Hospitalization, Overdose, and Mortality After Opioid Prescriptions Tied to Ophthalmic Surgery.

PURPOSE: Opioid prescriptions continue to carry significant short- and long-term systemic risks, even after ophthalmic surgery. The goal of this study was to identify any association of opioid prescription, after ophthalmic surgery, with postoperative hospitalization, opioid overdose, opioid dependence, and all-cause mortality. DESIGN: Retrospective, cross-sectional analysis. PARTICIPANTS: Patients undergoing an ophthalmic surgery in the OptumLabs Data Warehouse. METHODS: We used deidentified administrative claims data from the OptumLabs Data Warehouse to create 3 cohorts of patients for analysis from January 1, 2016, to June 30, 2022. The first cohort consisted of 1-to-1 propensity score-matched patients who had undergone ophthalmic surgery and had filled a prescription for an opioid and not filled a prescription for an opioid. The second cohort consisted of patients who were considered opioid naïve and had filled a prescription for an opioid matched to patients who had not filled a prescription for an opioid. The last cohort consisted of opioid-naïve patients matched across the following morphine milligram equivalents (MME) groups: ≤ 40, 41-80, and > 80. MAIN OUTCOME MEASURES: Short- and long-term risks of hospitalization, opioid overdose, opioid dependency/abuse, and death were compared between the cohorts. RESULTS: We identified 1 577 692 patients who had undergone an ophthalmic surgery, with 312 580 (20%) filling an opioid prescription. Among all patients, filling an opioid prescription after an ophthalmic surgery was associated with increased mortality (hazard rate [HR], 1.28; 95% confidence interval [CI], 1.25-1.31; P < 0.001), hospitalization (HR, 1.51; 95% CI, 1.49-1.53; P < 0.001), opioid overdose (HR, 7.31; 95% CI, 6.20-8.61, P < 0.001), and opioid dependency (HR, 13.05; 95% CI, 11.48-14.84; P < 0.001) compared with no opioid prescription. Furthermore, we found that higher MME doses of opioids were associated with higher rates of mortality, hospitalization, and abuse/dependence. CONCLUSIONS: Patients who filled an opioid prescription after an ophthalmic surgery experienced higher rates of mortality, hospitalization, episodes of opioid overdose, and opioid dependence compared with patients who did not fill an opioid prescription. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found after the references.

Firearm-Related Injuries and the US Opioid and Other Substance Use Epidemic: A Nationwide Evaluation of Emergency Department Encounters.

INTRODUCTION: There has been a sharp climb in the Unites States' death rate among opioid and other substance abuse patients, as well as an increased prevalence in gun violence. We aimed to investigate the association between substance abuse and gun violence in a national sample of patients presenting to US emergency departments (EDs). METHODS: We queried the 2018-2019 Nationwide Emergency Department Sample for patients ≥18 years with substance abuse disorders (opioid and other) using International Classification of Diseases, 10th Revision, Clinical Modification codes. Within this sample, we analyzed characteristics and outcomes of patients with firearm-related injuries. The primary outcome was mortality; secondary outcomes were ED charges and length of stay. RESULTS: Among the 25.2 million substance use disorder (SUD) patients in our analysis, 35,306 (0.14%) had a firearm-related diagnosis. Compared to other SUD patients, firearm-SUD patients were younger (33.3 versus 44.7 years, P < 0.001), primarily male (88.6% versus 54.2%, P < 0.001), of lower-income status (0-25th percentile income: 56.4% versus 40.5%, P < 0.001), and more likely to be insured by Medicaid or self-pay (71.6% versus 53.2%, P < 0.001). Firearm-SUD patients had higher mortality (1.4% versus 0.4%, P < 0.001), longer lengths of stay (6.5 versus 4.9 days, P < 0.001), and higher ED charges ($9269 versus $5,164, P < 0.001). Firearm-SUD patients had a 60.3% rate of psychiatric diagnoses. Firearm-SUD patients had 5.5 times greater odds of mortality in adjusted analyses (adjusted odds ratio: 5.5, P < 0.001). CONCLUSIONS: Opioid-substance abuse patients with firearm injuries have higher mortality rates and costs among these groups, with limited discharge to postacute care resources. All these factors together point to the urgent need for improved screening and treatment for this vulnerable group of patients.

