Clinical, genomic, and neurophysiological correlates of lifetime suicide attempts among individuals with an alcohol use disorder

Research has identified clinical, genomic, and neurophysiological markers associated with suicide attempts (SA) among individuals with psychiatric illness. However, there is limited research among those with an alcohol use disorder (AUD), despite their disproportionately higher rates of SA. We examined lifetime SA in 4,068 individuals with DSM-IV alcohol dependence from the Collaborative Study on the Genetics of Alcoholism (23% lifetime suicide attempt; 53% female; mean age: 38). Within participants with an AUD diagnosis, we explored risk across other clinical conditions, polygenic scores (PGS) for comorbid psychiatric problems, and neurocognitive functioning for lifetime suicide attempt. Participants with an AUD who had attempted suicide had greater rates of trauma exposure, major depressive disorder, post-traumatic stress disorder, and other substance use disorders compared to those who had not attempted suicide. Polygenic scores for suicide attempt, depression, and PTSD were associated with reporting a suicide attempt (ORs = 1.22 - 1.44). Participants who reported a SA also had decreased right hemispheric frontal-parietal theta and decreased interhemispheric temporal-parietal alpha electroencephalogram resting-state coherences relative to those who did not, but differences were small. Overall, individuals with an AUD who report a lifetime suicide attempt appear to experience greater levels of trauma, have more severe comorbidities, and carry polygenic risk for a variety of psychiatric problems. Our results demonstrate the need to further investigate suicide attempts in the presence of substance use disorders.

Clinical, genomic, and neurophysiological correlates of lifetime suicide attempts among individuals with alcohol dependence

Research has identified clinical, genomic, and neurophysiological markers associated with suicide attempts (SA) among individuals with psychiatric illness. However, there is limited research among those with an alcohol use disorder (AUD), despite their disproportionately higher rates of SA. We examined lifetime SA in 4,068 individuals with DSM-IV alcohol dependence from the Collaborative Study on the Genetics of Alcoholism (23% lifetime suicide attempt; 53% female; 17% Admixed African American ancestries; mean age: 38). We 1) conducted a genome-wide association study (GWAS) of SA and performed downstream analyses to determine whether we could identify specific biological pathways of risk, and 2) explored risk in aggregate across other clinical conditions, polygenic scores (PGS) for comorbid psychiatric problems, and neurocognitive functioning between those with AD who have and have not reported a lifetime suicide attempt. The GWAS and downstream analyses did not produce any significant associations. Participants with an AUD who had attempted suicide had greater rates of trauma exposure, major depressive disorder, post-traumatic stress disorder, and other substance use disorders compared to those who had not attempted suicide. Polygenic scores for suicide attempt, depression, and PTSD were associated with reporting a suicide attempt (ORs = 1.22-1.44). Participants who reported a SA also had decreased right hemispheric frontal-parietal theta and decreased interhemispheric temporal-parietal alpha electroencephalogram resting-state coherences relative to those who did not, but differences were small. Overall, individuals with alcohol dependence who report SA appear to experience a variety of severe comorbidities and elevated polygenic risk for SA. Our results demonstrate the need to further investigate suicide attempts in the presence of substance use disorders.

Understanding metric-related pitfalls in image analysis validation

Validation metrics are key for tracking scientific progress and bridging the current chasm between artificial intelligence research and its translation into practice. However, increasing evidence shows that, particularly in image analysis, metrics are often chosen inadequately. Although 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 multistage Delphi process conducted by a multidisciplinary expert consortium as well as extensive community feedback, the present work provides a reliable and comprehensive common point of access to information on pitfalls related to validation metrics in image analysis. Although focused on biomedical image analysis, the addressed pitfalls generalize across application domains and are categorized according to a newly created, domain-agnostic taxonomy. The work serves to enhance global comprehension of a key topic in image analysis validation.

Metrics reloaded: recommendations for image analysis validation

Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. In biomedical image analysis, chosen performance metrics often do not reflect the domain interest, and thus fail to adequately measure scientific progress and hinder translation of ML techniques into practice. To overcome this, we created Metrics Reloaded, a comprehensive framework guiding researchers in the problem-aware selection of metrics. Developed by a large international consortium in a multistage Delphi process, it is based on the novel concept of a problem fingerprint-a structured representation of the given problem that captures all aspects that are relevant for metric selection, from the domain interest to the properties of the target structure(s), dataset and algorithm output. On the basis of the problem fingerprint, users are guided through the process of choosing and applying appropriate validation metrics while being made aware of potential pitfalls. Metrics Reloaded targets image analysis problems that can be interpreted as classification tasks at image, object or pixel level, namely image-level classification, object detection, semantic segmentation and instance segmentation tasks. To improve the user experience, we implemented the framework in the Metrics Reloaded online tool. Following the convergence of ML methodology across application domains, Metrics Reloaded fosters the convergence of validation methodology. Its applicability is demonstrated for various biomedical use cases.

Exclusion of the non-English-speaking world from the scientific literature: Recommendations for change for addiction journals and publishers

Background: While English is only the native language of 7.3% of the world's population and less than 20% can speak the language, nearly 75% of all scientific publications are English. Aim: To describe how and why scientific contributions from the non-English-speaking world have been excluded from addiction literature, and put forward suggestions for making this literature more accessible to the non-English-speaking population. Methods: A working group of the International Society of Addiction Journal Editors (ISAJE) conducted an iterative review of issues related to scientific publishing from the non-English-speaking world. Findings: We discuss several issues stemming from the predominance of English in the scientific addiction literature, including historical drivers, why this matters, and proposed solutions, focusing on the increased availability of translation services. Conclusion: The addition of non-English-speaking authors, editorial team members, and journals will increase the value, impact, and transparency of research findings and increase the accountability and inclusivity of scientific publications.

Services Available at United States Addiction Treatment Facilities That Offer Medications versus Behavioral Treatment Only: A Cross-Sectional, Observational Analysis

Purpose

Substance use disorders (SUDs) are widespread and cause significant morbidity and mortality, yet most people in the United States with a SUD do not receive treatment. Recommendations call for widespread use of pharmacotherapy, including medications for opioid use disorder (MOUD). However, many facilities do not offer a full array of medication treatments. This study aims to characterize programs that do and do not offer pharmacotherapy as part of addiction treatment services. We hypothesized that the availability of pharmacotherapy would predict the existence of other recommended components of treatment.

Patients and Methods

We analyzed characteristics regarding treatment facilities (n = 15,782) recorded by the 2019 National Survey of Substance Abuse Treatment Services (N-SSATS) to determine how many SUD treatment facilities offer any pharmacotherapy. We compared facilities that offer any pharmacotherapy to facilities that offer none.

