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Modeling of overdose and naloxone distribution in the setting of fentanyl compared to heroin
Published Web Location
https://doi.org/10.1016/j.drugalcdep.2022.109478Abstract
Background
Fentanyl has replaced most other non-prescribed opioids in much of North America. There is controversy over whether a hypothetical reduced efficacy of naloxone in reversing fentanyl is a major contributor to the coincident rising overdose mortality.Methods
We modified an existing Markov decision analytic model of heroin overdose and naloxone distribution to account for known risks of fentanyl by adjusting overdose risk, the likelihood of death in the event of overdose, and the proportion of cases in which available naloxone was administered in time to prevent death. We assumed near-universal survival when naloxone was administered promptly for heroin or fentanyl overdose, but allowed that to decline in sensitivity analyses for fentanyl. We varied the proportion of use that was fentanyl and adjusted the modified parameters accordingly to estimate mortality as the dominant opioid shifted.Results
Absent naloxone, the annual overdose death rate was 1.0% and 4.1% for heroin and fentanyl, respectively. With naloxone reaching 80% of those at risk, the overdose death rate was 0.7% and 3.6% for heroin and fentanyl, respectively, representing reductions of 26.4% and 12.0%. Monte Carlo simulations resulted in overdose mortality with fentanyl of 3.3-5.2% without naloxone and 2.6-4.9% with naloxone, with 95% certainty. Positing reduced efficacy for naloxone in reversing fentanyl resulted in 3.6% of fentanyl overdose deaths being prevented by naloxone.Conclusions
Heightened risk for overdose and subsequent death, alongside the time-sensitive need for naloxone administration, fully account for increased mortality when fentanyl replaces heroin, assuming optimal pharmacologic efficacy of naloxone.Many UC-authored scholarly publications are freely available on this site because of the UC's open access policies. Let us know how this access is important for you.
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