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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
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1 to 2 of 2 Research Studies DisplayedYunusa I, Gagne JJ, Yoshida K
Risk of opioid overdose associated with concomitant use of oxycodone and selective serotonin reuptake inhibitors.
Oxycodone is a potent prescription opioid. Some Selective Serotonin Reuptake Inhibitors (SSRIs) inhibit oxycodone metabolism in the body, but the clinical consequences of this interaction on overdose risk have not been adequately determined. The study researchers compared the rates of opioid overdoses in patients who had initiated oxycodone while taking enzyme-inhibiting SSRIs with the overdose rates of patents who had initiated oxycodone while taking non-enzyme inhibiting SSRIs. Data from 3 U.S. health insurance databases was used to analyze a cohort of adults who initiated oxycodone while receiving SSRI therapy between the years 2000 and 2020. Of the total of 2,037,490 who initiated oxycodone, 69.6% were receiving SSRIs at the time of the initiation of the oxycodone. One-thousand-thirty-five overdose events were observed during this time, and the resulting incidence rate in those initiating oxycodone while using enzyme-inhibiting SSRI’s was higher than in those using other SSRIs. The researchers concluded that in the study cohort of U.S. adults, there is a small increased risk of opioid overdose when initiating oxycodone in patients taking enzyme-inhibiting SSRIs.
AHRQ-funded; HS027623.
Citation: Yunusa I, Gagne JJ, Yoshida K .
Risk of opioid overdose associated with concomitant use of oxycodone and selective serotonin reuptake inhibitors.
JAMA Netw Open 2022 Feb;5(2):e220194. doi: 10.1001/jamanetworkopen.2022.0194..
Keywords: Opioids, Medication, Risk, Depression, Adverse Drug Events (ADE), Adverse Events
Parthipan A, Banerjee I, Humphreys K
Predicting inadequate postoperative pain management in depressed patients: a machine learning approach.
Researchers employed a machine-learning approach to identify patients who were prescribed a combination of selective serotonin reuptake inhibitors (SSRIs) and prodrug opioids in order to examine the effect of this combination on postoperative pain control. They identified patients who received surgery over a 9-year period by using EHR data from an academic medical center, then developed and validated natural language processing (NLP) algorithms to extract depression-related information from both structured and unstructured data elements. The machine-learning algorithm accurately predicted the increase or decrease of the discharge, 3-week, and 8-week follow-up pain scores when compared to the pre-operative pain score; pre-operative pain, surgery type, and opioid tolerance were the strongest predictors of postoperative pain control. The researchers conclude that their study results provide the first direct clinical evidence that the known ability of SSRIs to inhibit prodrug opioid effectiveness is associated with worse pain control among depressed patients. They suggest that prescribers might choose direct acting opioids such as oxycodone or morphine for depressed patients on SSRIs instead of prodrug opioids.
AHRQ-funded; HS024096.
Citation: Parthipan A, Banerjee I, Humphreys K .
Predicting inadequate postoperative pain management in depressed patients: a machine learning approach.
PLoS One 2019 Feb 6;14(2):e0210575. doi: 10.1371/journal.pone.0210575..
Keywords: Care Management, Depression, Medication, Opioids, Pain, Surgery