Results

We found that 65% of SUD treatment facilities that responded to the N-SSATS survey provided at least one pharmacotherapy, while 35% of SUD treatment facilities did not. The facilities that provided at least one pharmacotherapy offered, on average, 6 additional treatment options (Cohen’s d = 0.87; 95% CI: 0.84–0.91). Psychiatric medications were the most commonly available pharmacotherapy, followed by buprenorphine/naloxone and naltrexone.

Conclusion

These results support that pharmacotherapy availability, such as MOUD, at SUD treatment facilities is associated with an increased number of recommended treatment components. Since MOUD has been shown elsewhere to reduce mortality for people with OUD, it should be universally available at SUD treatment facilities. Further efforts are needed to make pharmacotherapy more widely available.

Practical foundations of machine learning for addiction research. Part II. Workflow and use cases

In a continuum with applied statistics, machine learning offers a wide variety of tools to explore, analyze, and understand addiction data. These tools include algorithms that can leverage useful information from data to build models; these models can solve particular tasks to answer addiction scientific questions. In this second part of a two-part review on machine learning, we explain how to apply machine learning methods to addiction research. Like other analytical tools, machine learning methods require a careful implementation to carry out a reproducible and transparent research process with reliable results. This review describes a workflow to guide the application of machine learning in addiction research, detailing study design, data collection, data pre-processing, modeling, and results communication. How to train, validate, and test a model, detect and characterize overfitting, and determine an adequate sample size are some of the key issues when applying machine learning. We also illustrate the process and particular nuances with examples of how researchers in addiction have applied machine learning techniques with different goals, study designs, or data sources as well as explain the main limitations of machine learning approaches and how to best address them. A good use of machine learning enriches the addiction research toolkit.

Practical foundations of machine learning for addiction research. Part I. Methods and techniques

Machine learning assembles a broad set of methods and techniques to solve a wide range of problems, such as identifying individuals with substance use disorders (SUD), finding patterns in neuroimages, understanding SUD prognostic factors and their association, or determining addiction genetic underpinnings. However, the addiction research field underuses machine learning. This two-part narrative review focuses on machine learning tools and concepts, providing an introductory insight into their capabilities to facilitate their understanding and acquisition by addiction researchers. This first part presents supervised and unsupervised methods such as linear models, naive Bayes, support vector machines, artificial neural networks, and k-means. We illustrate each technique with examples of its use in current addiction research. We also present some open-source programming tools and methodological good practices that facilitate using these techniques. Throughout this work, we emphasize a continuum between applied statistics and machine learning, we show their commonalities, and provide sources for further reading to deepen the understanding of these methods. This two-part review is a primer for the next generation of addiction researchers incorporating machine learning in their projects. Researchers will find a bridge between applied statistics and machine learning, ways to expand their analytical toolkit, recommendations to incorporate well-established good practices in addiction data analysis (e.g., stating the rationale for using newer analytical tools, calculating sample size, improving reproducibility), and the vocabulary to enhance collaboration between researchers who do not conduct data analyses and those who do.

Substance Use in Pregnancy: Identifying Stigma and Improving Care

This review examines the impact of stigma on pregnant people who use substances. Stigma towards people who use drugs is pervasive and negatively impacts the care of substance-using people by characterizing addiction as a weakness and fostering beliefs that undermine the personal resources needed to access treatment and recover from addiction, including self-efficacy, help seeking and belief that they deserve care. Stigma acts on multiple levels by blaming people for having a problem and then making it difficult for them to get help, but in spite of this, most pregnant people who use substances reduce or stop using when they learn they are pregnant. Language, beliefs about gender roles, and attitudes regarding fitness for parenting are social factors that can express and perpetuate stigma while facilitating punitive rather than therapeutic approaches. Because of stigmatizing attitudes that a person who uses substances is unfit to parent, pregnant people who use substances are at heightened risk of being screened for substance use, referred to child welfare services, and having their parental rights taken away; these outcomes are even more likely for people of color. Various treatment options can successfully support recovery in substance-using pregnant populations, but treatment is underutilized in all populations including pregnant people, and more knowledge is needed on how to sustain engagement in treatment and recovery activities. To combat stigma when working with substance-using pregnant people throughout the peripartum period, caregivers should utilize a trauma-informed approach that incorporates harm reduction and motivational interviewing with a focus on building trust, enhancing self-efficacy, and strengthening the personal skills and resources needed to optimize health of the parent-baby dyad.

Associations between Suicidal Thoughts and Behaviors and Genetic Liability for Cognitive Performance, Depression, and Risk-Taking in a High-Risk Sample

Background

Suicidal thoughts and behaviors (STBs) and nonsuicidal self-injury (NSSI) behaviors are moderately heritable and may reflect an underlying predisposition to depression, impulsivity, and cognitive vulnerabilities to varying degrees.

Objectives

We aimed to estimate the degrees of association between genetic liability to depression, impulsivity, and cognitive performance and STBs and NSSI in a high-risk sample.

Methods

We used data on 7,482 individuals of European ancestry and 3,359 individuals of African ancestry from the Collaborative Study on the Genetics of Alcoholism to examine the links between polygenic scores (PGSs) for depression, impulsivity/risk-taking, and cognitive performance with 3 self-reported indices of STBs (suicidal ideation, persistent suicidal ideation defined as ideation occurring on at least 7 consecutive days, and suicide attempt) and with NSSI.

Results

The PGS for depression was significantly associated with all 4 primary self-harm measures, explaining 0.6-2.5% of the variance. The PGS for risk-taking behaviors was also associated with all 4 self-harm behaviors in baseline models, but was no longer associated after controlling for a lifetime measure of DSM-IV alcohol dependence and abuse symptom counts. Polygenic predisposition for cognitive performance was negatively associated with suicide attempts (q = 3.8e-4) but was not significantly associated with suicidal ideation nor NSSI. We did not find any significant associations in the African ancestry subset, likely due to smaller sample sizes.

Conclusions

Our results encourage the study of STB as transdiagnostic outcomes that show genetic overlap with a range of risk factors.

Polygenic contributions to alcohol use and alcohol use disorders across population-based and clinically ascertained samples

BACKGROUND

Studies suggest that alcohol consumption and alcohol use disorders have distinct genetic backgrounds.

METHODS

We examined whether polygenic risk scores (PRS) for consumption and problem subscales of the Alcohol Use Disorders Identification Test (AUDIT-C, AUDIT-P) in the UK Biobank (UKB; N = 121 630) correlate with alcohol outcomes in four independent samples: an ascertained cohort, the Collaborative Study on the Genetics of Alcoholism (COGA; N = 6850), and population-based cohorts: Avon Longitudinal Study of Parents and Children (ALSPAC; N = 5911), Generation Scotland (GS; N = 17 461), and an independent subset of UKB (N = 245 947). Regression models and survival analyses tested whether the PRS were associated with the alcohol-related outcomes.

