Revisiting Preaddiction.

The directors of the National Institute on Drug Abuse and the National Institute on Alcohol Abuse and Alcoholism have proposed new efforts to enable earlier identification and intervention for harmful substance use and its consequences. As editors of The ASAM Principles of Addiction Medicine, we fully support this goal. The word "preaddiction" has been suggested as a diagnostic label to describe individuals who would be targeted for early intervention.

Enhancing Clinical Predictive Modeling through Model Complexity-Driven Class Proportion Tuning for Class Imbalanced Data: An Empirical Study on Opioid Overdose Prediction.

Class imbalance issues are prevalent in the medical field and significantly impact the performance of clinical predictive models. Traditional techniques to address this challenge aim to rebalance class proportions. They generally assume that the rebalanced proportions are derived from the original data, without considering the intricacies of the model utilized.

Rapid Initiation of Injection Naltrexone for Opioid Use Disorder: A Stepped-Wedge Cluster Randomized Clinical Trial.

Importance: Injectable extended-release (XR)-naltrexone is an effective treatment option for opioid use disorder (OUD), but the need to withdraw patients from opioid treatment prior to initiation is a barrier to implementation.

Objective: To compare the effectiveness of the standard procedure (SP) with the rapid procedure (RP) for XR-naltrexone initiation.

Design, Setting, And Participants: The Surmounting Withdrawal to Initiate Fast Treatment with Naltrexone study was an optimized stepped-wedge cluster randomized trial conducted at 6 community-based inpatient addiction treatment units.

Tapping into alcohol use during COVID: Drinking correlates among bartenders and servers.

The COVID pandemic placed a spotlight on alcohol use and the hardships of working within the food and beverage industry, with millions left jobless. Following previous studies that have found elevated rates of alcohol problems among bartenders and servers, here we studied the alcohol use of bartenders and servers who were employed during COVID. From February 12-June 16, 2021, in the midst of the U.

Language-based EMA assessments help understand problematic alcohol consumption.

Background: Unhealthy alcohol consumption is a severe public health problem. But low to moderate alcohol consumption is associated with high subjective well-being, possibly because alcohol is commonly consumed socially together with friends, who often are important for subjective well-being. Disentangling the health and social complexities of alcohol behavior has been difficult using traditional rating scales with cross-section designs.

An integrated LSTM-HeteroRGNN model for interpretable opioid overdose risk prediction.

Opioid overdose (OD) has become a leading cause of accidental death in the United States, and overdose deaths reached a record high during the COVID-19 pandemic. Combating the opioid crisis requires targeting high-need populations by identifying individuals at risk of OD. While deep learning emerges as a powerful method for building predictive models using large scale electronic health records (EHR), it is challenged by the complex intrinsic relationships among EHR data.

Compassion within conflict: Toward a computational theory of social groups informed by maternal brain physiology.

Benevolent intersubjectivity developed in parent-infant interactions and compassion toward friend and foe alike are non-violent interventions to group behavior in conflict. Based on a dyadic active inference framework rooted in specific parental brain mechanisms, we suggest that interventions promoting compassion and intersubjectivity can reduce stress, and that compassionate mediation may resolve conflicts.

Where Opioid Overdose Patients Live Far From Treatment: Geospatial Analysis of Underserved Populations in New York State.

Background: Opioid addiction and overdose have a large burden of disease and mortality in New York State (NYS). The medication naloxone can reverse an overdose, and buprenorphine can treat opioid use disorder. Efforts to increase the accessibility of both medications include a naloxone standing order and a waiver program for prescribing buprenorphine outside a licensed drug treatment program.

Comparison of Methods for Alcohol and Drug Screening in Primary Care Clinics.

Importance: Guidelines recommend that adult patients receive screening for alcohol and drug use during primary care visits, but the adoption of screening in routine practice remains low. Clinics frequently struggle to choose a screening approach that is best suited to their resources, workflows, and patient populations.

Objective: To evaluate how to best implement electronic health record (EHR)-integrated screening for substance use by comparing commonly used screening methods and examining their association with implementation outcomes.

Identifying risk of opioid use disorder for patients taking opioid medications with deep learning.

