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      Association Between Opioid Dose Variability and Opioid Overdose Among Adults Prescribed Long-term Opioid Therapy

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          Key Points

          Question

          Among individuals prescribed long-term opioid therapy, is variability in opioid dose associated with an increased risk of overdose?

          Findings

          In this nested case-control study that included 228 case patients who experienced an opioid overdose and 3547 control patients who did not experience an opioid overdose, high variability in opioid dose was associated with a greater than 3-fold increased risk of opioid overdose even after controlling for dose.

          Meaning

          The findings suggest that when managing long-term opioid therapy, practitioners should consider the risk of overdose associated with dose variability.

          Abstract

          This nested case-control study of adults prescribed long-term opioid therapy examines the association between opioid dose variability and opioid overdose.

          Abstract

          Importance

          Attempts to discontinue opioid therapy to reduce the risk of overdose and adhere to prescribing guidelines may lead patients to be exposed to variability in opioid dosing. Such dose variability may increase the risk of opioid overdose even if therapy discontinuation is associated with a reduction in risk.

          Objective

          To examine the association between opioid dose variability and opioid overdose.

          Design, Setting, and Participants

          A nested case-control study was conducted in a large Colorado integrated health plan and delivery system from January 1, 2006, through June 30, 2018. Cohort members were individuals prescribed long-term opioid therapy.

          Exposures

          Dose variability was defined as the SD of the milligrams of morphine equivalents across each patient’s follow-up and categorized based on the quintile distribution of the SD in the cohort (0-5.3, 5.4-9.1, 9.2-14.6, 14.7-27.2, and >27.2 mg of morphine equivalents).

          Main Outcomes and Measures

          Opioid overdose cases were identified using International Classification of Diseases, Ninth Revision and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes. Each case patient with overdose was matched to up to 20 control patients using risk set sampling. Conditional logistic regression models were used to generate matched odds ratios and 95% CIs, adjusted for age, sex, race/ethnicity, drug or alcohol use disorder, tobacco use, benzodiazepine dispensings, medical comorbidities, mental health disorder, opioid dose, and opioid formulation.

          Results

          In a cohort of 14 898 patients (mean [SD] age, 56.3 [16.0] years; 8988 [60.3%] female) prescribed long-term opioid therapy, 228 case patients with incident opioid overdose were matched to 3547 control patients. The mean (SD) duration of opioid therapy was 36.7 (33.7) months in case patients and 33.0 (30.9) months in control patients. High-dose variability (SD >27.2 mg of morphine equivalents) was associated with a significantly increased risk of overdose compared with low-dose variability (matched odds ratio, 3.32; 95% CI, 1.63-6.77) independent of opioid dose.

          Conclusions and Relevance

          Variability in opioid dose may be a risk factor for opioid overdose, suggesting that practitioners should seek to minimize dose variability when managing long-term opioid therapy.

          Related collections

          Most cited references27

          • Record: found
          • Abstract: found
          • Article: not found

          Heart rate variability: measurement and clinical utility.

          Electrocardiographic RR intervals fluctuate cyclically, modulated by ventilation, baroreflexes, and other genetic and environmental factors that are mediated through the autonomic nervous system. Short term electrocardiographic recordings (5 to 15 minutes), made under controlled conditions, e.g., lying supine or standing or tilted upright can elucidate physiologic, pharmacologic, or pathologic changes in autonomic nervous system function. Long-term, usually 24-hour recordings, can be used to assess autonomic nervous responses during normal daily activities in health, disease, and in response to therapeutic interventions, e.g., exercise or drugs. RR interval variability is useful for assessing risk of cardiovascular death or arrhythmic events, especially when combined with other tests, e.g., left ventricular ejection fraction or ventricular arrhythmias.
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            • Abstract: found
            • Article: not found

            Mortality after prison release: opioid overdose and other causes of death, risk factors, and time trends from 1999 to 2009.

            Among former prisoners, a high rate of death has been documented in the early postrelease period, particularly from drug-related causes. Little is known about risk factors and trends in postrelease mortality in the past decade, especially given general population increases in overdose deaths from pharmaceutical opioids. To determine postrelease mortality between 1999 and 2009; cause-specific mortality rates; and whether sex, calendar year, and custody factors were risk factors for all-cause, overdose, and opioid-related deaths. Cohort study. Prison system of the Washington State Department of Corrections. 76 208 persons released from prison. Identities were linked probabilistically to the National Death Index to identify deaths and causes of death, and mortality rates were calculated. Cox proportional hazards regression estimated the effect of age, sex, race or ethnicity, whether the incarceration resulted from a violation of terms of the person's community supervision, length of incarceration, release type, and calendar year on the hazard ratio (HR) for death. The all-cause mortality rate was 737 per 100 000 person-years (95% CI, 708 to 766) (n = 2462 deaths). Opioids were involved in 14.8% of all deaths. Overdose was the leading cause of death (167 per 100 000 person-years [CI, 153 to 181]), and overdose deaths in former prisoners accounted for 8.3% of the overdose deaths among persons aged 15 to 84 years in Washington from 2000 to 2009. Women were at increased risk for overdose (HR, 1.38 [CI, 1.12 to 1.69]) and opioid-related deaths (HR, 1.39 [CI, 1.09 to 1.79]). The study was done in only 1 state. Innovation is needed to reduce the risk for overdose among former prisoners. National Institute on Drug Abuse and the Robert Wood Johnson Foundation.
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              • Article: not found

