WEDNESDAY, Jan. 9, 2019 — Specialized smartphone software can be used to detect early signs of opioid overdose, according to research published in the Jan. 9 issue of Science Translational Medicine.
Rajalakshmi Nandakumar, from the University of Washington in Seattle, and colleagues present a proof-of-concept contactless system that converts a smartphone into a short-range active sonar that uses frequency shifts to identify respiratory depression, apnea, and gross motor movements associated with acute opioid toxicity. Algorithms were developed and tested in two environments: an approved supervised injection facility (SIF) where people self-inject illicit opioids and the operating room (OR) where rapid, opioid-induced overdose events are simulated using routine induction of general anesthesia.
The researchers found that the system identified postinjection, opioid-induced central apnea with a sensitivity and specificity of 96 and 98 percent, respectively, among 209 patients in the SIF; respiratory depression was identified with 87 and 89 percent sensitivity and specificity, respectively. These two events frequently precede fatal opioid overdose. The algorithm identified 19 of 20 simulated overdose events in the OR.
“When the app detects decreased or absent breathing, we’d like it to send an alarm asking the person to interact with it,” a coauthor said in a statement. “Then if the person fails to interact with it, that’s when we say: ‘OK this is a stage where we need to alert someone,’ and the phone can contact someone with naloxone.”
All authors are listed as inventors on a U.S. provisional patent related to this work.
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Posted: January 2019
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