Nathan K Itoga1, Lindsay A Sceats2, Jordan R Stern2, Matthew W Mell2. 1. Department of Surgery, Stanford University, Stanford, Calif. Electronic address: nitoga@stanford.edu. 2. Department of Surgery, Stanford University, Stanford, Calif.
Abstract
BACKGROUND: Prescription opioids account for 40% of all U.S. opioid overdose deaths, and national efforts have intensified to reduce opioid prescriptions. Little is known about the relationship between peripheral artery disease (PAD) and high-risk opioid use. The objectives of this study were to evaluate this relationship and to assess the impact of PAD treatment on opiate use. METHODS: In this retrospective cohort study, the Truven Health MarketScan database (Truven Health Analytics, Ann Arbor, Mich), a deidentified national private insurance claims database, was queried to identify patients with PAD (two or more International Classification of Diseases, Ninth Revision diagnosis codes of PAD ≥2 months apart, with at least 2 years of continuous enrollment) from 2007 to 2015. Critical limb ischemia (CLI) was defined as the presence of rest pain, ulcers, or gangrene. The primary outcome was high opioid use, defined as two or more opioid prescriptions within a 1-year period. Multivariable analysis was used to determine risk factors for high opioid use. RESULTS: A total of 178,880 patients met the inclusion criteria, 35% of whom had CLI. Mean ± standard deviation follow-up time was 5.3 ± 2.1 years. An average of 24.7% of patients met the high opioid use criteria in any given calendar year, with a small but significant decline in high opioid use after 2010 (P < .01). During years of high opioid use, 5.9 ± 5.5 yearly prescriptions were filled. A new diagnosis of PAD increased high opioid use (21.7% before diagnosis vs 27.3% after diagnosis; P < .001). A diagnosis of CLI was also associated with increased high opioid use (25.4% before diagnosis vs 34.5% after diagnosis; P < .001). Multivariable analysis identified back pain (odds ratio [OR], 1.89; 95% confidence interval [CI], 1.84-1.93; P < .001) and illicit drug use (OR, 1.87; 95% CI, 1.72-2.03; P < .001) as the highest predictors of high opioid use. A diagnosis of CLI was also associated with higher risk (OR, 1.61; 95% CI, 1.57-1.64; P < .001). A total of 43,443 PAD patients (24.3%) underwent 80,816 PAD-related procedures. After exclusion of periprocedural opioid prescriptions (4.9% of all opioid prescriptions), the yearly percentage of high opioid users increased from 25.8% before treatment to 29.6% after treatment (P < .001). CONCLUSIONS: Patients with PAD are at increased risk for high opioid use, with nearly one-quarter meeting described criteria. CLI and treatment for PAD additionally increase high opioid use. In addition to heightened awareness and active opioid management, our findings warrant further investigation into underlying causes and deterrents of high-risk opioid use.
BACKGROUND: Prescription opioids account for 40% of all U.S. opioid overdose deaths, and national efforts have intensified to reduce opioid prescriptions. Little is known about the relationship between peripheral artery disease (PAD) and high-risk opioid use. The objectives of this study were to evaluate this relationship and to assess the impact of PAD treatment on opiate use. METHODS: In this retrospective cohort study, the Truven Health MarketScan database (Truven Health Analytics, Ann Arbor, Mich), a deidentified national private insurance claims database, was queried to identify patients with PAD (two or more International Classification of Diseases, Ninth Revision diagnosis codes of PAD ≥2 months apart, with at least 2 years of continuous enrollment) from 2007 to 2015. Critical limb ischemia (CLI) was defined as the presence of rest pain, ulcers, or gangrene. The primary outcome was high opioid use, defined as two or more opioid prescriptions within a 1-year period. Multivariable analysis was used to determine risk factors for high opioid use. RESULTS: A total of 178,880 patients met the inclusion criteria, 35% of whom had CLI. Mean ± standard deviation follow-up time was 5.3 ± 2.1 years. An average of 24.7% of patients met the high opioid use criteria in any given calendar year, with a small but significant decline in high opioid use after 2010 (P < .01). During years of high opioid use, 5.9 ± 5.5 yearly prescriptions were filled. A new diagnosis of PAD increased high opioid use (21.7% before diagnosis vs 27.3% after diagnosis; P < .001). A diagnosis of CLI was also associated with increased high opioid use (25.4% before diagnosis vs 34.5% after diagnosis; P < .001). Multivariable analysis identified back pain (odds ratio [OR], 1.89; 95% confidence interval [CI], 1.84-1.93; P < .001) and illicit drug use (OR, 1.87; 95% CI, 1.72-2.03; P < .001) as the highest predictors of high opioid use. A diagnosis of CLI was also associated with higher risk (OR, 1.61; 95% CI, 1.57-1.64; P < .001). A total of 43,443 PAD patients (24.3%) underwent 80,816 PAD-related procedures. After exclusion of periprocedural opioid prescriptions (4.9% of all opioid prescriptions), the yearly percentage of high opioid users increased from 25.8% before treatment to 29.6% after treatment (P < .001). CONCLUSIONS: Patients with PAD are at increased risk for high opioid use, with nearly one-quarter meeting described criteria. CLI and treatment for PAD additionally increase high opioid use. In addition to heightened awareness and active opioid management, our findings warrant further investigation into underlying causes and deterrents of high-risk opioid use.
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