              Opioid Prescribing in the United States Before and After the Centers for Disease Control and Prevention's 2016 Opioid Guideline

              Background: In response to adverse outcomes from prescription opioids, the Centers for Disease Control and Prevention (CDC) released the Guideline for Prescribing Opioids for Chronic Pain in March 2016. Objective: To test the hypothesis that the CDC guideline release corresponded to declines in specific opioid prescribing practices. Design: Interrupted time series analysis of monthly prescribing measures from the IQVIA transactional data warehouse and Real-World Data Longitudinal Prescriptions population-level estimates based on retail pharmacy data. Population size was determined by U.S. Census monthly estimates. Setting: United States, 2012 to 2017. Patients: Persons prescribed opioid analgesics. Measurements: Outcomes included opioid dosage, days supplied, overlapping benzodiazepine prescriptions, and the overall rate of prescribing. Results: The rate of high-dosage prescriptions (≥90 morphine equivalent milligrams per day) was 683 per 100 000 persons in January 2012 and declined by 3.56 (95% CI, −3.79 to −3.32) per month before March 2016 and by 8.00 (CI, −8.69 to −7.31) afterward. Likewise, the percentage of patients with overlapping opioid and benzodiazepine prescriptions was 21.04% in January 2012 and declined by 0.02% (CI, −0.04% to −0.01%) per month before the CDC guideline release and by 0.08% (CI, −0.08% to −0.07%) per month afterward. The overall opioid prescribing rate was 6577 per 100 000 persons in January 2012 and declined by 23.48 (CI, −26.18 to −20.78) each month before the guideline release and by 56.74 (CI, −65.96 to −47.53) per month afterward. Limitation: No control population; inability to determine the appropriateness of opioid prescribing. Conclusion: Several opioid prescribing practices were decreasing before the CDC guideline, but the time of its release was associated with a greater decline. Guidelines may be effective in changing prescribing practices. Primary Funding Source: CDC.
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                Author and article information

                Journal
                JAMA Netw Open
                JAMA Netw Open
                JAMA Netw Open
                JAMA Network Open
                American Medical Association
                2574-3805
                19 April 2019
                April 2019
                19 April 2019
                : 2
                : 4
                : e192613
                Affiliations
                [1 ]Institute for Health Research, Kaiser Permanente Colorado, Aurora
                [2 ]Department of Epidemiology, Colorado School of Public Health, Aurora
                [3 ]Department of Biostatistics and Informatics, Colorado School of Public Health, Aurora
                [4 ]Colorado Permanente Medical Group, Aurora
                [5 ]Division of General Internal Medicine, Department of Medicine, University of Colorado School of Medicine, Aurora
                Author notes
                Article Information
                Accepted for Publication: March 4, 2019.
                Published: April 19, 2019. doi:10.1001/jamanetworkopen.2019.2613
                Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2019 Glanz JM et al. JAMA Network Open.
                Corresponding Author: Jason M. Glanz, PhD, Institute for Health Research, Kaiser Permanente Colorado, 2550 S Parker Rd, Ste 200, Aurora, CO 80014 ( jason.m.glanz@ 123456kp.org ).
                Author Contributions: Drs Glanz and Binswanger served as co–first authors, each with equal contribution to this work. Drs Glanz and Binswanger had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
                Concept and design: Glanz, Binswanger, Xu.
                Acquisition, analysis, or interpretation of data: All authors.
                Drafting of the manuscript: Glanz, Binswanger, Xu.
                Critical revision of the manuscript for important intellectual content: All authors.
                Statistical analysis: Glanz, Binswanger, Xu.
                Obtained funding: Glanz, Binswanger.
                Supervision: Glanz, Xu.
                Conflict of Interest Disclosures: Dr Binswanger reported receiving royalties for educational content on the health of incarcerated persons from UpToDate. No other disclosures were reported.
                Funding/Support: Research reported in this publication was supported by award 1R56DA044302 from the National Institute on Drug Abuse, National Institutes of Health.
                Role of the Funder/Sponsor: The National Institutes of Health had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
                Disclaimer: The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute on Drug Abuse or the National Institutes of Health. All information and materials in this article are original.
                Additional Contributions: Jo Ann Shoup, PhD, and Kris Wain, MS, Institute for Health Research, Kaiser Permanente Colorado, Aurora, provided project management and data assistance. Their activities were supported by the grant.
                Article
                zoi190116
                10.1001/jamanetworkopen.2019.2613
                6481879
                31002325
                084b7475-a895-44a4-9049-aded6e2ab9c2
                Copyright 2019 Glanz JM et al. JAMA Network Open.

                This is an open access article distributed under the terms of the CC-BY License.

                History
                : 14 December 2018
                : 27 February 2019
                : 4 March 2019
                Categories
                Research
                Original Investigation
                Online Only
                Substance Use and Addiction

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