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A Large-Scale Observational Study on the Temporal Trends and Risk Factors of Opioid Overdose: Real-World Evidence for Better Opioids

By Jianyuan Deng, Wei Hou, Xinyu Dong, Janos Hajagos, Mary Saltz, Joel Saltz, Fusheng Wang

Posted 11 Oct 2020
medRxiv DOI: 10.1101/2020.10.08.20208678

BackgroundThe United States is in the midst of an opioid overdose epidemic. We evaluated the temporal trends and risk factors of inpatient opioid overdose. Based on the opioid overdose patterns, we further examined the innate properties underlying less overdose events. MethodsWe conducted a retrospective cross-sectional study based a large-scale inpatient electronic health records database, Cerner Health Facts(R). We included patients admitted between January 1, 2009 and December 31, 2017. Opioid overdose prevalence by year, demographics and prescription opioid exposures. ResultsA total of 4,720,041 patients with 7,339,480 inpatient encounters were retrieved from Cerner Health Facts(R). Among them, 30.2% patients were aged 65+, 57.0% female, 70.1% Caucasian, 42.3% single, 32.0% from South and 80.8% in urban area. From 2009 to 2017, annual opioid overdose prevalence per 1,000 patients significantly increased from 3.7 to 11.9 with an adjusted odds ratio (aOR): 1.16, 95% confidence interval (CI): [1.15-1.16]. Comparing to the major demographic counterparts above, being in 1) age group: 41-50 (overall aOR 1.36, 95% CI: [1.31-1.40]) or 51-64 (overall aOR 1.35, 95% CI: [1.32-1.39]), marital status: divorced (overall aOR 1.19, 95% CI: [1.15-1.23]), 3) census region: West (overall aOR 1.32, 95% CI: [1.28-1.36]), were significantly associated with higher odds of opioid overdose. Prescription opioid exposures were also associated with increased odds of opioid overdose, such as meperidine (overall aOR 1.09, 95% CI: [1.06-1.13]) and tramadol (overall aOR 2.20. 95% CI: [2.14-2.27]). Examination on the relationships between opioid agonists properties and their association strengths, aORs, in opioid overdose showed that lower aORs values were significantly associated with 1) high molecular weight, 2) negative interaction with multi-drug resistance protein 1 (MDR1) or positive interaction with cytochrome P450 3A4 (CYP3A4) and 3) negative interaction with delta opioid receptor (DOR) or kappa opioid receptor (KOR). ConclusionsThe significant increasing trends of opioid overdose at the inpatient care setting from 2009 to 2017 indicated an ongoing need of efforts to combat the opioid overdose epidemic in the US. Risk factors associated with opioid overdose included patient demographics and prescription opioid exposures. Different prescription opioids were associated with opioid overdose to different extents, indicating a necessity to better differentiate them during prescribing practice. Moreover, there are physicochemical, pharmacokinetic and pharmacodynamic properties underlying less overdose events, which can be utilized to develop better opioids. Key PointsO_LIThere were significant increasing trends of opioid overdose at the US inpatient care setting from 2009 to 2017, showing an ongoing need for opioid overdose prevention. C_LIO_LIDifferent prescription opioids were associated with opioid overdose to different extents, indicating a necessity to differentiate prescription opioids during prescribing. C_LIO_LIThe optimal properties underlying less overdose events mined from the large-scale, real-world electronic health records hold high potential to guide the development of better opioids with reduced overdose effects. C_LI

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