Contemporary burden and trends of opioid-overdose mortality in New York State.

BACKGROUND: Limited research exists on contemporary opioid overdose mortality burden and trends in New York State, with most studies focusing on New York City. This study aimed to assess opioid overdose burden and death trends in New York State by age, sex, race/ethnicity, geographic area, opioid type, and overdose intent from 1999 to 2020. METHODS: Mortality data were obtained from the Centers for Disease Control and Prevention's WONDER database. Opioid overdose decedents were identified using relevant International Classification of Diseases, 10th Revision codes. Joinpoint regression analyzed trends, estimating annual and average annual percentage changes in age-adjusted mortality rates (AAMR). 95% confidence intervals were derived using the Parametric Method. RESULTS: From 1999 to 2020, New York State recorded 34,109 opioid overdose deaths (AAMR = 7.9 per 100,000 persons; 95% CI: 7.8-7.9). The overall trend increased by 12.6% per year (95% CI: 10.8, 14.4) from 2004 to 2020. Subgroups exhibited varying trends, with an 11.1% yearly increase among Non-Hispanic White persons from 2007 to 2020 (95% CI: 9.0, 13.2), a 24.6% annual rise among Non-Hispanic Black persons from 2012 to 2020 (95% CI: 17.7, 31.8), and an 18.3% increase yearly among Hispanic individuals from 2011 to 2020 (95% CI: 14.0, 22.9). Recent trends have worsened in both males and females, across all age groups, in both New York City (NYC) and areas outside NYC, and for heroin, natural and semisynthetic opioids, and synthetic opioids. CONCLUSIONS: Opioid overdose mortality in New York State has worsened significantly in the last two decades. Further research is essential to identify driving factors for targeted public health interventions.

Association between opioid use disorder and palliative care: a cohort study using linked health administrative data in Ontario, Canada.

BACKGROUND: People with opioid use disorder (OUD) are at risk of premature death and can benefit from palliative care. We sought to compare palliative care provision for decedents with and without OUD. METHODS: We conducted a cohort study using health administrative databases in Ontario, Canada, to identify people who died between July 1, 2015, and Dec. 31, 2021. The exposure was OUD, defined as having emergency department visits, hospital admissions, or pharmacologic treatments suggestive of OUD within 3 years of death. Our primary outcome was receipt of 1 or more palliative care services during the last 90 days before death. Secondary outcomes included setting, initiation, and intensity of palliative care. We conducted a secondary analysis excluding sudden deaths (e.g., opioid toxicity, injury). RESULTS: Of 679 840 decedents, 11 200 (1.6%) had OUD. Compared with people without OUD, those with OUD died at a younger age and were more likely to live in neighbourhoods with high marginalization indices. We found people with OUD were less likely to receive palliative care at the end of their lives (adjusted relative risk [RR] 0.84, 95% confidence interval [CI] 0.82-0.86), but this difference did not exist after excluding people who died suddenly (adjusted RR 0.99, 95% CI 0.96-1.01). People with OUD were less likely to receive palliative care in clinics and their homes regardless of cause of death. INTERPRETATION: Opioid use disorder can be a chronic, life-limiting illness, and people with OUD are less likely to receive palliative care in communities during the 90 days before death. Health care providers should receive training in palliative care and addiction medicine to support people with OUD.

The effect of opioid use on traffic fatalities.

We use a difference-in-differences design to study the effect of opioid use on traffic fatalities. Following Alpert et al., we focus on the 1996 introduction and marketing of OxyContin, and we examine its long-term impacts on traffic fatalities involving Schedule II drugs or heroin. Based on the national fatal vehicle crash database, we find that the states heavily targeted by the initial marketing of OxyContin (i.e., non-triplicate states) experienced 2.4 times more traffic fatalities (1.6 additional deaths per million individuals) involving Schedule II drugs or heroin during 2011-2019, when overdose deaths from heroin and fentanyl became more prominent. We find no difference in traffic fatalities until after the mid-2000s between states with and without a triplicate prescription program. The effect is mainly concentrated in fatal crashes with drug involvement of drivers ages between 25 and 44. Our results highlight additional long-term detrimental consequences of the introduction and marketing of OxyContin.

