after 1 year. The objective of the study was to examine the correlation between mental disorders and drug consumption and its relationship to clients' general life situation. In the majority of the opiate addicts, a pattern of polydrug consumption was observed, but the amount of drugs consumed was clearly lower after 1 year. In the initial survey, a mental disorder according to ICD-10 could be diagnosed for 55% of the sample. Among groups formed by the severity and course of mental disorders or their symptoms, a significant correlation was observed, particularly at the time of follow-up, between the extent of drug consumption and the course of the mental disorder. Other areas, like physical health or social problems/conflicts, were also related to comorbidity (i.e., heavy drug consumption and/or mental disorder). These interrelationships should be taken into account in treatment, care and guidance to increase the prospects for successful treatment.

We recently demonstrated a coupling between nervousness and pain sensitivity in healthy volunteers, and we defined a mean ratio of nervousness/log pain threshold of 1.95 +/- 1.47 for healthy humans. Because in another study former opiate addicts were found to exhibit a persistent opioid independent analgesia, we wondered whether nervousness is also changed in these patients, or if the balance between nervousness and pain sensitivity is altered. Forty unmedicated former opiate addicts during long-term rehabilitation and 40 age-matched control subjects were included in the study. The subjects rated their nervousness prior to a cold pressor test on a Visual Analog Scale. It turned out that the average nervousness rating was higher than in the control subjects and that a distinct subgroup of pain sensitive ex-addicts exhibited a higher ratio of nervousness vs. pain threshold. In this group the risk for relapse was three to four times higher than in the other ex-addicts.

This article used the diagnostic criteria of the Diagnostic and Statistical Manual-Fourth Edition (DSM-IV) to compare the validity of a qualitative and a quantitative model of the abuse-dependence distinction for different psychoactive substances in samples of drug users drawn from drug treatment inpatients, general psychiatric patients, and the community. The hypothesis that DSM-IV abuse criteria differ from dependence criteria in kind rather than degree (a qualitative model) was only occasionally supported by confirmatory factor analyses of DSM-IV diagnostic criteria, by patterns of correlations of the two kinds of criteria with Addiction Severity Score (ASI) composites and measures of frequency of substance abuse, and by concurrent/prognostic validity analyses. However, the findings were consistent with a quantitative model of the abuse-dependence distinction that posits that abuse is a mild form of dependence. Whether abuse and dependence categories of users were established from separate DSM-IV criteria for abuse and dependence or from scores from a severity-of-dependence scale based on the pooled DSM-IV dependence and abuse criteria, abusers generally used drugs less than users in the dependence category and reported less problems associated with substance abuse on the ASI.

The construct of illness severity serves many scientific and clinical functions. This study tested the performance as severity scales of three systems for diagnosing drug dependence--DSM-III, DSM-IV and ICD-10--in a multisite regional sample of 370 clinical subjects. Both lifetime and current severity of four drug problems--alcohol, cannabis, cocaine and opiate dependence--was studied in three stages: (a) item difficulty and internal consistency analysis; (b) probabilistic modeling of distribution behavior; and (c) concurrent validation against a set of independent measures. All three systems, for most drugs correlated with most test variables, had good to excellent concurrent validity. Unexpectedly, DSM-III showed in some instances better item behavior, composite score behavior and concurrent validity than the other systems, though DSM-IV and ICD-10 are based on slimmer generic algorithms, and may represent a good balance between simplicity and concurrent validity. Results suggest that the design of future diagnostic algorithms start at the item level and strive for moderate levels of both internal consistency and difficulty. Composite score distributions can then be modeled in field research, and necessary item corrections can be made before the algorithm is widely promulgated.

This paper focuses on the prevalence and profile of opiate use, primarily heroin, in the United States and Europe. Methods include representative population surveys, which understate prevalence, and targeted approaches, which reflect more problematic use. In the United States and Europe, the lifetime prevalence of opiate use reported in surveys remained stable over the 1980s (around 1%), though young adults report higher rates. Estimates for the early 1990s suggest that the prevalence of problematic heroin use in the United States was double the average for western Europe. However, in a few European countries prevalence is now approaching that of the United States. Rates in major cities are considerably higher, especially in the north-east and south-west of the United States. Higher prevalence is often, although not always, associated with socio-economic deprivation. An important trend away from injecting is observed, notably in some European countries. Heroin availability and use, as well as serious heroin-related consequences, are increasing again in many European countries after an apparent pause in the mid-1980s. They are also increasing in parts of the United States. Heroin remains a public health priority, especially among vulnerable populations, including young people in central and eastern Europe.