RESULTS

In COGA, AUDIT-P PRS was associated with alcohol dependence, AUD symptom count, maximum drinks (R2 = 0.47-0.68%, p = 2.0 × 10-8-1.0 × 10-10), and increased likelihood of onset of alcohol dependence (hazard ratio = 1.15, p = 4.7 × 10-8); AUDIT-C PRS was not an independent predictor of any phenotype. In ALSPAC, the AUDIT-C PRS was associated with alcohol dependence (R2 = 0.96%, p = 4.8 × 10-6). In GS, AUDIT-C PRS was a better predictor of weekly alcohol use (R2 = 0.27%, p = 5.5 × 10-11), while AUDIT-P PRS was more associated with problem drinking (R2 = 0.40%, p = 9.0 × 10-7). Lastly, AUDIT-P PRS was associated with ICD-based alcohol-related disorders in the UKB subset (R2 = 0.18%, p < 2.0 × 10-16).

CONCLUSIONS

AUDIT-P PRS was associated with a range of alcohol-related phenotypes across population-based and ascertained cohorts, while AUDIT-C PRS showed less utility in the ascertained cohort. We show that AUDIT-P is genetically correlated with both use and misuse and demonstrate the influence of ascertainment schemes on PRS analyses.

Late- and Typical-Onset Heroin Use Among Older Adults Seeking Treatment for Opioid Use Disorder

OBJECTIVE

Analyze 10-year trends in opioid use disorder with heroin (OUD-H) among older persons and to compare those with typical-onset (age <30 years) to those with late (age 30+) onset.

DESIGN

Naturalistic observation using the most recent (2008-2017) Treatment Episode Data Set-Admissions (TEDS-A).

SETTING

Admission records in TEDS-A come from all public and private U.S. programs for substance use disorder treatment receiving public funding.

PARTICIPANTS

U.S. adults aged 55 years and older entering treatment for the first time between 2008 and 2017 to treat OUD-H.

MEASUREMENTS

Admission trends, demographics, substance use history.

RESULTS

The number of older adults who entered treatment for OUD-H nearly tripled between 2007 and 2017. Compared to those with typical-onset (before age 30), those with late-onset heroin use were more likely to be white, female, more highly educated, and rural. Older adults with late-onset were more likely to be referred to treatment by an employer and less likely to be referred by the criminal justice system. Those with late-onset were more likely to use heroin more frequently but less likely to inject heroin than those with typical-onset. Those with typical onset were more likely to receive medication for addiction treatment than those with late-onset.

CONCLUSION

Late-onset heroin use is increasing among older U.S. adults. Research is needed to understand the unique needs of this population better. As this population grows, geriatric psychiatrists may be increasingly called upon to provide specialized care to people with late-onset OUD-H.

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.

A latent class analysis of alcohol and posttraumatic stress symptoms among offspring of parents with and without alcohol use disorder

The co-occurrence of posttraumatic stress disorder (PTSD) and alcohol use disorder (AUD) is widely known, yet few studies have examined whether and how AUD symptoms co-occur with PTSD symptom clusters of hypervigilance, avoidance/numbing, and re-experiencing. The purpose of this study was to examine potential overlap between AUD and posttraumatic stress symptomatology, and to characterize the resultant latent classes in terms of demographics, drinking behaviors, parental AUD, and specific traumas experienced (physical violence, sexual violence, and non-assaultive trauma). We hypothesized that classes would be differentiated by type and severity of AUD and PTS symptoms. Drawing from a sample of white and Black participants from the Collaborative Study on the Genetics of Alcoholism (COGA), we examined young adults between the ages of 18-35 who had experienced trauma (N = 2478). A series of LCA models based on the type of trauma experienced, posttraumatic stress symptoms and problematic alcohol use were then fitted to the data. A four-class solution provided the best fit, consisting of a low symptom class (N = 1134), moderate alcohol/low PTS severity (N = 623), mild alcohol/high PTS severity (N = 544), and high symptom severity (N = 177). Higher prevalence of sexual assault was associated with membership in high PTS severity classes, and parent AUD was associated with membership in each class, particularly when the mother or both parents had the disorder. Using person-centered methods such as LCA is a commonsense approach to understanding the heterogeneity of symptoms, trauma types, and individual-level characteristics associated with trauma-exposed individuals and comorbid AUD-PTSD, and our study is one of relatively few to empirically ascertain the co-occurrence of alcohol and PTS symptoms in a high-risk family sample.

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.

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.

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.

A Pilot Follow-Up Study of Older Alcohol-Dependent COGA Adults

BACKGROUND

Alcohol consumption and problems are increasing among older adults, who are at elevated risk for alcohol-related accidents and medical problems. This paper describes a pilot follow-up of older adults with a history of alcohol dependence that was designed to determine the feasibility of conducting a more extensive investigation.

METHODS

The sample consisted of previously assessed subjects in the Collaborative Studies on the Genetics of Alcoholism who: (i) were age 50+; (ii) had lifetime DSM-IV AD; and (iii) had DNA available. Individuals were located through family contacts, Internet searches, and death registries. A brief telephone interview assessed demographics, health, and alcohol involvement.

RESULTS

Of the total sample (N = 2,174), 36% were contacted, 24% were deceased, and 40% were not yet located. Most (89%) contacted subjects were interviewed, and 99% of them agreed to future evaluation. Thirty percent of interviewed subjects reported abstinence for 10+ years, 56% reported drinking within the past year, and 14% last drank between >1 and 10 years ago. There were no age-related past-year differences in weekly consumption (overall sample mean: 16 drinks), number of drinking weeks (30.8), maximum number of drinks in 24 hours (8.1), or prevalence of weekly risky drinking (19%). Among those who drank within the past 5 years, the 3 most common alcohol-related problems were spending excessive time drinking or recovering (49%), drinking more/longer than intended (35%), and driving while intoxicated (35%); and about a third (32%) received some form of treatment.

CONCLUSIONS

Over a 1-year period, we located 60% of individuals last seen an average of 23 years ago. The majority of contacted individuals were interviewed and willing to be evaluated again. Although the proportion of individuals currently drinking diminished with age, subjects exhibited troublesome levels of alcohol consumption and problems. Our findings suggest the importance and feasibility of a more comprehensive follow-up.

Reliability and validity of an internalizing symptom scale based on the adolescent and adult Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA)

BACKGROUND

The Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA) is an interview that assesses psychiatric symptoms and diagnoses, including substance use disorders and anxiety and mood (i.e., internalizing) disorders. Although the SSAGA is widely used, there exists no overall internalizing characteristics scale based on items drawn from SSAGA's mood and anxiety disorder sections.