A simple heuristic for allocating opioid settlement funding to reduce overdose mortality in the United States.

As resolution for opioid-related claims and litigation against pharmaceutical manufacturers and other stakeholders, state and local governments are newly eligible for millions of dollars of settlement funding to address the overdose crisis in the United States. To inform effective use of opioid settlement funds, we propose a simple framework that highlights the principal determinants of overdose mortality: the number of people at risk of overdose each year, the average annual number of overdoses per person at risk, and the average probability of death per overdose event. We assert that the annual number of overdose deaths is a function of these three determinants, all of which can be modified through public health intervention. Our proposed heuristic depicts how each of these drivers of drug-related mortality - and the corresponding interventions designed to address each term - operate both in isolation and in conjunction. We intend for this framework to be used by policymakers as a tool for identifying and evaluating public health interventions and funding priorities that will most effectively address the structural forces shaping the overdose crisis and reduce overdose deaths.

Reducing overdose deaths among persons with opioid use disorder in connecticut.

BACKGROUND: People in Connecticut are now more likely to die of a drug-related overdose than a traffic accident. While Connecticut has had some success in slowing the rise in overdose death rates, substantial additional progress is necessary. METHODS: We developed, verified, and calibrated a mechanistic simulation of alternative overdose prevention policy options, including scaling up naloxone (NLX) distribution in the community and medications for opioid use disorder (OUD) among people who are incarcerated (MOUD-INC) and in the community (MOUD-COM) in a simulated cohort of people with OUD in Connecticut. We estimated how maximally scaling up each option individually and in combinations would impact 5-year overdose deaths, life-years, and quality-adjusted life-years. All costs were assessed in 2021 USD, employing a health sector perspective in base-case analyses and a societal perspective in sensitivity analyses, using a 3% discount rate and 5-year and lifetime time horizons. RESULTS: Maximally scaling NLX alone reduces overdose deaths 20% in the next 5 years at a favorable incremental cost-effectiveness ratio (ICER); if injectable rather than intranasal NLX was distributed, 240 additional overdose deaths could be prevented. Maximally scaling MOUD-COM and MOUD-INC alone reduce overdose deaths by 14% and 6% respectively at favorable ICERS. Considering all permutations of scaling up policies, scaling NLX and MOUD-COM together is the cost-effective choice, reducing overdose deaths 32% at ICER $19,000/QALY. In sensitivity analyses using a societal perspective, all policy options were cost saving and overdose deaths reduced 33% over 5 years while saving society $338,000 per capita over the simulated cohort lifetime. CONCLUSIONS: Maximally scaling access to naloxone and MOUD in the community can reduce 5-year overdose deaths by 32% among people with OUD in Connecticut under realistic budget scenarios. If societal cost savings due to increased productivity and reduced crime costs are considered, one-third of overdose deaths can be reduced by maximally scaling all three policy options, while saving money.

An individual-based dynamic model to assess interventions to mitigate opioid overdose risk.