Objective: The United States is experiencing an opioid epidemic. In recent years, there were more than 10 million opioid misusers aged 12 years or older annually. Identifying patients at high risk of opioid use disorder (OUD) can help to make early clinical interventions to reduce the risk of OUD.

Association of Opioid Use Disorder With 2016 Presidential Voting Patterns: Cross-sectional Study in New York State at Census Tract Level.

Background: Opioid overdose-related deaths have increased dramatically in recent years. Combating the opioid epidemic requires better understanding of the epidemiology of opioid poisoning (OP) and opioid use disorder (OUD).

Objective: We aimed to discover geospatial patterns in nonmedical opioid use and its correlations with demographic features related to despair and economic hardship, most notably the US presidential voting patterns in 2016 at census tract level in New York State.

Predicting opioid overdose risk of patients with opioid prescriptions using electronic health records based on temporal deep learning.

The US is experiencing an opioid epidemic, and opioid overdose is causing more than 100 deaths per day. Early identification of patients at high risk of Opioid Overdose (OD) can help to make targeted preventative interventions. We aim to build a deep learning model that can predict the patients at high risk for opioid overdose and identify most relevant features.

A large-scale retrospective study of opioid poisoning in New York State with implications for targeted interventions.

Opioid overdose related deaths have increased dramatically in recent years. Combating the opioid epidemic requires better understanding of the epidemiology of opioid poisoning (OP). To discover trends and patterns of opioid poisoning and the demographic and regional disparities, we analyzed large scale patient visits data in New York State (NYS).

Machine Learning Based Opioid Overdose Prediction Using Electronic Health Records.

Opioid addiction in the United States has come to national attention as opioid overdose (OD) related deaths have risen at alarming rates. Combating opioid epidemic becomes a high priority for not only governments but also healthcare providers. This depends on critical knowledge to understand the risk of opioid overdose of patients.

Novel Formulations of Buprenorphine for Treatment of Opioid Use Disorder.

Opioid use disorder (OUD) is epidemic in the United States. In addition to medical, economic, and social impairments, risk of overdose fatality is high. In 2017, there were 14,958 deaths from natural or semisynthetic opioids, 15,958 from heroin, and 29,406 from synthetic opioids, such as fentanyl.

Gabapentin Enacarbil Extended-Release for Alcohol Use Disorder: A Randomized, Double-Blind, Placebo-Controlled, Multisite Trial Assessing Efficacy and Safety.

Background: Several single-site alcohol treatment clinical trials have demonstrated efficacy for immediate-release (IR) gabapentin in reducing drinking outcomes among individuals with alcohol dependence. The purpose of this study was to conduct a large, multisite clinical trial of gabapentin enacarbil extended-release (GE-XR) (HORIZANT ), a gabapentin prodrug formulation, to determine its safety and efficacy in treating alcohol use disorder (AUD).

Methods: Men and women (n = 346) who met DSM-5 criteria for at least moderate AUD were recruited across 10 U.

Barriers and facilitators affecting the implementation of substance use screening in primary care clinics: a qualitative study of patients, providers, and staff.

Background: Alcohol and drug use are leading causes of morbidity and mortality that frequently go unidentified in medical settings. As part of a multi-phase study to implement electronic health record-integrated substance use screening in primary care clinics, we interviewed key clinical stakeholders to identify current substance use screening practices, barriers to screening, and recommendations for its implementation.

Methods: Focus groups and individual interviews were conducted with 67 stakeholders, including patients, primary care providers (faculty and resident physicians), nurses, and medical assistants, in two urban academic health systems.

Blood Levels of Monoamine Precursors and Smoking in Patients with Schizophrenia.

Smoking is highly prevalent in patients with schizophrenia and exerts a negative impact on cardiovascular mortality in these patients. Smoking has complex interactions with monoamine metabolism through the ability of cigarette smoke to suppress Type 1 T helper cell (Th1) type immunity, the immunophenotype that is implicated in phenylalanine hydroxylase (PAH) dysfunction and tryptophan (Trp) breakdown to kynurenine (Kyn) via indoleamine 2,3-dioxygenase. Nicotine also induces tyrosine hydroxylase (TH) gene expression, leading to increased synthesis of catecholamines.