Three-month outcomes from a patient-centered program to treat opioid use disorder in Iowa, USA

Background: Opioid use disorder (OUD), a chronic disease, is a major public health problem. Despite availability of effective treatment, too few people receive it and treatment retention is low. Understanding barriers and facilitators of treatment access and retention is needed to improve outcomes for people with OUD. Objectives: To assess 3-month outcomes pilot data from a patient-centered OUD treatment program in Iowa, USA, that utilized flexible treatment requirements and prioritized engagement over compliance. Methods: Forty patients (62.5% female: mean age was 35.7 years, SD 9.5) receiving medication, either buprenorphine or naltrexone, to treat OUD were enrolled in an observational study. Patients could select or decline case management, counseling, and peer recovery groups. Substance use, risk and protective factors, and recovery capital were measured at intake and 3 months. Results: Most participants reported increased recovery capital. The median Assessment of Recovery Capital (ARC) score went from 37 at enrollment to 43 (p < 0.01). Illegal drug use decreased, with the median days using illegal drugs in the past month dropping from 10 to 0 (p < 0.001). Cravings improved: 29.2% reported no cravings at intake and 58.3% reported no cravings at 3 months (p < 0.001). Retention rate was 92.5% at 3 months. Retention rate for participants who were not on probation/parole was higher (96.9%) than for those on probation/parole (62.5%, p = 0.021). Conclusion: This study shows preliminary evidence that a care model based on easy and flexible access and strategies to improve treatment retention improves recovery capital, reduces illegal drug use and cravings, and retains people in treatment.Fil: Lynch, Alison C.. University of Iowa; Estados UnidosFil: Weber, Andrea N.. University of Iowa; Estados UnidosFil: Hedden, Suzy. University of Iowa; Estados UnidosFil: Sabbagh, Sayeh. University of Iowa; Estados UnidosFil: Arndt, Stephan. University of Iowa; Estados UnidosFil: Acion, Laura. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Calculo. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Calculo; Argentin

Treating alcohol use disorder in U.S. veterans: The role of traumatic brain injury

Objective: The authors examined the efficacy of valproate to reduce relapse to heavy drinking among veterans with alcohol use disorder (AUD) and neuropsychiatric comorbidities and whether antecedent traumatic brain injury (TBI) or posttraumatic stress disorder (PTSD) affected treatment response. Methods: Participants were male veterans 18–60 years old with an AUD and no other substance use besides nicotine or cannabis. Sixty-two patients were randomly assigned to receive either valproate or naltrexone. Participants were evaluated at baseline and followed weekly for 24 weeks. All participants received standardized psychosocial interventions as well as treatment for coexistent psychiatric conditions. Results: During the follow-up period, nine study subjects in the naltrexone group and 14 in the valproate group relapsed to heavy drinking, but the difference did not reach statistical significance. Participants with a history of moderate to severe TBI were more likely to relapse to heavy drinking compared with those with no TBI (hazard ratio=4.834, 95% CI=1.103–21.194, p=0.033). PTSD status did not significantly affect outcome. Conclusions: Intensive outpatient programs are efficacious alternatives to treat AUD in veterans, although the role of pharmacological treatment is not completely elucidated. Glutamatergic agents appear to be less effective than opiate antagonists to prevent relapse to heavy drinking and to increase cumulative abstinence. Future studies should examine novel pharmacological and nonpharmacological options.Fil: Jorge, Ricardo E.. Baylor College of Medicine;Fil: Li, Ruosha. Baylor College of Medicine;Fil: Liu, Xiangyu. Baylor College of Medicine;Fil: McGavin, Jill K.. Baylor College of Medicine;Fil: Shorter, Daryl I.. Baylor College of Medicine;Fil: Acion, Laura. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Calculo. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Calculo; ArgentinaFil: Arndt, Stephan. University of Iowa; Estados Unido