BACKGROUND: Illicit opioid overdose continues to rise in North America and is a leading cause of death. Mathematical modeling is a valuable tool to investigate the epidemiology of this public health issue, as it can characterize key features of population outcomes and quantify the broader effect of structural and interventional changes on overdose mortality. The aim of this study is to quantify and predict the impact of key harm reduction strategies at differing levels of scale-up on fatal and nonfatal overdose among a population of people engaging in unregulated opioid use in Toronto. METHODS: An individual-based model for opioid overdose was built featuring demographic and behavioural variation among members of the population. Key individual attributes known to scale the risk of fatal and nonfatal overdose were identified and incorporated into a dynamic modeling framework, wherein every member of the simulated population encompasses a set of distinct characteristics that govern demographics, intervention usage, and overdose incidence. The model was parametrized to fatal and nonfatal overdose events reported in Toronto in 2019. The interventions considered were opioid agonist therapy (OAT), supervised consumption sites (SCS), take-home naloxone (THN), drug-checking, and reducing fentanyl in the drug supply. Harm reduction scenarios were explored relative to a baseline model to examine the impact of each intervention being scaled from 0% use to 100% use on overdose events. RESULTS: Model simulations resulted in 3690.6 nonfatal and 295.4 fatal overdoses, coinciding with 2019 data from Toronto. From this baseline, at full scale-up, 290 deaths were averted by THN, 248 from eliminating fentanyl from the drug supply, 124 from SCS use, 173 from OAT, and 100 by drug-checking services. Drug-checking and reducing fentanyl in the drug supply were the only harm reduction strategies that reduced the number of nonfatal overdoses. CONCLUSIONS: Within a multi-faceted harm reduction approach, scaling up take-home naloxone, and reducing fentanyl in the drug supply led to the largest reduction in opioid overdose fatality in Toronto. Detailed model simulation studies provide an additional tool to assess and inform public health policy on harm reduction.

Cause-Specific Mortality among Patients in Treatment for Opioid Use Disorder in Multiple Settings: A Prospective Comparative Cohort Study.

INTRODUCTION: Among people receiving current or previous opioid maintenance treatment (OMT), the leading cause of premature death is an opioid overdose. However, other causes of mortality remain high in this group. An understanding of causes of deaths across multiple settings can be useful in informing more comprehensive prevention responses. The aim of this study was to describe all non-overdose causes of death in three national cohorts (Czechia, Denmark, and Norway) among OMT patients and to explore associations of non-overdose mortality with age and gender. METHODS: This prospective comparative cohort study used national mortality registry databases for OMT patients from Czechia (2000-2019), Denmark (2000-2018), and Norway (2010-2019). Crude mortality rates and age-standardized mortality rates (ASMRs) were calculated as deaths per 1,000 person years for cause-specific mortality. RESULTS: In total, 29,486 patients were included, with 5,322 deaths recorded (18%). We found variations in causes of death among the cohorts and within gender and age groups. The leading non-overdose causes of death were accidents in Czechia and Denmark, and neoplasms in Norway. Cardiovascular deaths were highest in Czechia, particularly for women in OMT (ASMR 3.59 vs. 1.24 in Norway and 1.87 in Denmark). CONCLUSION: This study found high rates of preventable death among both genders and all age groups. Different demographic structures, variations in risk exposure, as well as variations in coding practices can explain the differences. The findings support increased efforts towards screening and preventative health initiatives among OMT patients specific to the demographic characteristics in different settings.

The Fast Track intervention's impact on behaviors of despair in adolescence and young adulthood.

How to mitigate the dramatic increase in the number of self-inflicted deaths from suicide, alcohol-related liver disease, and drug overdose among young adults has become a critical public health question. A promising area of study looks at interventions designed to address risk factors for the behaviors that precede these -often denoted-"deaths of despair." This paper examines whether a childhood intervention can have persistent positive effects by reducing adolescent and young adulthood (age 25) behaviors that precede these deaths, including suicidal ideation, suicide attempts, hazardous drinking, and opioid use. These analyses test the impact and mechanisms of action of Fast Track (FT), a comprehensive childhood intervention designed to decrease aggression and delinquency in at-risk kindergarteners. We find that random assignment to FT significantly decreases the probability of exhibiting any behavior of despair in adolescence and young adulthood. In addition, the intervention decreases the probability of suicidal ideation and hazardous drinking in adolescence and young adulthood as well as opioid use in young adulthood. Additional analyses indicate that FT's improvements to children's interpersonal (e.g., prosocial behavior, authority acceptance), intrapersonal (e.g., emotional recognition and regulation, social problem solving), and academic skills in elementary and middle school partially mediate the intervention effect on adolescent and young adult behaviors of despair and self-destruction. FT's improvements to interpersonal skills emerge as the strongest indirect pathway to reduce these harmful behaviors. This study provides evidence that childhood interventions designed to improve these skills can decrease the behaviors associated with premature mortality.

Opioid Overdose Deaths Among Formerly Incarcerated Persons and the General Population: North Carolina, 2000‒2018.