OBJECTIVES

To design and assess a SSAGA-based measurement instrument capturing the overall internalizing dimension that underlies more specific internalizing conditions.

METHODS

We developed, assessed, and characterized a new scale for measuring internalizing problematic characteristics derived from the SSAGA interview. All samples were drawn from the Collaborative Studies on the Genetics of Alcoholism, a prospective multi-site genetic study of families at high risk for alcohol use disorders. All participants taking part in the study between September 2005 and September 2017 were eligible (n = 904, 52.2% female).

RESULTS

The scale had adequate internal consistency (ordinal α = 0.85, 95% CI = [0.81, 0.89]). Construct validity was supported by its association with other measures of internalizing characteristics (Internalizing Scale from Achenbach Self Reports; Neuroticism Scale from the Neuroticism-Extraversion-Openness Five-Factor Personality Inventory). Several indices of alcohol, marijuana, and nicotine misuse were also positively associated with Internalizing Scale scores.

CONCLUSIONS

The Internalizing Scale has very good psychometric properties and can be used in studies that incorporate the SSAGA interview to study the association between internalizing characteristics and problematic alcohol and other substance use. These associations can potentially be utilized to identify individuals at risk for substance problems and to design treatments targeting such individuals.

Repeated mild traumatic brain injury produces neuroinflammation, anxiety-like behaviour and impaired spatial memory in mice

PRIMARY OBJECTIVE

Repeated traumatic brain injuries (rmTBI) are frequently associated with debilitating neuropsychiatric conditions such as cognitive impairment, mood disorders, and post-traumatic stress disorder. We tested the hypothesis that repeated mild traumatic brain injury impairs spatial memory and enhances anxiety-like behaviour.

RESEARCH DESIGN

We used a between groups design using single (smTBI) or repeated (rmTBI) controlled cranial closed skull impacts to mice, compared to a control group.

METHODS AND PROCEDURES

We assessed the effects of smTBI and rmTBI using measures of motor performance (Rotarod Test [RT]), anxiety-like behaviour (Elevated Plus Maze [EPM] and Open Field [OF] tests), and spatial memory (Morris Water Maze [MWM]) within 12 days of the final injury. In separate groups of mice, astrocytosis and microglial activation were assessed 24 hours after the final injury using GFAP and IBA-1 immunohistochemistry.

MAIN OUTCOMES AND RESULTS

RmTBI impaired spatial memory in the MWM and increased anxiety-like behaviour in the EPM and OFT. In addition, rmTBI elevated GFAP and IBA-1 immunohistochemistry throughout the mouse brain. RmTBI produced astrocytosis and microglial activation, and elicited impaired spatial memory and anxiety-like behaviour.

CONCLUSIONS

rmTBI produces acute cognitive and anxiety-like disturbances associated with inflammatory changes in brain regions involved in spatial memory and anxiety.

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.

Accelerated Changes in Cortical Thickness Measurements with Age in Military Service Members with Traumatic Brain Injury

Finding objective and quantifiable imaging markers of mild traumatic brain injury (TBI) has proven challenging, especially in the military population. Changes in cortical thickness after injury have been reported in animals and in humans, but it is unclear how these alterations manifest in the chronic phase, and it is difficult to characterize accurately with imaging. We used cortical thickness measures derived from Advanced Normalization Tools (ANTs) to predict a continuous demographic variable: age. We trained four different regression models (linear regression, support vector regression, Gaussian process regression, and random forests) to predict age from healthy control brains from publicly available datasets (n = 762). We then used these models to predict brain age in military Service Members with TBI (n = 92) and military Service Members without TBI (n = 34). Our results show that all four models overpredicted age in Service Members with TBI, and the predicted age difference was significantly greater compared with military controls. These data extend previous civilian findings and show that cortical thickness measures may reveal an association of accelerated changes over time with military TBI.

Use of a machine learning framework to predict substance use disorder treatment success

There are several methods for building prediction models. The wealth of currently available modeling techniques usually forces the researcher to judge, a priori, what will likely be the best method. Super learning (SL) is a methodology that facilitates this decision by combining all identified prediction algorithms pertinent for a particular prediction problem. SL generates a final model that is at least as good as any of the other models considered for predicting the outcome. The overarching aim of this work is to introduce SL to analysts and practitioners. This work compares the performance of logistic regression, penalized regression, random forests, deep learning neural networks, and SL to predict successful substance use disorders (SUD) treatment. A nationwide database including 99,013 SUD treatment patients was used. All algorithms were evaluated using the area under the receiver operating characteristic curve (AUC) in a test sample that was not included in the training sample used to fit the prediction models. AUC for the models ranged between 0.793 and 0.820. SL was superior to all but one of the algorithms compared. An explanation of SL steps is provided. SL is the first step in targeted learning, an analytic framework that yields double robust effect estimation and inference with fewer assumptions than the usual parametric methods. Different aspects of SL depending on the context, its function within the targeted learning framework, and the benefits of this methodology in the addiction field are discussed.

What are the complications and emerging strategies for preventing depression following traumatic brain injury?

INTRODUCTION

Depression is a common and disabling complication of traumatic brain injury (TBI). The high rates of post-TBI depression (PTBID) make this condition an important candidate for selective preventive interventions. Areas covered: The authors recently reported on the efficacy of sertraline, a selective serotonin reuptake inhibitor (SSRI), for the prevention of new cases of depression in the first six months after TBI. The authors review this and other studies on preventive strategies in PTBID as ascertained from a PubMed and citation search. The potential complications and barriers to the implementation of pharmacological prevention in patients with TBI are also discussed. Expert commentary: The prevention of depression in patients with TBI has received little attention relative to other medical conditions. Future studies are needed to confirm the benefit of SSRIs and investigate other pharmacological and non-pharmacological interventions, including in special groups of patients at greater risk of developing PTBID.

Preliminary Investigation of Cerebral Blood Flow and Amyloid Burden in Veterans With and Without Combat-Related Traumatic Brain Injury

This study aimed to examine global and regional cerebral blood flow and amyloid burden in combat veterans with and without traumatic brain injury (TBI). Cerebral blood flow (in milliliters per minute per 100 mL) was measured by quantitative [(15)O]water, and amyloid burden was measured by [(11)C]PIB imaging. Mean global cerebral blood flow was significantly lower in veterans with TBI compared with non-TBI veterans. There were essentially no differences between groups for globally normalized regional cerebral blood flow. Amyloid burden did not differ between TBI and non-TBI veterans. Veterans who have suffered a TBI have significantly lower cerebral blood flow than non-TBI controls but did not manifest increased levels of amyloid, globally or regionally.

