Buprenorphine treatment and clinical outcomes under the opioid use disorder cascade of care.

BACKGROUND: Challenges to engagement and retention on buprenorphine undermine treatment of individuals with opioid use disorder (OUD). Under the OUD Cascade of Care framework, we sought to identify patient characteristics and treatment response associated with superior clinical outcomes. METHODS: A retrospective cohort study of specialty buprenorphine treatment patients entering treatment (n=19,487) based on EHR records from a large multi-state buprenorphine treatment network (2011-2019). Person-level care episodes were evaluated across treatment intake, engagement (i.e. 2+ visits in the month following intake), and retention at 6, 12, and 24 months. Time to achieving 90 days of continuous opioid abstinence was assessed using Cox proportional hazards regressions models and also assessed as a predictor of long-term retention. RESULTS: Most patients engaged (82.4 %), but retention steadily declined over 6-month (38.7 %), 12-month (26.2 %), and 24-month (17.1 %) timepoints. Opioid-positive baseline tests were associated with lower hazards of achieving continuous abstinence for both buprenorphine-positive (aHR=0.33, p<.001) and buprenorphine-negative (aHR=0.49,p<.001) intakes. Opioid abstinence was associated with buprenorphine-positive baseline testing (aHR=1.59,p<.001), especially for those testing opioid-negative (aHR=1.82,p<.001). Patients who achieved and sustained abstinence at 6 months in care were 4.1 and 5.5 times as likely to achieve 12-month and 24-month retention, respectively, compared to patients with intermittent opioid use. CONCLUSION: Treatment discontinuation was concentrated early in care and buprenorphine and opioid status at intake were prognostic of achieving and sustaining abstinence. Early abstinence was associated with higher likelihood of subsequent stage progression. Implementing interventions to support early clinical stability for high-risk patients is critical to improve clinical outcomes.

The role of prescription opioid and cannabis supply policies on opioid overdose deaths.

Mandatory prescription drug monitoring programs and cannabis legalization have been hypothesized to reduce overdose deaths. We examined associations between prescription monitoring programs with access mandates ("must-query PDMPs"), legalization of medical and recreational cannabis supply, and opioid overdose deaths in United States counties in 2013-2020. Using data on overdose deaths from the National Vital Statistics System, we fit Bayesian spatiotemporal models to estimate risk differences and 95% credible intervals (CrI) in county-level opioid overdose deaths associated with enactment of these state policies. Must-query PDMPs were independently associated with on average 0.8 (95% CrI: 0.5, 1.0) additional opioid-involved overdose deaths per 100,000 person-years. Legal cannabis supply was not independently associated with opioid overdose deaths in this time period. Must-query PDMPs enacted in the presence of legal (medical or recreational) cannabis supply were associated with 0.7 (95% CrI: 0.4, 0.9) more opioid-involved deaths, relative to must-query PDMPs without any legal cannabis supply. In a time when overdoses are driven mostly by non-prescribed opioids, stricter opioid prescribing policies and more expansive cannabis legalization were not associated with reduced overdose death rates.

Associations between cannabis policies and state-level specialty cannabis use disorder treatment in the United States, 2004-2019.

BACKGROUND: Cannabis use disorder (CUD) treatment prevalence decreased in the US between 2002 and 2019, yet structural mechanisms for this decrease are poorly understood. We tested associations between cannabis laws becoming effective and self-reported CUD treatment. METHODS: Restricted-use 2004-2019 National Surveys on Drug Use and Health included people ages 12+ classified as needing CUD treatment (i.e., past-year DSM-5-proxy CUD or last/current specialty treatment for cannabis). Time-varying indicators of medical cannabis laws (MCL) with/without cannabis dispensary provisions differentiated state-years before/after laws using effective dates. Multi-level logistic regressions with random state intercepts estimated individual- and state-adjusted CUD treatment odds by MCLs and model-based changes in specialty CUD treatment state-level prevalence. Secondary analyses tested associations between CUD treatment and MCL or recreational cannabis laws (RCL). RESULTS: Using a broad treatment need sample definition in 2004-2014, specialty CUD treatment prevalence decreased by 1.35 (95 % CI = -2.51, -0.18) points after MCL without dispensaries and by 2.15 points (95 % CI = -3.29, -1.00) after MCL with dispensaries provisions became effective, compared to before MCL. Among people with CUD in 2004-2014, specialty treatment decreased only in MCL states with dispensary provisions (aPD = -0.91, 95 % CI = -1.68, -0.13). MCL were not associated with CUD treatment use in 2015-2019. RCL were associated with lower CUD treatment among people classified as needing CUD treatment, but not among people with past-year CUD. CONCLUSIONS: Policy-related reductions in specialty CUD treatment were concentrated in states with cannabis dispensary provisions in 2004-2014, but not 2015-2019, and partly driven by reductions among people without past-year CUD. Other mechanisms (e.g., CUD symptom identification, criminal-legal referrals) could contribute to decreasing treatment trends.

