Literature DB >> 31106686

Predicting substance use disorder using long-term attention deficit hyperactivity disorder medication records in Truven.

Sajjad Fouladvand, Emily R Hankosky, Heather Bush, Jin Chen, Linda P Dwoskin, Patricia R Freeman, Darren W Henderson1, Kathleen Kantak2, Jeffery Talbert1, Shiqiang Tao, Guo-Qiang Zhang3.   

Abstract

About 20% of individuals with attention deficit hyperactivity disorder are first diagnosed during adolescence. While preclinical experiments suggest that adolescent-onset exposure to attention deficit hyperactivity disorder medication is an important factor in the development of substance use disorder phenotypes in adulthood, the long-term impact of attention deficit hyperactivity disorder medication initiated during adolescence has been largely unexplored in humans. Our analysis of 11,624 adolescent enrollees with attention deficit hyperactivity disorder in the Truven database indicates that temporal medication features, rather than stationary features, are the most important factors on the health consequences related to substance use disorder and attention deficit hyperactivity disorder medication initiation during adolescence.

Entities:  

Keywords:  attention deficit hyperactivity disorder; big data; deep learning; long-short term memory model; substance use disorder

Year:  2019        PMID: 31106686      PMCID: PMC6861600          DOI: 10.1177/1460458219844075

Source DB:  PubMed          Journal:  Health Informatics J        ISSN: 1460-4582            Impact factor:   2.681


  21 in total

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4.  Age of Onset, Duration, and Type of Medication Therapy for Attention-Deficit/Hyperactivity Disorder and Substance Use During Adolescence: A Multi-Cohort National Study.

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2.  Deep Learning Prediction of Mild Cognitive Impairment using Electronic Health Records.

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  2 in total

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