Age moderates the association of depressive symptoms and unhealthy alcohol use in the National Guard

Unhealthy drinking is a significant problem contributing to poor health and performance of military personnel. The Iowa Army National Guard and the Iowa Department of Public Health have collaborated with the Substance Abuse and Mental Health Administration to better identify unhealthy substance use via Screening, Brief Intervention, and Referral to Treatment program (SBIRT). Yet, little research has been conducted on the Guard's use of SBIRT. This study examined depression, age, deployment status, and sex as factors contributing to unhealthy drinking. Of the Guardsmen who took part in SBIRT, 3.7% (n=75) met the criteria for unhealthy drinking and 3.9% (n=78) had some level of depression. The overall multivariate model significantly predicted unhealthy drinking (χ(2)(5)=41.41, p<0.001) with age moderating the association of depressive symptoms and unhealthy alcohol (Wald χ(2)(1)=7.16, p=0.007). These findings add to the existing understanding of factors contributing to unhealthy drinking suggesting the association between the presence of depression and unhealthy drinking depends on age of the Guradsman. This age and depression interaction may be an important diagnostic feature to consider for unhealthy drinking in the Guard. Furthermore, previous research on the general military population finds similar percentages, providing support for SBIRT as an effective screening tool in the Guard.

Sertraline for Preventing Mood Disorders Following Traumatic Brain Injury: A Randomized Clinical Trial

IMPORTANCE

Prevention is more effective than treatment to decrease the burden of significant medical conditions such as depressive disorders, a major cause of disability worldwide. Traumatic brain injury (TBI) is a candidate for selective strategies to prevent depression given the incidence, prevalence, and functional effect of depression that occurs after TBI.

OBJECTIVE

To assess the efficacy of sertraline treatment in preventing depressive disorders following TBI.

DESIGN, SETTING, AND PARTICIPANTS

A double-blind, placebo-controlled, parallel-group randomized clinical trial was conducted at a university hospital from July 3, 2008, to September 17, 2012, with 24 weeks of follow-up. A consecutive sample of 534 patients aged 18 to 85 years, hospitalized for mild, moderate, or severe TBI, was eligible for the study. Ninety-four patients consented to participate and were randomized (46 to placebo and 48 to sertraline), of whom 79 (84%) completed the study. Intention-to-treat data analysis was conducted from July 1, 2014, to December 31, 2015.

INTERVENTIONS

Placebo or sertraline, 100 mg/d, for 24 weeks or until development of a mood disorder.

MAIN OUTCOMES AND MEASURES

Time to onset of depressive disorders, as defined by the DSM-IV, associated with TBI.

RESULTS

Of the 94 patients in the study (38 female and 56 male; 92 white), the number needed to treat to prevent depression after TBI at 24 weeks was 5.9 (95% CI, 3.1-71.1; χ2 = 4.6; P = .03) for sertraline treatment vs placebo. The influence of sertraline in the course of neuropsychological variables was not detected. The intervention was well tolerated, and adverse effects were mild in both the sertraline and placebo groups.

CONCLUSIONS AND RELEVANCE

Sertraline appears to be efficacious to prevent the onset of depressive disorders following TBI. Future studies should replicate these findings in a large sample of patients with TBI and depict their long-term physical, cognitive, behavioral, and functional outcomes.

TRIAL REGISTRATION

clinicaltrials.gov Identifier: NCT00704379.

National analysis of differences among substance abuse treatment outcomes: college student and nonstudent emerging adults

OBJECTIVE

To discover differences between student and nonstudent substance abuse treatment demographics, treatment characteristics, and outcomes.

PARTICIPANTS

Conducted February 2014, clients without prior treatment admissions, aged 18-24, not in methadone maintenance therapy, and in nonintensive and ambulatory intensive outpatient treatment settings (N=467,233).

METHODS

Chi-square was used to analyze differences. Multivariate logistic regression including covariates and the student status predicted successful completion with risk differences (RD).

RESULTS

Students were more likely to successfully complete treatment than nonstudents (56.15% vs 41.96%; χ2=1355.04, df=1, p<.0001, RD=14.19, 95% confidence interval [CI] [13.43, 14.95]), and students were 6.92 (95% CI [6.26, 7.58]) percentage points less likely than nonstudents to remain in treatment for longer than 4 months (χ2=367.24, df=1, p<.0001).

CONCLUSIONS

Treatment providers seem to have greater results retaining students in shorter periods. Suggestions for higher education treatment engagement are discussed.

How reliable are county and regional health rankings?

Surveillance system indicators of morbidity, mortality, or behaviors are used to provide regional information for ever-smaller areas, most recently for ranking counties. These rankings are thought to provide information about the relative standing of regions and provide information about problem areas and the success of programs. We investigate the ability of such rankings to reliably assess health. We assess the reliability of several ranked health indices used at the county level and the consistency of an index's quality across different states. Reliability is assessed using an index of reliability, simulations, and the ability of an index to consistently identify the top 10 % (worst) counties within a state. There is marked variability across measures to provide consistent ranks, across states, and, many times, across states for a particular measure. A few health measures do consistently well, e.g., Teen Birth, Chlamydia, and Years of Potential Life Lost rates. While a few health rankings appear worthy of use for policy and in the identification of local problems, in general, they are not consistent across regions.

The role of ventromedial prefrontal cortex in text comprehension inferences: semantic coherence or socio-emotional perspective?

Two hypotheses about the role of the ventromedial prefrontal cortex (vmPFC) in narrative comprehension inferences, global semantic coherence versus socio-emotional perspective, were tested. Seven patients with vmPFC lesions and seven demographically matched healthy comparison participants read short narratives. Using the consistency paradigm, narratives required participants to make either an emotional or visuo-spatial inference, in which a target sentence provided consistent or inconsistent information with a previous emotional state of a character or a visuo-spatial location of an object. Healthy comparison participants made the inferences both for spatial and emotional stories, as shown by longer reading times for inconsistent critical sentences. For patients with vmPFC lesions, inconsistent sentences were read slower in the spatial stories, but not in the emotional ones. This pattern of results is compatible with the hypothesis that vmPFC contributes to narrative comprehension by supporting inferences about socio-emotional aspects of verbally described situations.

How the states stack up: disparities in substance abuse outpatient treatment completion rates for minorities

BACKGROUND

This study was an exploratory investigation of state-level minority disparities in successfully completing outpatient treatment, a major objective for attending substance abuse treatment and a known process outcome measure.