Impact and Equity of New York City's Tobacco Retail Reduction Initiative.

INTRODUCTION: High levels of tobacco retailer density in communities is associated with a range of tobacco use behaviors and is a key structural driver of tobacco-related disparities. This study evaluates the impacts of New York City's (NYC) novel policy intervention to cap tobacco retail licenses on tobacco retailer density levels and neighborhood inequities in tobacco access. METHODS: Using geocoded tobacco retail licensing data from 2010 to 2022, Bayesian conditional autoregressive Poisson panel models estimated the association between policy implementation in 2018 and retailer density per 1,000 population, controlling for neighborhood-level sociodemographic factors. Data were analyzed in 2023. RESULTS: The number of tobacco retail licenses decreased from 9,304 in 2010 to 5,107 in 2022, with the rate of decline significantly accelerating post-policy (-14·2% versus -34·2%). Policy effects were stronger in districts with lower income and greater proportions of non-Hispanic Black residents. CONCLUSIONS: NYC's policy substantially reduced tobacco retailer density and appeared to close longstanding patterns of inequity in tobacco access, serving as a rare example of a tobacco control policy that may effectively reduce tobacco-related disparities. This emergent approach to restructure tobacco retail in communities may reach populations that have not benefitted from traditional tobacco control policies and should be considered by other localities.

Factors impacting parental uptake of COVID-19 vaccination for U.S. Children ages 5-17.

COVID-19 vaccination of U.S. children lags behind adult vaccination, but remains critical in mitigating the pandemic. Using a subset of a nationally representative survey, this study examined factors contributing to parental uptake of COVID-19 vaccine for children ages 12-17 and 5-11, stratified by parental COVID-19 vaccination status. Among vaccinated parents, uptake was higher for 12-17-year-olds (78.6%) than 5-11-year-olds (50.7%); only two unvaccinated parents vaccinated their children. Child influenza vaccination was predictive of uptake for both age groups, while side effect concerns remained significant only for younger children. Although parents were more likely to involve adolescents in vaccine decision-making than younger children, this was not predictive of vaccine uptake. These results highlight the importance of addressing the unique and shared concerns parents have regarding COVID-19 vaccination for children of varying ages. Future work should further explore adolescent/child perspectives of involvement in COVID-19 vaccination decision-making to support developmentally appropriate involvement.

Naloxone expansion is not associated with increases in adolescent heroin use and injection drug use: Evidence from 44 US states.

BACKGROUND: Naloxone distribution is central to ongoing efforts to address the opioid overdose crisis. Some critics contend that naloxone expansion may inadvertently promote high-risk substance use behaviors among adolescents, but this question has not been directly investigated. METHODS: We examined relationships between naloxone access laws and pharmacy naloxone distribution with lifetime heroin and injection drug use (IDU), 2007-2019. Models generating adjusted odds ratios (aOR) and 95% confidence intervals (CI) included year and state fixed effects, controlled for demographics and sources of variation in opioid environments (e.g., fentanyl penetration), as well as additional policies expected to impact substance use (e.g., prescription drug monitoring). Exploratory and sensitivity analyses further examined naloxone law provisions (e.g., third-party prescribing) and applied e-value testing to assess vulnerability to unmeasured confounding. RESULTS: Adoption of any naloxone law was not associated with changes in adolescent lifetime heroin or IDU. For pharmacy dispensing, we observed a small decrease in heroin use (aOR: 0.95 [CI: 0.92, 0.99]) and a small increase in IDU (aOR: 1.07 [CI: 1.02, 1.11]). Exploratory analyses of law provisions suggested that third-party prescribing (aOR: 0.80, [CI: 0.66, 0.96]) and non-patient-specific dispensing models (aOR: 0.78, [CI: 0.61, 0.99]) were associated with decreased heroin use but not decreased IDU. Small e-values associated with the pharmacy dispensing and provision estimates indicate that unmeasured confounding may explain observed findings. CONCLUSION: Naloxone access laws and pharmacy naloxone distribution were more consistently associated with decreases rather than increases in lifetime heroin and IDU among adolescents. Our findings therefore do not support concerns that naloxone access promotes high-risk adolescent substance use behaviors. As of 2019, all US states have adopted legislation to improve naloxone access and facilitate use. However, further removal of adolescent naloxone access barriers is an important priority given that the opioid epidemic continues to affect people of all ages.

