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Article
Classification of Pain Dynamics in Sickle Cell Disease from Mobile App Reporting
Blood
  • Gary Nave
  • Swati Padhee, Wright State University - Main Campus
  • Amanuel Alambo, Wright State University - Main Campus
  • Kumar Utkarsh
  • Tanvi Banerjee, Wright State University - Main Campus
  • Nirmish Shah
  • Daniel M. Abrams
Document Type
Poster
Publication Date
11-5-2021
Identifier/URL
136361485 (Orcid)
Disciplines
Abstract

Sickle Cell Disease (SCD) is a chronic blood disorder in which complications result from vaso-occlusion. Pain is the most common symptom reported in patients with SCD and includes both acute unpredictable pain as well as chronic pain. Chronic pain is clinically defined as having more days with pain than without pain over a period of 6 months. Various classifications systems have been developed to better understand pain phenotypes, however, there is variability in data and groupings of patients. Recent work based on patient-reported outcome data has shown that patients may be classified into three subgroups: infrequent acute pain, limited recent pain with moderate long-term pain, and persistent severe pain. An improved understanding of the ways in which pain dynamics manifest over time will allow patients and medical providers to better manage pain. Using previously-published data which collected self-reported data through a mobile app over 6 months (Clifton et al., 2017, J. Comput. Biol.), we aimed to characterize the different ways in which patients experienced pain over time. In this work, we sought to identify classes of patients based only on their self reported pain levels.

DOI
10.1182/blood-2021-151927
Citation Information
Gary Nave, Swati Padhee, Amanuel Alambo, Kumar Utkarsh, et al.. "Classification of Pain Dynamics in Sickle Cell Disease from Mobile App Reporting" Blood Vol. 138 Iss. Supplement 1 (2021) p. 983 - 984 ISSN: 0006-4971
Available at: http://works.bepress.com/tanvi-banerjee/59/