METHOD

This was a retrospective analysis of state discharge and admission data from the 2006 to 2008 Treatment Episode Datasets-Discharge (TEDS-D). Data were included representing all discharges from outpatient substance abuse treatment centers across the United States. All first treatment episode clients with admission/discharge records meeting inclusion criteria who could be classified as White, Latino, or Black/African American were used (n=940,058).

RESULTS

States demonstrated racial and ethnic disparities in their crude and adjusted completion rates, which also varied considerably among the states. Minorities typically showed a disadvantage. A few states showed significantly higher completion rates for Blacks or Latinos.

CONCLUSIONS

Realistically, a variety of factors likely cause the state race/ethnic differences in successful completion rates. States should investigate their delivery systems to reduce completion disparities.

Increased risk of alcohol and drug use among children from deployed military families

AIMS

To examine the association between military deployment of a parent and use of alcohol and drugs among children of deployed military personnel.

DESIGN

Observational and cross-sectional study.

SETTING

Data from the USA 2010 Iowa Youth Survey, a statewide survey of 6th, 8th and 11th graders, were analyzed during 2011.

PARTICIPANTS

Of all 6th-, 8th- and 11th-grade students enrolled in Iowa in 2010, 69% (n = 78 240) completed the survey.

MEASUREMENTS

Ever drink more than a few sips of alcohol and past 30-day: binge drinking, marijuana consumption, other illegal drug use and prescription drug misuse.

FINDINGS

The rates of alcohol use [risk difference (RD) = 7.85, 99.91% confidence interval (CI) = 4.44-11.26], binge drinking (RD = 8.02, 99.91% CI = 4.91-11.13), marijuana use (RD = 5.30, 99.91% CI = 2.83-7.77), other illegal drug use (RD = 7.10, 99.91% CI = 4.63-9.56) and prescription drug misuse (RD = 8.58, 99.91% CI = 5.64-11.51) are greater for children of currently or recently deployed parents than for children of parents who are not in the military. The magnitude of the effects is consistent across 6th, 8th and 11th grades. Disrupted living arrangements further accentuate increased substance use, with the largest effect seen in children with a deployed parent who was not living with a parent or relative.

CONCLUSIONS

Children of deployed military personnel should be considered at higher risk for substance use than children of non-military citizens.

White matter abnormalities in veterans with mild traumatic brain injury

OBJECTIVE

It has been estimated that 10%-20% of U.S. veterans of the wars in Iraq and Afghanistan experienced mild traumatic brain injury (TBI), mostly secondary to blast exposure. Diffusion tensor imaging (DTI) may detect subtle white matter changes in both the acute and chronic stages of mild TBI and thus has the potential to detect white matter damage in patients with TBI. The authors used DTI to examine white matter integrity in a relatively large group of veterans with a history of mild TBI.

METHOD

DTI images from 72 veterans of the wars in Iraq and Afghanistan who had mild TBI were compared with DTI images from 21 veterans with no exposure to TBI during deployment. Conventional voxel-based analysis as well as a method of identifying spatially heterogeneous areas of decreased fractional anisotropy ("potholes") were used. Veterans also underwent psychiatric and neuropsychological assessments.

RESULTS

Voxel-based analysis did not reveal differences in DTI parameters between the veterans with mild TBI and those with no TBI. However, the veterans with mild TBI had a significantly higher number of potholes than those without TBI. The difference in the number of potholes was not influenced by age, time since trauma, a history of mild TBI unrelated to deployment, or coexisting psychopathology. The number of potholes was correlated with the severity of TBI and with performance in executive functioning tasks.

CONCLUSIONS

Veterans who had blast-related mild TBI showed evidence of multifocal white matter abnormalities that were associated with severity of the injury and with relevant functional measures. Overall, white matter potholes may constitute a sensitive biomarker of axonal injury that can be identified in mild TBI at acute and chronic stages of its clinical course.

Assessing community variation and randomness in public health indicators

Background

Evidence-based health indicators are vital to needs-based programming and epidemiological planning. Agencies frequently make programming funds available to local jurisdictions based on need. The use of objective indicators to determine need is attractive but assumes that selection of communities with the highest indicators reflects something other than random variability from sampling error.

Methods

The authors compare the statistical performance of two heterogeneity measures applied to community differences that provide tests for randomness and measures of the percentage of true community variation, as well as estimates of the true variation. One measure comes from the meta-analysis literature and the other from the simple Pearson chi-square statistic. Simulations of populations and an example using real data are provided.

Results

The measure based on the simple chi-square statistic seems superior, offering better protection against Type I errors and providing more accurate estimates of the true community variance.

Conclusions

The heterogeneity measure based on Pearson's χ² should be used to assess indices. Methods for improving poor indices are discussed.

Escitalopram and enhancement of cognitive recovery following stroke

CONTEXT

Adjunctive restorative therapies administered during the first few months after stroke, the period with the greatest degree of spontaneous recovery, reduce the number of stroke patients with significant disability.

OBJECTIVE

To examine the effect of escitalopram on cognitive outcome. We hypothesized that patients who received escitalopram would show improved performance in neuropsychological tests assessing memory and executive functions than patients who received placebo or underwent Problem Solving Therapy.

DESIGN

Randomized trial.

SETTING

Stroke center.

PARTICIPANTS

One hundred twenty-nine patients were treated within 3 months following stroke. The 12-month trial included 3 arms: a double-blind placebo-controlled comparison of escitalopram (n = 43) with placebo (n = 45), and a nonblinded arm of Problem Solving Therapy (n = 41).

OUTCOME MEASURES

Change in scores from baseline to the end of treatment for the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) and Trail-Making, Controlled Oral Word Association, Wechsler Adult Intelligence Scale-III Similarities, and Stroop tests.

RESULTS

We found a difference among the 3 treatment groups in change in RBANS total score (P < .01) and RBANS delayed memory score (P < .01). After adjusting for possible confounders, there was a significant effect of escitalopram treatment on the change in RBANS total score (P < .01, adjusted mean change in score: escitalopram group, 10.0; nonescitalopram group, 3.1) and the change in RBANS delayed memory score (P < .01, adjusted mean change in score: escitalopram group, 11.3; nonescitalopram group, 2.5). We did not observe treatment effects in other neuropsychological measures.

CONCLUSIONS

When compared with patients who received placebo or underwent Problem Solving Therapy, stroke patients who received escitalopram showed improvement in global cognitive functioning, specifically in verbal and visual memory functions. This beneficial effect of escitalopram was independent of its effect on depression. The utility of antidepressants in the process of poststroke recovery should be further investigated. Trial Registration clinicaltrials.gov Identifier: NCT00071643.

Leptin gene -2548G/A variants predict risperidone-associated weight gain in children and adolescents

OBJECTIVE

As the use of atypical antipsychotics in children and adolescents has increased, concerns have been raised about their long-term safety. We aimed to investigate the association between risperidone-induced weight gain, leptin concentration, and the leptin gene (LEP) -2548G/A variants in youths.