Adult Medical Cannabinoid Use and Changes in Prescription Controlled Substance Use.

Introduction: Nonopioid-based strategies for managing chronic noncancer pain are needed to help reduce overdose deaths. Although lab studies and population-level data suggest that cannabinoids could provide opioid-sparing effects, among medical cannabis participants they may also impact overdose risk by modifying other controlled substance use such as sedative hypnotics. However, no study has combined observational data at the individual level to empirically address interactions between the use of cannabinoids and prescribed controlled substances. Methods: Electronic health records, including prescription drug monitoring program data, from a large multisite medical cannabis program in New York State were abstracted for all participants with noncancer pain and recently prescribed noncannabinoid controlled substances who completed a new intake visit from April 15, 2018-April 14, 2019 and who remained actively in treatment for >180 days. Participants were partitioned into two samples: those with recent opioid use and those with active opioid use and co-use of sedative hypnotics. A patient-month level analysis assessed total average equivalent milligrams by class of drug (i.e., cannabinoid distinguishing tetrahydrocannabinol [THC] vs. cannabidiol [CBD], opioids, and sedative-hypnotics) received as a time-varying outcome measure across each 30-day "month" period postintake for at least 6 months for all participants. Results: Sample 1 of 285 opioid users were 61.1 years of age (±13.5), 57.5% female, and using an average of 49.7 (±98.5) morphine equivalents daily at intake. Unadjusted analyses found a modest decline in morphine equivalents to 43.9 mg (±94.1 mg) from 49.7 (±98.5) in month 1 (p=0.047) while receiving relatively low doses of THC (2.93 mg/day) and CBD (2.15 mg/day). Sample 2 of 95 opioid and sedative-hypnotic users were 60.9 years of age (±13.1), 63.2% female, and using an average of 86.6 (±136.2) morphine equivalents daily, and an average of 4.3 (±5.6) lorazepam equivalents. Unadjusted analyses did not find significant changes in either morphine equivalents (p=0.81) or lorazepam equivalents (p=0.980), and patients similarly received relatively low doses of THC (2.32 mg/day) and CBD (2.24 mg/day). Conclusions: Findings demonstrated minimal to no change in either opioids or sedative hypnotics over the 6 months of medical cannabis use but may be limited by low retention rates, external generalizability, and an inability to account for nonprescribed substance use.

Non-prescribed buprenorphine preceding treatment intake and clinical outcomes for opioid use disorder.

OBJECTIVE: Successful retention on buprenorphine improves outcomes for opioid use disorder (OUD); however, we know little about associations between use of non-prescribed buprenorphine (NPB) preceding treatment intake and clinical outcomes. METHODS: The study conducted observational retrospective analysis of abstracted electronic health record (EHR) data from a multi-state nationwide office-based opioid treatment program. The study observed a random sample of 1000 newly admitted patients with OUD for buprenorphine maintenance (2015-2018) for up to 12 months following intake. We measured use of NPB by mandatory intake drug testing and manual EHR coding. Outcomes included hazards of treatment discontinuation and rates of opioid use. RESULTS: Compared to patients testing negative for buprenorphine at intake, those testing positive (59.6%) had lower hazards of treatment discontinuation (HR = 0.52, 95% CI: 0.44, 0.60, p < 0.01). Results were little changed following adjustment for baseline opioid use and other patient characteristics (aHR: 0.60, 95% CI: 0.51, 0.70, p < 0.01). Risk of discontinuation did not significantly differ between patients by buprenorphine source: prescribed v. NPB (reference) at admission (HR = 1.15, 95% CI: 0.90, 1.46). Opioid use was lower in the buprenorphine positive group at admission (25.0% vs. 53.1%, p < 0.0001) and throughout early months of treatment but converged after 7 months for those remaining in care (17.1% vs. 16.5%, p = 0.89). CONCLUSION: NPB preceding treatment intake was associated with decreased hazards of treatment discontinuation and lower opioid use. These findings suggest use of NPB may be a marker of treatment readiness and that buprenorphine testing at intake may have predictive value for clinical assessments regarding risk of early treatment discontinuation.

