• Author: David W. Oslin
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Development of a peer-delivered primary care intervention to improve Veteran mental health treatment engagement

Abstract: Veteran engagement in mental health treatment (MHT) remains low. Peer specialists (PS) are well positioned to implement interventions addressing barriers to MHT …

Clusters based on within-treatment symptom trajectories as predictors of dropout in treatment for posttraumatic stress disorder and substance use disorder

Abstract: Objective: Dropout rates are high in treatments for co-occurring posttraumatic stress disorder (PTSD) and substance use disorders (SUDs). We examined dropout predictors …

Longitudinal Oral and Fecal Microbiome Alterations in Veterans With New Antidepressant Monotherapy for Major Depressive Disorder

Abstract: Major depressive disorder (MDD) is associated with a wide range of adverse outcomes. Though antidepressants are often implemented as first-line treatments for MDD, …

Longitudinal influence of prescribed antidepressants on fecal and oral microbiomes among Veterans with major depressive disorder

Abstract: OBJECTIVE: The purpose of this study was to evaluate the influence of a new course of antidepressant monotherapy on gut and oral microbiomes and the relationship to …

High dimensional predictions of suicide risk in 4.2 million US Veterans using ensemble transfer learning

Abstract: We present an ensemble transfer learning method to predict suicide from Veterans Affairs (VA) electronic medical records (EMR). A diverse set of base models was trained …

The impact of substance use on posttraumatic stress disorder symptoms and treatment discontinuation

Abstract: This study examined the impact of ongoing substance use during posttraumatic stress disorder (PTSD) and substance use disorder (SUD) treatment on PTSD symptoms and …

Pharmacogenetic testing and monitoring of complete blood counts among Veterans newly prescribed thiopurine treatments: A retrospective cohort study

Abstract: Pharmacogenetic (PGx) testing before initiation of thiopurine treatment and CBC monitoring post-initiation helps avoid adverse events and ensure patient safety. This …

Deep sequential neural network models improve stratification of suicide attempt risk among US Veterans

Abstract: OBJECTIVE: To apply deep neural networks (DNNs) to longitudinal EHR data in order to predict suicide attempt risk among veterans. Local explainability techniques were …

Development of a model to predict combined antidepressant medication and psychotherapy treatment response for depression among veterans

Abstract: Although research shows that more depressed patients respond to combined antidepressants (ADM) and psychotherapy than either alone, many patients do not respond even to …

Drug-drug-gene interaction risk among opioid users in the U.S. Department of Veterans Affairs

Abstract: Response to analgesic therapy is influenced by several factors including genetics and drug-drug interactions. Pharmacogenetic (PGx) variants in the CYP2D6 gene modify …

Development of a model to predict antidepressant treatment response for depression among Veterans

Abstract: Background: Only a limited number of patients with major depressive disorder (MDD) respond to a first course of antidepressant medication (ADM). We investigated the …

Are Veterans Getting Their Preferred Depression Treatment? A National Observational Study in the Veterans Health Administration

Abstract: Background: Physician responsiveness to patient preferences for depression treatment may improve treatment adherence and clinical outcomes. Objective: To examine …