Mechanisms of Alcohol Addiction: Bridging Human and Animal Studies

Aim: The purpose of this brief narrative review is to address the complexities and benefits of extending animal alcohol addiction research to the human domain, emphasizing Allostasis and Incentive Sensitization, two models that inform many pre-clinical and clinical studies. Methods: The work reviewed includes a range of approaches, including: a) animal and human studies that target the biology of craving and compulsive consumption; b) human investigations that utilize alcohol self-administration and alcohol challenge paradigms, in some cases across 10 years; c) questionnaires that document changes in the positive and negative reinforcing effects of alcohol with increasing severity of addiction; and d) genomic structural equation modeling based on data from animal and human studies. Results: Several general themes emerge from specific study findings. First, positive reinforcement is characteristic of early stage addiction and sometimes diminishes with increasing severity, consistent with both Allostasis and Incentive Sensitization. Second, evidence is less consistent for the predominance of negative reinforcement in later stages of addiction, a key tenant of Allostasis. Finally, there are important individual differences in motivation to drink at a given point in time as well as person-specific change patterns across time. Conclusions: Key constructs of addiction, like stage and reinforcement, are by necessity operationalized differently in animal and human studies. Similarly, testing the validity of addiction models requires different strategies by the two research domains. Although such differences are challenging, they are not insurmountable, and there is much to be gained in understanding and treating addiction by combining pre-clinical and clinical approaches.Fil: Kramer, John. University of Iowa; Estados UnidosFil: Dick, Danielle M.. University of Virginia; Estados UnidosFil: King, Andrea. University of Chicago; Estados UnidosFil: Ray, Lara A.. University of California at Los Angeles; Estados UnidosFil: Sher, Kenneth J.. University of Missouri; Estados UnidosFil: Vena, Ashley. University of Chicago; Estados UnidosFil: Vendruscolo, Leandro F.. National Institutes of Health; Estados UnidosFil: Acion, Laura. University of Iowa; Estados Unidos. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Calculo. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Calculo; Argentin

Development of Alcohol Use Disorder as a Function of Age, Severity, and Comorbidity with Externalizing and Internalizing Disorders in a Young Adult Cohort

Background: As part of the ongoing Collaborative Study of the Genetics of Alcoholism, we performed a longitudinal study of a high risk cohort of adolescents/young adults from families with a proband with an alcohol use disorder, along with a comparison group of age-matched controls. The intent was to compare the development of alcohol problems in subjects at risk with and without comorbid externalizing and internalizing psychiatric disorders. Methods: Subjects (N = 3286) were assessed with a structured psychiatric interview at 2 year intervals over 10 years (2004–2017). The age range at baseline was 12–21. Results: Subjects with externalizing disorders (with or without accompanying internalizing disorders) were at increased risk for the onset of an alcohol use disorder during the observation period. Subjects with internalizing disorders were at greater risk than those without comorbid disorders for onset of a moderate or severe alcohol use disorder. The statistical effect of comorbid disorders was greater in subjects with more severe alcohol use disorders. The developmental trajectory of drinking milestones and alcohol use disorders was also accelerated in those with more severe disorders. Conclusions: These results may be useful for counseling of subjects at risk who present for clinical care, especially those subjects manifesting externalizing and internalizing disorders in the context of a positive family history of an alcohol use disorder. We confirm and extend findings that drinking problems in subjects at greatest risk will begin in early adolescence

A GABRA2 Polymorphism Improves a Model for Prediction of Drinking Initiation

Background Survival analysis was used to explore the addition of a single nucleotide polymorphism (SNP) and covariates (sex, interview age, and ancestry) on a previously published model's ability to predict onset of drinking. A SNP variant of rs279871, in the chromosome 4 gene encoding gamma-aminobutyric acid receptor (GABRA2), was selected due to its associations with alcoholism in young adults and with behaviors that increased risk for early drinking. Methods A subsample of 674 adolescents (ages 14–17) participating in the Collaborative Study on the Genetics of Alcoholism (COGA) was examined using a previously derived Cox proportional hazards model containing: 1) number of non-drinking related conduct disorder (CD) symptoms, 2) membership in a high-risk alcohol-dependent (AD) family, 3) most best friends drank (MBFD), 4) Achenbach Youth Self Report (YSR) externalizing score, and 5) YSR social problems score. The above covariates along with the SNP variant of GABRA2, rs279871, were added to this model. Five new prototype models were examined. The most parsimonious model was chosen based on likelihood ratio tests and model fit statistics. Results The final model contained four of the five original predictors (YSR social problems score was no longer significant and hence dropped from subsequent models), the three covariates, and a recessive GABRA2 rs279871 TT genotype (two copies of the high-risk allele containing thymine). The model indicated that adolescents with the high-risk TT genotype were more likely to begin drinking than those without this genotype. Conclusions The joint effect of the gene (rs279871 TT genotype) and environment (MBFD) on adolescent alcohol initiation is additive, but not interactive, after controlling for behavior problems (CD and YSR externalizing score). This suggests that the impact of the high-risk TT genotype on the onset of drinking is affected by controlling for peer drinking and does not include genotype-by-environment interactions