Racial and Ethnic Differences in Cannabis Use Following Legalization in US States With Medical Cannabis Laws.

Importance: Little is known about changes in cannabis use outcomes by race and ethnicity following the enactment of recreational cannabis laws (RCLs). Objectives: To examine the association between enactment of state RCLs and changes in cannabis outcomes by race and ethnicity overall and by age groups in the US. Design, Setting, and Participants: This cross-sectional study used restricted use file data from the National Surveys of Drug Use and Health between 2008 and 2017, which were analyzed between September 2019 and March 2020. National survey data included the entire US population older than 12 years. Main Outcomes and Measures: Self-reported past-year and past-month cannabis use and, among people that used cannabis, daily past-month cannabis use and past-year Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) cannabis use disorder. Multi-level logistic regressions were fit to estimates changes in cannabis use outcomes by race and ethnicity overall and by age between respondents in states with and without enacted RCLs, controlling for trends in states with medical cannabis laws or no cannabis laws. Results: A total of 838 600 participants were included for analysis (mean age, 43 years [range, 12-105 years]; 434 900 women [weighted percentage, 51.5%]; 511 900 participants (weighted percentage, 64.6%) identified as non-Hispanic White, 99 000 (11.9%) as non-Hispanic Black, 78 400 (15.8%) as Hispanic, and 149 200 (7.6%) as other (including either Native American, Pacific Islander, Asian, or more than 1 race or ethnicity). Compared with the period before RCL enactment, the odds of past-year cannabis use after RCL enactment increased among Hispanic (adjusted odds ratio [aOR], 1.33; 95% CI, 1.15-1.52), other (aOR, 1.31; 95% CI, 1.12-1.52), and non-Hispanic White (aOR, 1.21; 95% CI, 1.12-1.31) populations, particularly among those aged 21 years or more. Similarly, the odds of past-month cannabis use increased among Hispanic (aOR, 1.43; 95% CI, 1.22-1.69), other (aOR, 1.43; 95% CI, 1.20-1.70), and non-Hispanic White (aOR, 1.24; 95% CI, 1.13-1.35) populations after RCL enactment. No increases were found in the odds of past-year or past-month cannabis use post-RCL enactment among non-Hispanic Black individuals or among individuals aged 12 to 20 years for all race and ethnicity groups. In addition, among people who used cannabis, while no increases were found in past-month daily cannabis in any racial or ethnic group, the odds of cannabis use disorder increased post-RCL among individuals categorized as other overall (aOR, 1.45; 95% CI, 1.07-1.95), but no increases were found by age group. Conclusions and Relevance: Changes in cannabis use by race and ethnicity that may be attributable to policy enactment and variations in recreational policy provisions should be monitored. To ensure that the enactment of recreational cannabis laws truly contributes to greater equity in outcomes and adheres to antiracist policies, monitoring unintended and intended consequences that may be attributable to recreational cannabis use and similar policies by race and ethnicity is needed.

Joint perceptions of the risk and availability of Cannabis in the United States, 2002-2018.

BACKGROUND: Prior work suggests that perceived risk and perceived availability of cannabis independently affect cannabis use. However, perceived risk likely modifies the effect of perceived availability, and vice versa. This study explored trends in joint perceived risk and availability of cannabis from 2002 to 2018 and the relationship between combined perceptions and cannabis use, frequent use, and cannabis use disorder (CUD). METHODS: National Surveys on Drug Use and Health data (n = 949,285, ages 12+) were used to create combined categories of perceived risk of weekly cannabis use and perceived cannabis availability. Descriptive analyses compared joint perceived risk/availability trends (pre/post-2015 due to survey redesign) overall and stratified by age, gender, past-year cannabis use, frequent use, and CUD. Regression analysis estimated associations between perceived risk/availability and cannabis outcomes. RESULTS: From 2002 to 2018, the prevalence of perceiving cannabis as low-risk doubled while perceiving cannabis as available remained unchanged. The proportion of individuals perceiving cannabis as Low-risk/Available increased by 86% from 2002 to 2014 (16.8%-31.2%) and 19% from 2015 to 2018 (30.1%-35.8%) while High-risk/Available and High-risk/Unavailable proportions declined. Differing patterns were observed by age and gender. Compared with individuals perceiving cannabis as High-risk/Unavailable, people in all other perception categories had greater risk of all cannabis outcomes. Results were consistent with additive interaction between perceived risk and availability in their effects on cannabis use. CONCLUSIONS: Trends and associations with cannabis outcomes differ when considering perceived risk and availability independently versus jointly. Longitudinal studies and cannabis policy evaluations would advance understanding of links between cannabis perceptions and use.