Despite the historical importance of tolerance and withdrawal in the substance abuse nomenclature, empirical evaluations of tolerance and withdrawal relative to other, non-physical, dependence criteria have been infrequent. Based on data from 521 subjects from a newly completed survey evaluating proposed options for DSM-IV substance use disorders, we found, first, across classes of drugs, requiring tolerance or withdrawal had little effect on rates of dependence, as most subjects who met dependence criteria for each drug class also reported tolerance. Second, tolerance and withdrawal did not emerge as superior to the other dependence criteria on several indicators of concurrent and predictive validity, including severity.

This report presents results of a field trial of Substance Use Disorders as defined by DSM-III-R, DSM-IV (proposed) and ICD-10. Diagnoses based on the three systems were derived from interviews using the Composite International Diagnostic Interview (CIDI) in a heterogeneous sample of 521 adults drawn from clinical and community settings. Two issues are addressed: (1) cross system agreement; and (2) syndrome coherence of proposed criterion sets for Substance Dependence in each of the three systems. Findings were as follows: (1) Cross system agreement for Dependence was generally high, especially between DSM-III-R and DSM-IV. (2) Cross system agreement was lower for DSM-III-R and DSM-IV Abuse and very low for DSM-IV Abuse and ICD-10 Harmful Use. (3) Agreement varied across drug categories with lowest DSM-III-R/DSM-IV agreement for alcohol abuse and DSM-IV/ICD-10 agreement for marijuana use disorders. (4) Overall prevalence differed for the three systems with DSM-IV yielding highest rates followed by DSM-III-R and ICD-10 in that order. (5) Factor analysis of Dependence criteria showed high loadings of all items on a single factor across the three diagnostic systems and for all categories of drugs. Implications for validity of the dependence syndrome construct and for revisions in DSM-IV are discussed.

Naltrexone is a pure narcotic antagonist with optimum pharmacologic properties for the long-term management of opiate addiction. The above study confirms the usefulness of naltrexone for the prevention of relapse in subjects who have been weaned from narcotics. However, the short follow up does not yet permit evaluation of its medium and long-term efficacy. The better course and outcome of treatment are significantly related to certain characteristics and types of addicts. It may be said that by assuring complete, albeit time-limited, remission the antagonist allows the addict to open a window through which to face the world, and offers the therapist the possibility to apply all the instruments at his disposal in an effective manner.

Attempts to classify drug addicts are divided into three main groups: (1) psychiatric classifications, (2) psychosocial classifications, and (3) classifications by pattern of abuse. An extensive literature review of the psychiatric classifications of narcotic addicts suggests that there is no one diagnosis that fits all narcotic addicts and that the importance of psychopathology in drug addiction has been exaggerated. It is concluded that theoretical psychiatric classifications of narcotic addicts have failed to stimulate empirical research and that empirical classifications have not demonstrated their utility for treatment and prognosis.

On the basis of structured interview data concerning their life-styles, behaviors, circumstances, and activities during their most recent periods of addiction, 460 male narcotic addicts (230 Black and 230 White) were empirically classified, or "typed," using factor and cluster analytic techniques in a multistage process. Mean factor score profiles for each of the eight types derived are presented, along with provisional labels and verbal descriptions. It is believed that this classification is descriptive of the major addict types to be encountered in a large urban population.

Attempts to classify drug addicts are divided into three main groups: (1) psychiatric classifications, (2) psychological classifications, and (3) classifications by pattern of abuse. An extensive literature review of the psychiatric classifications of narcotic addicts suggests that there is no one diagnosis that fits all narcotic addicts and that the importance of psychopathology in drug addiction has been exaggerated. It is concluded that theoretical psychiatric classifications of narcotic addicts have failed to stimulate empirical research and that empirical classifications have not demonstrated their utility for treatment and prognosis.

Recent research conducted by independent investigators concerning the relationship between crime and narcotic (primarily heroin) addiction has revealed a remarkable degree of consistency of findings across studies. The major conclusion supported by the majority of these studies is that narcotic addicts commit a vast amount of crime and that much of this is directly related to the need to purchase drugs. A large proportion of the crimes committed does not consist merely of drug sales or possession, but involves other criminal behaviors including serious crimes. The strongest evidence of a causal relationship between narcotic drug use and crime is derived from longitudinal studies in which the amount of crime committed during periods of active addiction far exceeds that committed during periods of nonaddiction. Much of this crime goes unreported, although addicts, under conditions of strict confidentiality, have provided information that permits realistic estimates of criminal activity. Use of this methodology has permitted the identification of different types of addicts, especially with respect to the amounts and types of crimes in which they are engaged. The implication of these findings is that although addicts as a group commit a great amount of crime, they cannot be regarded as a homogeneous class. Some addicts commit many crimes, regardless of current addiction status, whereas others commit relatively few, and these are obviously related to their need to purchase drugs. There is a discernible impact of treatment on narcotic drug use and criminality. Although the relationships between addict characteristics and treatment response have yet to be fully determined, extensive prior criminal involvement is associated with a negative outcome.