Objectives. To compare opioid overdose death (OOD) rates among formerly incarcerated persons (FIPs) from 2016 to 2018 with the North Carolina population and with OOD rates from 2000 to 2015. Methods. We performed a retrospective cohort study of 259 861 North Carolina FIPs from 2000 to 2018 linked with North Carolina death records. We used indirectly standardized OOD mortality rates and ratios and present 95% confidence intervals (CIs). Results. From 2017 to 2018, the OOD rates in the North Carolina general population decreased by 10.1% but increased by 32% among FIPs. During 2016 to 2018, the highest substance-specific OOD rate among FIPs was attributable to synthetic narcotics (mainly fentanyl and its analogs), while OOD rates for other opioids were half or less than that from synthetic narcotics. During 2016 to 2018, the OOD risk for FIPs from synthetic narcotics was 50.3 (95% CI = 30.9, 69.6), 20.2 (95% CI = 17.3, 23.2), and 18.2 (95% CI = 15.9, 20.5) times as high as that for the North Carolina population at 2-week, 1-year, and complete follow-up after release, respectively. Conclusions. While nationwide OOD rates declined from 2017 to 2018, OOD rates among North Carolina FIPs increased by about a third, largely from fentanyl and its analogs. (Am J Public Health. 2022;112(2):300-303. https://doi.org/10.2105/AJPH.2021.306621).

Prior use of medications for opioid use disorder in ED patients with opioid overdose: prevalence, misuse and overdose severity.

OBJECTIVES: Medications for opioid use disorder (MOUD) reduce opioid overdose (OD) deaths; however, prevalence and misuse of MOUD in ED patients presenting with opioid overdose are unclear, as are any impacts of existing MOUD prescriptions on subsequent OD severity. METHODS: This was a prospective observational cohort of ED patients with opioid OD at two tertiary-care hospitals from 2015 to 19. Patients with confirmed opioid OD (via urine toxicology) were included, while patients with alternate diagnoses, insufficient data, age < 18, and prisoners were excluded. OD severity was defined using: (a) hospital LOS (days); and (b) in-hospital mortality. Time trends by calendar year and associations between MOUD and study outcomes were calculated. RESULTS: In 2829 ED patients with acute drug OD, 696 with confirmed opioid OD were included. Overall, 120 patients (17%) were previously prescribed any MOUD, and MOUD prevalence was significantly higher in 2018 and 2019 compared to 2016 (20.1% and 27.8% vs. 8.8%, p < 0.05). Odds of MOUD misuse were significantly higher for methadone (OR 3.96 95% CI 2.57-6.12) and lowest for buprenorphine (OR 1.16, p = NS). Mean LOS was over 50% longer for methadone (3.08 days) compared to buprenorphine and naltrexone (both 2.0 days, p = NS). Following adjustment for confounders, buprenorphine use was associated with significantly shorter LOS (IRR -0.44 (95%CI -0.85, -0.04)). Odds of death were 30% lower for patients on any MOUD (OR 0.70, 95%CI 0.09-5.72), but highest in the methadone group (OR 0.82, 95%CI 0.10-6.74). CONCLUSIONS: While MOUD prevalence significantly increased over the study period, MOUD misuse occurred for patients taking methadone, and OD LOS overall was lower in patients with any prior buprenorphine prescription.

History of Methadone and Buprenorphine Opioid Agonist Therapy Among People Who Died of an Accidental Opioid-Involved Overdose: Rhode Island, January 1, 2018-June 30, 2020.

To guide intervention efforts, we identified the proportion of individuals previously engaged in opioid agonist therapy among people who died of an accidental opioid-involved overdose. Most individuals (60.9%) had never received any prior buprenorphine or methadone treatment. Individuals who died of an overdose in 2020 had a similar demographic profile and treatment history compared with prior years. To prevent additional accidental opioid-involved overdose deaths, efforts should be directed toward linking individuals to care.

Accounting for confounding by time, early intervention adoption, and time-varying effect modification in the design and analysis of stepped-wedge designs: application to a proposed study design to reduce opioid-related mortality.