METHODS

Medically healthy 7- to 17-year-old children and adolescents, in extended naturalistic treatment with risperidone, were recruited through pediatric psychiatry clinics. Anthropometric measures and laboratory testing were conducted. Growth and medication history was obtained from the medical record. The effect of the LEP genotypes on leptin concentration and on the slopes of the weight and body mass index (BMI) Z-score curves before and after the onset of risperidone treatment was investigated .

RESULTS

In 74 individuals, chronically treated with risperidone, the A allele was associated with higher leptin concentration at low weight and BMI Z-scores. There was no effect of the LEP genotypes on weight or BMI Z-scores before risperidone was started. Afterwards, however, the A-allele carriers showed a steeper rate of increase in weight and BMI Z-scores. As a result, the GG-genotype carriers were 2.5 times less likely to be overweight/obese (i.e. having a BMI above the 85th percentile). This genetic effect on risperidone-associated weight gain did not extend to weight loss related to psychostimulants.

CONCLUSION

The LEP - 2548G/A variants seem to moderate the weight-altering effect of risperidone but not psychostimulants. This may be related to genetic differences in tissue sensitivity to leptin, resulting in differential body composition.

Neuroimaging correlates of apathy and depression in Alzheimer's disease

A consecutive series of 79 patients with probable Alzheimer's disease were assessed with a structured psychiatric evaluation, and diagnoses of apathy and depression were made using standardized criteria. Three-dimensional MRI scans were obtained from all patients, and images were segmented into gray matter, white matter, and CSF. White matter hyperintensities were edited on segmented images, and lobar assignments (frontal, temporal, parietal, and occipital) were made based on Talairach coordinates. Patients with apathy showed a significantly larger volume of frontal white matter hyperintensities than patients without apathy. Patients with depression had a significantly larger volume of right parietal white matter hyperintensities than patients without depression. However, neither apathy nor depression was significantly associated with lobar gray or white matter atrophy. Frontal and right parietal white matter hyperintensities are the strongest brain structural correlates of apathy and depression in Alzheimer's disease.

Variants of the dopamine D2 receptor gene and risperidone-induced hyperprolactinemia in children and adolescents

OBJECTIVE

To investigate the association between hyperprolactinemia and variants of the dopamine D2 receptor (DRD2) gene in children and adolescents in long-term treatment with risperidone.

METHODS

Medically healthy 7 to 17-year-old patients chronically treated with risperidone but receiving no other antipsychotics were recruited in a cross-sectional study. Four DRD2 variants were genotyped and prolactin concentration was measured. Medication history was obtained from the medical records. The effect of the TaqIA variants of the DRD2 on the risk of risperidone-induced hyperprolactinemia was the primary outcome measure.

RESULTS

Hyperprolactinemia was present in 50% of 107 patients (87% males) treated with risperidone for an average of 2.9 years. Age, stage of sexual development, and the dose of risperidone independently predicted a higher prolactin concentration, whereas the dose of psychostimulants was negatively correlated with it. However, these four predictors became nonsignificant when risperidone serum concentration was entered into the model. Adverse events potentially related to hyperprolactinemia were more common in participants with elevated prolactin concentration and in girls (45%) compared with boys (10%). After controlling for risperidone concentration and the dose of psychostimulants, the TaqIA A1 and the A-241G alleles were associated with higher prolactin concentration, whereas the -141C Ins/Del and C957T variants had no significant effect. In addition, adverse events potentially related to hyperprolactinemia were four times more common in TaqIA A1 allele carriers.

CONCLUSION

Prolactin concentration is closely related to central DRD2 blockade, as reflected by risperidone serum concentration. Furthermore, the TaqIA and A-241G variants of the DRD2 gene could be useful in predicting the emergence of hyperprolactinemia and its potential adverse events.

Weight gain and metabolic abnormalities during extended risperidone treatment in children and adolescents

OBJECTIVE

The aim of this study was to investigate the prevalence of clinical and laboratory metabolic abnormalities during long-term risperidone treatment in children and adolescents.

METHODS

Medically healthy 7- to 17-year-old children chronically treated, in a naturalistic setting, with risperidone were recruited through child psychiatry clinics. Anthropometric measurements and laboratory testing were conducted. Developmental and medication histories were obtained from medical records.

RESULTS

In 99 patients treated with risperidone for an average of 2.9 years, a significant increase in age- and gender-adjusted weight and body mass index (BMI) (i.e., z-scores) was observed. Concomitant treatment with psychostimulants did not attenuate this weight gain. Risperidone-associated weight gain was negatively correlated with the BMI z-score obtained at the onset of risperidone treatment. Compared to lean children, overweight and obese children had higher odds of metabolic abnormalities, including increased waist circumference, hypertriglyceridemia, and low high-density lipoprotein cholesterol (HDL-C). They also tended to have a higher insulin level and homeostasis model assessment insulin resistance (HOMA-IR) index. As a result, upon recruitment in the study, children with excessive weight were 12 times more likely to have at least one laboratory metabolic abnormality and seven times more likely to have at least one criterion of the metabolic syndrome compared to lean subjects. In contrast to excessive weight status, gaining > or =0.5 BMI z-score point during risperidone treatment was not associated with a significantly higher occurrence of metabolic disturbances.

CONCLUSIONS

The long-term use of risperidone, especially when weight is above normal, is associated with a number of metabolic abnormalities but a low prevalence of the metabolic syndrome phenotype. Future studies should evaluate the stability of these abnormalities over time.

Epidemiological characteristics of pregnancy, delivery, and birth outcome in women with multiple sclerosis in Argentina (EMEMAR study)

Background

The influence of pregnancy on Multiple Sclerosis (MS) has been extensively studied but such influence on Latin American women with MS has not been characterized. Our objective was to describe the course of pregnancy and birth outcome in Argentinean MS patients and the evolution of MS during pregnancy and after delivery.

Method

We used a retrospective design in eight MS centers in Argentina and administered a survey to women with definite MS (Mc Donald) with pregnancies during or after MS onset. We contacted 355 women of which 81 met inclusion criteria. We recorded 141 pregnancies.