Density and Dichotomous Family History Measures of Alcohol Use Disorder as Predictors of Behavioral and Neural Phenotypes: A Comparative Study Across Gender and Race/Ethnicity

Background: Family history (FH) is an important risk factor for the development of alcohol use disorder (AUD). A variety of dichotomous and density measures of FH have been used to predict alcohol outcomes; yet, a systematic comparison of these FH measures is lacking. We compared 4 density and 4 commonly used dichotomous FH measures and examined variations by gender and race/ethnicity in their associations with age of onset of regular drinking, parietal P3 amplitude to visual target, and likelihood of developing AUD. Methods: Data from the Collaborative Study on the Genetics of Alcoholism (COGA) were utilized to compute the density and dichotomous measures. Only subjects and their family members with DSM-5 AUD diagnostic information obtained through direct interviews using the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA) were included in the study. Area under receiver operating characteristic curves were used to compare the diagnostic accuracy of FH measures at classifying DSM-5 AUD diagnosis. Logistic and linear regression models were used to examine associations of FH measures with alcohol outcomes. Results: Density measures had greater diagnostic accuracy at classifying AUD diagnosis, whereas dichotomous measures presented diagnostic accuracy closer to random chance. Both dichotomous and density measures were significantly associated with likelihood of AUD, early onset of regular drinking, and low parietal P3 amplitude, but density measures presented consistently more robust associations. Further, variations in these associations were observed such that among males (vs. females) and Whites (vs. Blacks), associations of alcohol outcomes with density (vs. dichotomous) measures were greater in magnitude. Conclusions: Density (vs. dichotomous) measures seem to present more robust associations with alcohol outcomes. However, associations of dichotomous and density FH measures with different alcohol outcomes (behavioral vs. neural) varied across gender and race/ethnicity. These findings have great applicability for alcohol research examining FH of AUD

Common Limitations of Image Processing Metrics:A Picture Story

While the importance of automatic image analysis is continuously increasing, recent meta-research revealed major flaws with respect to algorithm validation. Performance metrics are particularly key for meaningful, objective, and transparent performance assessment and validation of the used automatic algorithms, but relatively little attention has been given to the practical pitfalls when using specific metrics for a given image analysis task. These are typically related to (1) the disregard of inherent metric properties, such as the behaviour in the presence of class imbalance or small target structures, (2) the disregard of inherent data set properties, such as the non-independence of the test cases, and (3) the disregard of the actual biomedical domain interest that the metrics should reflect. This living dynamically document has the purpose to illustrate important limitations of performance metrics commonly applied in the field of image analysis. In this context, it focuses on biomedical image analysis problems that can be phrased as image-level classification, semantic segmentation, instance segmentation, or object detection task. The current version is based on a Delphi process on metrics conducted by an international consortium of image analysis experts from more than 60 institutions worldwide.Comment: This is a dynamic paper on limitations of commonly used metrics. The current version discusses metrics for image-level classification, semantic segmentation, object detection and instance segmentation. For missing use cases, comments or questions, please contact [email protected] or [email protected]. Substantial contributions to this document will be acknowledged with a co-authorshi

Understanding metric-related pitfalls in image analysis validation

Validation metrics are key for the reliable tracking of scientific progress and for bridging the current chasm between artificial intelligence (AI) research and its translation into practice. However, increasing evidence shows that particularly in image analysis, metrics are often chosen inadequately in relation to the underlying research problem. This could be attributed to a lack of accessibility of metric-related knowledge: While taking into account the individual strengths, weaknesses, and limitations of validation metrics is a critical prerequisite to making educated choices, the relevant knowledge is currently scattered and poorly accessible to individual researchers. Based on a multi-stage Delphi process conducted by a multidisciplinary expert consortium as well as extensive community feedback, the present work provides the first reliable and comprehensive common point of access to information on pitfalls related to validation metrics in image analysis. Focusing on biomedical image analysis but with the potential of transfer to other fields, the addressed pitfalls generalize across application domains and are categorized according to a newly created, domain-agnostic taxonomy. To facilitate comprehension, illustrations and specific examples accompany each pitfall. As a structured body of information accessible to researchers of all levels of expertise, this work enhances global comprehension of a key topic in image analysis validation.Comment: Shared first authors: Annika Reinke, Minu D. Tizabi; shared senior authors: Paul F. J\"ager, Lena Maier-Hei