BACKGROUND: Beginning in 2019, stepped-wedge designs (SWDs) were being used in the investigation of interventions to reduce opioid-related deaths in communities across the United States. However, these interventions are competing with external factors such as newly initiated public policies limiting opioid prescriptions, media awareness campaigns, and the COVID-19 pandemic. Furthermore, control communities may prematurely adopt components of the intervention as they become available. The presence of time-varying external factors that impact study outcomes is a well-known limitation of SWDs; common approaches to adjusting for them make use of a mixed effects modeling framework. However, these models have several shortcomings when external factors differentially impact intervention and control clusters. METHODS: We discuss limitations of commonly used mixed effects models in the context of proposed SWDs to investigate interventions intended to reduce opioid-related mortality, and propose extensions of these models to address these limitations. We conduct an extensive simulation study of anticipated data from SWD trials targeting the current opioid epidemic in order to examine the performance of these models in the presence of external factors. We consider confounding by time, premature adoption of intervention components, and time-varying effect modification- in which external factors differentially impact intervention and control clusters. RESULTS: In the presence of confounding by time, commonly used mixed effects models yield unbiased intervention effect estimates, but can have inflated Type 1 error and result in under coverage of confidence intervals. These models yield biased intervention effect estimates when premature intervention adoption or effect modification are present. In such scenarios, models incorporating fixed intervention-by-time interactions with an unstructured covariance for intervention-by-cluster-by-time random effects result in unbiased intervention effect estimates, reach nominal confidence interval coverage, and preserve Type 1 error. CONCLUSIONS: Mixed effects models can adjust for different combinations of external factors through correct specification of fixed and random time effects. Since model choice has considerable impact on validity of results and study power, careful consideration must be given to how these external factors impact study endpoints and what estimands are most appropriate in the presence of such factors.

Chronic Opioid Use and Central Sleep Apnea, Where Are We Now and Where To Go? A State of the Art Review.

Opioids are commonly used for pain management, perioperative procedures, and addiction treatment. There is a current opioid epidemic in North America that is paralleled by a marked increase in related deaths. Since 2000, chronic opioid users have been recognized to have significant central sleep apnea (CSA). After heart failure-related Cheyne-Stokes breathing (CSB), opioid-induced CSA is now the second most commonly seen CSA. It occurs in around 24% of chronic opioid users, typically after opioids have been used for more than 2 months, and usually corresponds in magnitude to opioid dose/plasma concentration. Opioid-induced CSA events often mix with episodes of ataxic breathing. The pathophysiology of opioid-induced CSA is based on dysfunction in respiratory rhythm generation and ventilatory chemoreflexes. Opioids have a paradoxical effect on different brain regions, which result in irregular respiratory rhythm. Regarding ventilatory chemoreflexes, chronic opioid use induces hypoxia that appears to stimulate an augmented hypoxic ventilatory response (high loop gain) and cause a narrow CO2 reserve, a combination that promotes respiratory instability. To date, no direct evidence has shown any major clinical consequence from CSA in chronic opioid users. A line of evidence suggested increased morbidity and mortality in overall chronic opioid users. CSA in chronic opioid users is likely to be a compensatory mechanism to avoid opioid injury and is potentially beneficial. The current treatments of CSA in chronic opioid users mainly focus on continuous positive airway pressure (CPAP) and adaptive servo-ventilation (ASV) or adding oxygen. ASV is more effective in reducing CSA events than CPAP. However, a recent ASV trial suggested an increased all-cause and cardiovascular mortality with the removal of CSA/CSB in cardiac failure patients. A major reason could be counteracting of a compensatory mechanism. No similar trial has been conducted for chronic opioid-related CSA. Future studies should focus on (1) investigating the phenotypes and genotypes of opioid-induced CSA that may have different clinical outcomes; (2) determining if CSA in chronic opioid users is beneficial or detrimental; and (3) assessing clinical consequences on different treatment options on opioid-induced CSA.

A Retrospective Cohort Study Comparing In-Person and Telemedicine-Based Opioid Agonist Treatment in Ontario, Canada, Using Administrative Health Data.