Prescription Opioid Laws and Opioid Dispensing in US Counties: Identifying Salient Law Provisions With Machine Learning.

BACKGROUND: Hundreds of laws aimed at reducing inappropriate prescription opioid dispensing have been implemented in the United States, yet heterogeneity in provisions and their simultaneous implementation have complicated evaluation of impacts. We apply a hypothesis-generating, multistage, machine-learning approach to identify salient law provisions and combinations associated with dispensing rates to test in future research. METHODS: Using 162 prescription opioid law provisions capturing prescription drug monitoring program (PDMP) access, reporting and administration features, pain management clinic provisions, and prescription opioid limits, we used regularization approaches and random forest models to identify laws most predictive of county-level and high-dose dispensing. We stratified analyses by overdose epidemic phases-the prescription opioid phase (2006-2009), heroin phase (2010-2012), and fentanyl phase (2013-2016)-to further explore pattern shifts over time. RESULTS: PDMP patient data access provisions most consistently predicted high-dispensing and high-dose dispensing counties. Pain management clinic-related provisions did not generally predict dispensing measures in the prescription opioid phase but became more discriminant of high dispensing and high-dose dispensing counties over time, especially in the fentanyl period. Predictive performance across models was poor, suggesting prescription opioid laws alone do not strongly predict dispensing. CONCLUSIONS: Our systematic analysis of 162 law provisions identified patient data access and several pain management clinic provisions as predictive of county prescription opioid dispensing patterns. Future research employing other types of study designs is needed to test these provisions' causal relationships with inappropriate dispensing and to examine potential interactions between PDMP access and pain management clinic provisions. See video abstract at, http://links.lww.com/EDE/B861.

State criminal justice policy context and opioid agonist treatment delivery among opioid treatment admissions, 2015.

BACKGROUND: Criminal justice referral to treatment is associated with reduced odds of receiving opioid agonist treatment (OAT), the gold-standard treatment for opioid use disorder. States vary substantially in the extent of criminal justice system involvement in opioid treatment; however, the effects on treatment provision are not clear. We examined whether state-level criminal justice involvement in the substance use treatment system modified the association between criminal justice referral to treatment and OAT provision among opioid treatment admissions. METHODS: We conducted a random effects logistic regression to investigate how the effects of criminal justice referral to treatment on OAT provision differed in states with high vs. low state-level criminal justice involvement in opioid treatment, adjusting for individual and state-level covariates, among 22 states in the 2015 Treatment Episode Dataset-Admissions. RESULTS: Criminal justice referral to treatment was associated with an 85% reduction in the odds of receiving OAT, compared to other sources of treatment referral (OR = 0.15; 95% CI: 0.15, 0.16). Among opioid treatment admissions resulting from criminal justice referral in 2015, receiving treatment in high criminal justice involvement states was associated with a 63% reduction in the odds of OAT provision, compared to opioid treatment received in low criminal justice involvement states (interaction OR = 0.37, 95% CI: 0.11, 0.89). CONCLUSION: The effects of criminal justice referral to treatment on OAT provision varied by criminal justice involvement in opioid treatment at the state level. Targeted interventions should increase access to OAT in states that rely on the criminal justice system for opioid treatment referrals.

Association of US Medical Marijuana Laws With Nonmedical Prescription Opioid Use and Prescription Opioid Use Disorder.

