Gender differences in ADHD adults during clinical trials with atomoxetine

posterIntroduction: Patients with ADHD exhibit several consistent gender differences, a male preponderance and more males with externalizing disorders (conduct and oppositional defiant disorder). Objective: To examine gender differences in a very large clinical trial of adults with ADHD. Methods: Data from two identical placebo-controlled studies of atomoxetine in adult ADHD using 535 subjects at 31 sites were combined1. The studies lasted 8 weeks and both showed positive medication-placebo differences. Most current Axis-I diagnoses were exclusionary criteria. Results: The male/female ratio of this self-referred population was 2.4:1, lower than in child studies2. In contrast to a predominance of an inattentive ADHD diagnosis subtype in female children, these adult females were more frequently combined type versus the males. Females were rated as more impaired on every measure of ADHD symptoms including total CAARS-INV, total WRAADDS3, and subscales of both measures. Females were rated as having more emotional symptoms on the WRAADDS emotional dimension, lifetime SCID-P psychiatric diagnoses, HAM-A, and HAM-D. Females exhibited significantly greater improvement on the WRAADDS emotional dimension but not on similar items in the Psychological Well-Being Scale. There were no significant gender by treatment effects in the CAARS-INV or CGI-S scores. Conclusion: These females with ADHD displayed significantly greater ADHD symptoms and emotional impairment on multiple measures. On the WRAADDS emotional dimension they responded better to treatment, than their male counterparts. Past research shows that ADHD is much more common in males particularly in pediatric samples. Children exhibit few gender differences on a consistent basis except in the area of associated symptoms. The present study addresses whether ADHD adults displayed gender differences at screening or in treatment response using data from the largest studies ever conducted in ADHD adults

Systems for multivariate monitoring of behavioral status over time

Decision-theoretic criteria are presented for optimizing the information gathered from a series of interviews over time. It is shown that the optimum interviewing strategy depends strongly on assumptions about the covariation of behavior over time. Standard interviewing strategies, including the major-problem/target-complaints approach, are optimal only under extreme assumptions about behavior. An interviewing strategy based on dynamic programming is presented that will provide optimal information return from a series of interviews under assumptions that are realistic for mental health applications. A system using this approach can tailor its interviewing strategy to adapt to differences in interview content, item importance, and individual response patterns, selecting the optimally informative questions to ask each subject at each point in time. Simulation results show that this approach achieves a 34% reduction in the false negatives obtained with the major-problem/target-complaints method, and, depending on the acceptable error rate, a reduction of 47 % or more in the questions that are needed in standard interviewing

Risk factors for borderline personality disorder in treatment seeking patients with a substance use disorder: An international multicenter study

Borderline personality disorder (BPD) and substance use disorders (SUDs) often co-occur, partly because they share risk factors. In this international multicenter study, risk factors for BPD were examined for SUD patients. In total, 1,205 patients were comprehensively examined by standardized interviews and questionnaires on psychiatric diagnosis and risk factors, and it was found that 1,033 (85.7%) had SUDs without BPD (SUD) and 172 (14.3%) had SUD with BPD (SUD + BPD). SUD + BPD patients were significantly younger, more often females and more often diagnosed with comorbid adult attention deficit/hyperactivity disorder. SUD + BPD patients did not differ from SUD patients on most risk factors typical for SUD such as maternal use of drugs during pregnancy or parents having any SUD. However, SUD + BPD patients did have a higher risk of having experienced emotional and physical abuse, neglect, or family violence in childhood compared to SUD patients, suggesting that child abuse and family violence are BPD-specific risk factors in patients with SUDs

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Persistence and Subtype Stability of ADHD Among Substance Use Disorder Treatment Seekers

OBJECTIVE: To examine ADHD symptom persistence and subtype stability among substance use disorder (SUD) treatment seekers. METHOD: In all, 1,276 adult SUD treatment seekers were assessed for childhood and adult ADHD using Conners' Adult ADHD Diagnostic Interview for Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV; CAADID). A total of 290 (22.7%) participants met CAADID criteria for childhood ADHD and comprise the current study sample. RESULTS: Childhood ADHD persisted into adulthood in 72.8% (n = 211) of cases. ADHD persistence was significantly associated with a family history of ADHD, and the presence of conduct disorder and antisocial personality disorder. The combined subtype was the most stable into adulthood (78.6%) and this stability was significantly associated with conduct disorder and past treatment of ADHD. CONCLUSION: ADHD is highly prevalent and persistent among SUD treatment seekers and is associated with the more severe phenotype that is also less likely to remit. Routine screening and follow-up assessment for ADHD is indicated to enhance treatment management and outcomes

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

Exposure compliance methodologies for multiple input multiple output (mimo) enabled networks and terminals

Multiple input multiple output (MIMO) enabled handsets and base-stations feature antenna systems that generate electromagnetic fields for which relevant exposure standards and guidelines do not explicitly define compliance testing methodologies. Here, through computational modeling, we explore several field summation schemes for evaluating such exposures and propose compliance testing methodologies that limit the degree of exposure under/over-estimation for both base stations and handsets. The methodologies rely on scalar field probe measurements thus avoiding significant equipment upgrades and are applicable to cases where access to signals from eachMIMO antenna element can be arranged