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A pilot study to identify pharmacogenomic and clinical risk factors associated with opioid related falls and adverse
Sophia Sheikh1, Rosemarie Fernandez2, Carmen Smotherman3
1Department of Emergency Medicine, University of Florida College of Medicine-Jacksonville, Jacksonville, Florida, USA.
Abstract:
Given the high prevalence of pain in older adults and current trends in opioid prescribing, inclusion of genetic information in risk prediction tools may improve opioid risk assessment. Our objectives were to (1) determine the feasibility of recruiting socioeconomically disadvantaged and racially diverse middle aged and older adult populations for a study seeking to identify risk factors for opioid-related falls and other serious adverse effects and (2) explore potential associations between the Risk Index for Overdose or Serious Opioid-induced Respiratory Depression (CIP-RIOSORD) risk class and other patient factors with falls and serious opioid adverse effects. This was an observational study of 44 participants discharged home from the emergency department with an opioid prescription for acute pain and followed for 30 days. We found pain interference may predict opioid-related falls or serious adverse effects within older, opioid-treated patients. If validated, pain interference may prove to be a beneficial marker for risk stratification of older adults initiated on opioids for acute pain.
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