BACKGROUND: This study evaluated how telemedicine as a modality for opioid agonist treatment compares to in-person care. METHODS: We conducted a retrospective cohort study of patients enrolled in opioid agonist treatment between January 1, 2011, and December 31, 2015, in Ontario, Canada. We compared patients who received opioid agonist treatment predominantly in person, mixed, and predominantly by telemedicine. We used a logistic regression model to evaluate mortality, a Cox proportional hazard model to assess retention, and a negative binomial regression model to evaluate emergency department visits and hospitalizations. The study was performed using administrative health data with physician billing data from the Ontario Health Insurance Plan and prescription data from the Ontario Drug Benefit databases. RESULTS: A total of 55,924 individuals were included in the study. Receiving opioid agonist treatment by predominantly telemedicine was not associated with all-cause mortality (OR = 0.9, 95% CI: 0.8-1.0), 1-year treatment retention (OR = 1.0, 95% CI: 0.9-1.1), or opioid-related emergency department visits and hospitalizations when compared to in-person care. The rate of emergency department visits (IRR = 1.4), the rate of mental health-related emergency department visits (IRR = 1.5), and the rate of mental health-related hospitalizations per year (IRR = 1.2) was higher for patients who received opioid agonist treatment predominantly by telemedicine compared to in person. CONCLUSION: Our findings support the conclusion that telemedicine is equal to in-person care regarding mortality opioid-related emergency department visits and retention, and is a viable option for those seeking opioid agonist treatment.

Effect of Opioids on All-cause Mortality and Opioid Addiction in Total Hip Arthroplasty: a Korea Nationwide Cohort Study.

BACKGROUND: The purpose of this study was to investigate the use of opioids before and after total hip arthroplasty (THA), to find out the effect of opioid use on mortality in patients with THA, and to analyze whether preoperative opioid use is a risk factor for sustained opioid use after surgery using Korean nationwide cohort data. METHODS: This retrospective nationwide study identified subjects from the Korean National Health Insurance Service-Sample cohort (NHIS-Sample) compiled by the Korean NHIS. The index date (time zero) was defined as 90 days after an admission to a hospital to fulfill the eligibility criteria of the THA. RESULTS: In the comparison of death risk according to current use and the defined daily dose of tramadol and strong opioids in each patient group according to past opioid use, there were no statistically significant differences in the adjusted hazard ratio for death compared to the current non-users in all groups (P > 0.05). Past tramadol and strong opioid use in current users increased the risk of the sustained use of tramadol and strong opioids 1.45-fold (adjusted rate ratio [aRR]; 95% confidence interval [CI], 1.12-1.87; P = 0.004) and 1.65-fold (aRR; 95% CI, 1.43-1.91; P < 0.001), respectively, compared to past non-users. CONCLUSION: In THA patients, the use of opioids within 6 months before surgery and within 3 months after surgery does not affect postoperative mortality, but a past-use history of opioid is a risk factor for sustained opioid use. Even after THA, the use of strong opioids is observed to increase compared to before surgery.

Can a Neighborhood Fall Sick? Opioid Addiction, Collective Violence and Currents of Death in Contemporary India.

Opioid abuse is an increasingly global phenomenon. Rather than assuming it to be a uniformly global or neoliberal pathology, how might we better understand comparative and locally specific dimensions of opioid addiction? Working with neighborhoods as a unit of analysis, this article analyzes the striking differences between patterns of addiction and violence in two proximate and seemingly similar urban poor neighborhoods in Delhi, India. Rather than global or national etiologies, I suggest that an attention to sharp ecological variation within epidemics challenges social scientists to offer more fine-grained diagnostics. Using a combination of quantitative and ethnographic methods, I show how heroin addiction and collective violence might be understood as expressions of what Durkheim called "suicido-genetic currents." I suggest the idea of varying currents as an alternative to the sociology of neighborhood "effects" in understanding significant differences in patterns of self-harm and injury across demographically similar localities.

An investigation of demographic and drug-use patterns in fentanyl and carfentanil deaths in Ontario.

