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Browsing by Subject "Analgesics, Opioid"
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Item Are Pain Management Questions in Patient Satisfaction Surveys Driving the Opioid Epidemic?(American Public Health Association, 2016-06) Adams, Jerome; Bledsoe, Gregory H.; Armstrong, John H.; Anesthesia, School of MedicineItem Incident and long-term opioid therapy among patients with psychiatric conditions and medications: a national study of commercial health care claims(Wolters Kluwer, 2017-01) Quinn, Patrick D.; Hur, Kwan; Chang, Zheng; Krebs, Erin E.; Bair, Matthew J.; Scott, Eric L.; Rickert, Martin E.; Gibbons, Robert D.; Kroenke, Kurt; D’Onofrio, Brian M.; Medicine, School of MedicineThere is growing evidence that opioid prescribing in the United States follows a pattern in which patients who are at the highest risk of adverse outcomes from opioids are more likely to receive long-term opioid therapy. These patients include, in particular, those with substance use disorders (SUDs) and other psychiatric conditions. This study examined health insurance claims among 10,311,961 patients who filled prescriptions for opioids. Specifically, we evaluated how opioid receipt differed among patients with and without a wide range of preexisting psychiatric and behavioral conditions (ie, opioid and nonopioid SUDs, suicide attempts or other self-injury, motor vehicle crashes, and depressive, anxiety, and sleep disorders) and psychoactive medications (ie, antidepressants, benzodiazepines, hypnotics, mood stabilizers, antipsychotics, and medications used for SUD, tobacco cessation, and attention-deficit/hyperactivity disorder). Relative to those without, patients with all assessed psychiatric conditions and medications had modestly greater odds of subsequently filling prescriptions for opioids and, in particular, substantially greater risk of long-term opioid receipt. Increases in risk for long-term opioid receipt in adjusted Cox regressions ranged from approximately 1.5-fold for prior attention-deficit/hyperactivity disorder medication prescriptions (hazard ratio [HR] = 1.53; 95% confidence interval [CI], 1.48-1.58) to approximately 3-fold for prior nonopioid SUD diagnoses (HR = 3.15; 95% CI, 3.06-3.24) and nearly 9-fold for prior opioid use disorder diagnoses (HR = 8.70; 95% CI, 8.20-9.24). In sum, we found evidence of greater opioid receipt among commercially insured patients with a breadth of psychiatric conditions. Future studies assessing behavioral outcomes associated with opioid prescribing should consider preexisting psychiatric conditions.Item Overdoses in Patients on Opioids: Risks Associated with Mental Health Conditions and Their Treatment(Springer, 2015-08) Bair, Matthew J.; Bohnert, Amy S.; Department of Medicine, IU School of MedicineItem Transcriptional regulation of the mouse mu opioid receptor gene(1997) Liang, YanbinItem Wearable biosensors have the potential to monitor physiological changes associated with opioid overdose among people who use drugs: A proof-of-concept study in a real-world setting(Elsevier, 2021-12-01) Roth, Alexis M.; Tran, Nguyen K.; Cocchiaro, Ben; Mitchell, Allison K.; Schwartz, David G.; Hensel, Devon J.; Ataiants, Janna; Brenner, Jacob; Yahav, Inbal; Lankenau, Stephen E.INTRODUCTION: Wearable biosensors have the potential to monitor physiological change associated with opioid overdose among people who use drugs. METHODS: We enrolled 16 individuals who reported ≥ 4 daily opioid use events within the previous 30 day. Each was assigned a wearable biosensor that measured respiratory rate (RR) and actigraphy every 15 s for 5 days and also completed a daily interview assessing drug use. We describe the volume of RR data collected, how it varied by participant characteristics and drug use over time using repeated measures one-way ANOVA, episodes of acute respiratory depression (≤5 breaths/minute), and self-reported overdose experiences. RESULTS: We captured 1626.4 h of RR data, an average of 21.7 daily hours/participant over follow-up. Individuals with longer injection careers and those engaging in polydrug use captured significantly fewer total hours of respiratory data over follow-up compared to those with shorter injections careers (94.7 vs. 119.9 h, p = 0.04) and injecting fentanyl exclusively (98.7 vs. 119.5 h, p = 0.008), respectively. There were 385 drug use events reported over follow-up. There were no episodes of acute respiratory depression which corresponded with participant reports of overdose experiences. DISCUSSION: Our preliminary findings suggest that using a wearable biosensor to monitor physiological changes associated with opioid use was feasible. However, more sensitive biosensors that facilitate triangulation of multiple physiological data points and larger studies of longer duration are needed.