Results

Involuntary abortion was observed in 16% of pregnancies (95% CI = 10–23). Thirty five women received immunomodulatory therapy (IMT) before 42 pregnancies. Twenty three (55%) out of 42 pregnancies were exposed to IMT. The mean time of IMT discontinuation before conception in 19 (45.2%) pregnancies without exposure, was 104 days (95% CI = 61.0–147.0). There were 103 deliveries: 79% full term. Birth defects were detected in 19% of pregnancies exposed to IMT (95% CI = 4–46) and in 2% of non-exposed (95% CI = 0.3–8.0). The mean relapse rate was: pre-pregnancy year: 0.22 (95% CI = 0.12–0.32); pregnancy: 0.31 in 1st (95% CI = 0.10–0.52), 0.19 (95% CI = 0.03–0.36) in 2nd, and 0.04 in 3rd trimester (95% CI = –0.04–0.12); 1st trimester post delivery: 0.82 (95% CI = 0.42–1.22).

Conclusion

We observed a higher rate of birth defects among infants exposed to immunomodulators in utero than those not exposed. The reduction in MS relapses during 2nd and 3rd trimester of pregnancy and its increase during postpartum is consistent with previous reports.

Validation of the Multiple Sclerosis Neuropsychological Screening Questionnaire in Argentina

BACKGROUND

Considering the lack of screening technology that would permit neurologists to identify patients who may benefit from formal or more comprehensive assessment of neuropsychological status in patients with multiple sclerosis (MS) in Argentina, we felt the need to validate the Multiple Sclerosis Neuropsychological Screening Questionnaire (MSNQ) developed by Benedict, et al.

OBJECTIVE

The objective in this multicenter study was to test the reliability and validity of the MSNQ after translation into Spanish in Argentina. We also compared the MSNQ yield by the patient report with that of the two different informants. The sample included 125 patients with MS and 36 normal controls, 27 patients had two informants available and 23 patients and their informants were examined twice at 1-week intervals (test-retest group). All participants completed the MSNQ, RAO BRB, Beck Depression Inventory-Fast Screen, EDSS, and MS Functional Composite.

RESULTS

We found that an MSNQ-I score of 26 or more resulted in classifications yielding sensitivity of 0.91 and specificity of 0.80, suggesting some utility for this Argentine, informant-report measure.

CONCLUSIONS

This Spanish version of the MSNQ is reliable and useful as a screening test for identifying patients at high risk for cognitive impairment in MS.

Escitalopram and problem-solving therapy for prevention of poststroke depression: a randomized controlled trial

CONTEXT

Depression occurs in more than half of patients who have experienced a stroke. Poststroke depression has been shown in numerous studies to be associated with both impaired recovery in activities of daily living and increased mortality. Prevention of depression thus represents a potentially important goal.

OBJECTIVE

To determine whether treatment with escitalopram or problem-solving therapy over the first year following acute stroke will decrease the number of depression cases that develop compared with placebo medication.

DESIGN, SETTING, AND PARTICIPANTS

A multisite randomized controlled trial for prevention of depression among 176 nondepressed patients was conducted within 3 months following acute stroke from July 9, 2003, to October 1, 2007. The 12-month trial included 3 groups: a double-blind placebo-controlled comparison of escitalopram (n = 59) with placebo (n = 58), and a nonblinded problem-solving therapy group (n = 59).

MAIN OUTCOME MEASURES

The main outcome measure was the development of major or minor poststroke depression based on symptoms elicited by the Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition) (DSM-IV) and the diagnostic criteria from DSM-IV for depression due to stroke with major depressive-like episode or minor depression (ie, research criteria).

RESULTS

Patients who received placebo were significantly more likely to develop depression than individuals who received escitalopram (11 major and 2 minor cases of depression [22.4%] vs 3 major and 2 minor cases of depression [8.5%], adjusted hazard ratio [HR], 4.5; 95% confidence interval [CI], 2.4-8.2; P < .001) and also more likely than individuals who received problem-solving therapy (5 major and 2 minor cases of depression [11.9%], adjusted HR, 2.2; 95% CI, 1.4-3.5; P < .001). These results were adjusted for history of mood disorders and remained significant after considering possible confounders such as age, sex, treatment site, and severity of impairment in the model. Using an intention-to-treat conservative method of analyzing the data, which assumed that all 27 patients who did not start randomized treatment would have developed depression, and controlling for prior history of mood disorders, escitalopram was superior to placebo (23.1% vs 34.5%; adjusted HR, 2.2; 95% CI, 1.2-3.9; P = .007), while problem-solving therapy was not significantly better than placebo (30.5% vs 34.5%; adjusted HR, 1.1; 95% CI, 0.8-1.5; P = .51). Adverse events, including all-cause hospitalizations, nausea, and adverse effects associated with escitalopram were not significantly different between the 3 groups.

CONCLUSIONS

In this study of nondepressed patients with recent stroke, the use of escitalopram or problem-solving therapy resulted in a significantly lower incidence of depression over 12 months of treatment compared with placebo, but problem-solving therapy did not achieve significant results over placebo using the intention-to-treat conservative method of analysis.

TRIAL REGISTRATION

clinicaltrials.gov Identifier: NCT00071643.

Treatment of vascular depression using repetitive transcranial magnetic stimulation

CONTEXT

The term vascular depression (VD) has been used to describe late-life depressive disorders in patients with clinical evidence of cerebrovascular disease. Preliminary data on poststroke depression suggest that repetitive transcranial magnetic stimulation (rTMS) might also be effective among patients with VD.

OBJECTIVE

To examine the efficacy and safety of rTMS to treat VD.

DESIGN

Prospective, randomized, sham-controlled study.

SETTING

University hospital.

METHODS

After discontinuation of antidepressant therapy, 92 patients with clinically defined VD were randomly assigned to receive active or sham rTMS of the left dorsolateral prefrontal cortex. Approximately half of the patients met criteria for magnetic resonance imaging-defined VD. In experiment 1, we administered a total cumulative dose (TCD) of 12 000 pulses (TCD-12K); in experiment 2, 18,000 pulses (TCD-18K). Sham stimulation was performed using a sham coil.

RESULTS

In experiment 1, the sham group showed a 13.6% decrease in the 17-item Hamilton Depression Rating Scale (HAMD-17) scores compared with a 33.1% decrease in the TCD-12K group (P = .04). Response rates were 6.7% in the sham group and 33.3% in the active-stimulation group (P = .08); remission rates were 6.7% and 13.3%, respectively (P = .50). In experiment 2, the sham group showed a 17.5% decrease in the 17-item Hamilton Depression Rating Scale scores compared with a 42.4% decrease observed in the TCD-18K group (P < .001). Response rates were 6.9% in the sham group and 39.4% in the active-stimulation group (P = .003); remission rates were 3.5% and 27.3%, respectively (P = .01). Response rates to rTMS were negatively correlated with age and positively correlated with higher frontal gray matter volumes.

CONCLUSIONS

To our knowledge, this is the first controlled trial that demonstrates the efficacy of rTMS among geriatric patients with VD. Older age and smaller frontal gray matter volumes were associated with a poorer response to rTMS.