The opioid epidemic in Ontario has seen opioid-related deaths double in recent years, from 676 deaths in 2014 to 1,474 in 2018, with an overwhelming prevalence of fentanyl and fentanyl-analogues, such as carfentanil. The presence of drug paraphernalia and a history of drug-use is often a strong indicator of a drug-related death, indicating a need for toxicological analysis. Demographic and drug-related patterns associated with opioid deaths in Ontario from June 2017 to December 2018 (n = 2403) were investigated using data collected from the Coroner's Opioid Investigative Aid (OIA). This work aims to provide insight on how the opioid epidemic affects certain demographics to aid investigators conduct targeted analyses and help public health officials identify vulnerable communities. Chi-square and logistic regressions were conducted to evaluate if age and sex were predictors for the presence of drug paraphernalia, and if drug paraphernalia, sex, age, or history of drug use were associated with causes of deaths (COD). Chi-square analysis revealed that sex (p < 0.001), the presence of drug-use history (p < 0.001), and the presence of drug paraphernalia at the scene of death (p < 0.001) were significantly associated with CODs. Sex was also significantly associated with the presence of drug paraphernalia (p < 0.001). Logistic regression analysis indicated that age (p < 0.001) influenced the probability of opioid-related deaths. Probability models relating age to various opioid-related CODs were also generated. These results demonstrated that fentanyl-related deaths are more associated with males, younger individuals, individuals with a history or drug-use, and the presence of drug paraphernalia.

Economic burden and clinical impact of preoperative opioid dependence for patients undergoing lower extremity bypass surgery.

OBJECTIVE: Surgeons' prescription practices and the opioid epidemic have received significant attention in the media. Limited data exist, however, on the impact of prior or coexistent opioid use on vascular surgery outcomes. This study aimed to quantify the incidence, economic burden, and clinical impact of pre-existing opioid dependency in patients undergoing lower extremity bypass (LEB) surgery. METHODS: Data were collected from 1,132,645 weighted (230,858 unweighted) patient admissions for LEB in the National Inpatient Sample for the years 2002 to 2015. Patients with a concomitant diagnosis of opioid abuse or dependency were identified using International Classification of Diseases, Ninth Revision codes. Matched cohorts of patients with (n = 606 unweighted) and without (n = 32,343 unweighted) opioid dependence were created using coarsened exact matching to control for patient demographics. Linear regression was used to control for hospital-level factors and to identify differential outcomes for patients with opioid dependency. Our primary end points were hospital cost and length of stay. Our secondary end points were surgical complications and in-hospital mortality. RESULTS: There were 1,132,645 (230,858 unweighted) patient admissions for LEB in the National Inpatient Sample during 2002 to 2015. There were 3190 (0.3%) patients (643 unweighted) who had a diagnosis of pre-existing opioid dependency. The incidence of opioid dependency rose over time (2002, 0.13%; 2015, 0.63%; R2 = 0.90; P < .001). Before matching, opioid-dependent patients were younger (53.9 ± 12.3 years vs 66.7 ± 12.1 years; P < .001) and more likely to be male (65.2% vs 61.9%; P < .001), to be nonwhite (37.9% vs 24.1%; P < .001), to pay with Medicaid (29.6% vs 7.4%; P < .001), and to fall in the lowest income quartile based on ZIP code (39.6% vs 27.5%; P < .001). After matching, opioid-dependent patients (n = 606 unweighted vs n = 32,343 unweighted nonopioid-dependent patients) were at increased risk of surgical site infections (odds ratio [OR], 1.61; P = .006), major bleeding (OR, 1.56; P = .04), acute kidney injury (OR, 1.46; P = .02), and deep venous thrombosis (OR, 2.53; P = .005). Linear regression of matched cohorts revealed that opioid-dependent patients had an increased length of hospital stay (11.76 days vs 9.80 days; P < .001) and an increased mean inflation-adjusted in-hospital cost of U.S. $7032 ($37,522 vs $30,490; P < .001). CONCLUSIONS: The incidence of pre-existing opioid dependency in patients undergoing LEB continues to rise. Patients with opioid use disorder undergoing LEB surgery have substantial increases in length of hospital stay and costs. These findings highlight the importance of early preoperative recognition of this disorder in vascular surgery patients and open the opportunity for early intervention in that cohort.