Characterizing patients at higher cardiovascular risk for prescribed stimulants: Learning from health records data with predictive analytics and data mining techniques.

Journal: Computers in biology and medicine
PMID: 39978098

Abstract

OBJECTIVE: Given the significantly increased number of individuals prescribed stimulants in the past decade, there has been growing concern regarding the risk of cardiovascular events among adults on stimulant therapy. We aimed to quantify the added risk of cardiovascular events by prescription stimulant use and characterize patients who were adversely affected.

Authors

  • Yifang Yan
    The Harold and Inge Marcus Department of Industrial and Manufacturing Engineering, The Pennsylvania State University, University Park, PA, USA.
  • QiuShi Chen
    Section of Pacing and Electrophysiology, Division of Cardiology, First Affiliated Hospital of Nanjing Medical University, Guangzhou Road 300, Nanjing, 210006, Jiangsu, China.
  • Rafay Nasir
    Department of Family and Community Medicine, The Pennsylvania State University, Hershey, PA, USA.
  • Paul Griffin
    Regenstrief Center for Healthcare Engineering, Purdue University, West Lafayette, IN, USA.
  • Curtis Bone
    Department of Family and Community Medicine, The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.
  • Wen-Jan Tuan
    Department of Family and Community Medicine, The Pennsylvania State University, Hershey, PA, USA.

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