Importance: Between 1997 and 2017, the United States saw increases in nonmedical prescription opioid use and its consequences, as well as changes in marijuana policies. Ecological-level research hypothesized that medical marijuana legalization may reduce prescription opioid use by allowing medical marijuana as an alternative. Objectives: To investigate the association of state-level medical marijuana law enactment with individual-level nonmedical prescription opioid use and prescription opioid use disorder among prescription opioid users and to determine whether these outcomes varied by age and racial/ethnic groups. Design, Setting, and Participants: This cross-sectional study used restricted data on 627 000 individuals aged 12 years and older from the 2004 to 2014 National Survey on Drug Use and Health, a population-based survey representative of the civilian population of the United States. Analyses were completed from March 2018 to May 2018. Exposures: Time-varying indicator of state-level medical marijuana law enactment (0 = never law enactment, 1 = before law enactment, and 2 = after law enactment). Main Outcomes and Measures: Past-year nonmedical prescription opioid use and prescription opioid use disorder among prescription opioid users. Odds ratios of nonmedical prescription opioid use and prescription opioid use disorder comparing the period before and after law enactment were presented overall, by age and racial/ethnic group, and adjusted for individual- and state-level confounders. Results: The study sample included 627 000 participants (51.51% female; 9.88% aged 12-17 years, 13.30% aged 18-25 years, 14.30% aged 26-34 years, 25.02% aged 35-49 years, and 37.50% aged ≥50 years; the racial/ethnic distribution was 66.97% non-Hispanic white, 11.83% non-Hispanic black, 14.47% Hispanic, and 6.73% other). Screening and interview response rates were 82% to 91% and 71% to 77%, respectively. Overall, there were small changes in nonmedical prescription opioid use prevalence after medical marijuana law enactment (4.32% to 4.86%; adjusted odds ratio, 1.13; 95% CI, 1.06-1.20). Prescription opioid use disorder prevalence among prescription opioid users decreased slightly after law enactment, but the change was not statistically significant (15.41% to 14.76%; adjusted odds ratio, 0.95; 95% CI, 0.81-1.11). Outcomes were similar when stratified by age and race/ethnicity. Conclusions and Relevance: This study found little evidence of an association between medical marijuana law enactment and nonmedical prescription opioid use or prescription opioid use disorder among prescription opioid users. Further research should disentangle the potential mechanisms through which medical marijuana laws may reduce opioid-related harm.

Deep structural brain lesions associated with consciousness impairment early after hemorrhagic stroke.

The purpose of this study was to determine the significance of deep structural lesions for impairment of consciousness following hemorrhagic stroke and recovery at ICU discharge. Our study focused on deep lesions that previously were implicated in studies of disorders of consciousness. We analyzed MRI measures obtained within the first week of the bleed and command following throughout the ICU stay. A machine learning approach was applied to identify MRI findings that best predicted the level consciousness. From 158 intracerebral hemorrhage patients that underwent MRI, one third was unconscious at the time of MRI and half of these patients recovered consciousness by ICU discharge. Deep structural lesions predicted both, impairment and recovery of consciousness, together with established measures of mass effect. Lesions in the midbrain peduncle and pontine tegmentum alongside the caudate nucleus were implicated as critical structures. Unconscious patients predicted to recover consciousness by ICU discharge had better long-term functional outcomes than those predicted to remain unconscious.

Adverse Event Profile Associated with Prolonged Use of CentriMag Ventricular Assist Device for Refractory Cardiogenic Shock.

Several studies have investigated early outcomes with a surgical short-term ventricular assist device (VAD), but little is known about adverse event profile during prolonged support with a surgical short-term VAD. This is a retrospective analysis of 161 patients who received a CentriMag ventricular assist system (Abbott Laboratories, Abbott Park, IL) at our institution between January 2007 and June 2014. Device-related adverse events include major bleeding, infection, and stroke incidents occurring during CentriMag support. Cumulative frequency of adverse events was estimated by Nelson's nonparametric method. One hundred and forty-three (88.8%) patients had biventricular VAD and 18 (11.2%) had isolated left VAD. Median duration of support was 16 days (interquartile range [IQR]: 10-29). Mortality was 24.8% and 1 year overall survival is 51.8% (95% CI: 43.3-59.5%). The most common adverse event during support was major bleeding (n = 121, 75.1%). Ninety-five (59.0%) developed major infections such as pneumonia and urinary tract infection. Sixteen patients (10%) experienced stroke. Cumulative data analysis showed that stroke and reoperation caused by bleeding were rare beyond 30 days, whereas infection and nonsurgical bleeding events were directly related to support time. In conclusion, temporary VAD with CentriMag support is an effective treatment for patients in refractory cardiogenic shock. Despite its side effect, profile including a high rate of blood transfusion early in the immediate postoperative period of CentriMag support, aggressive use of the CentriMag support device has acceptable survival to discharge and 1 year survival.

Associations between state-level policy liberalism, cannabis use, and cannabis use disorder from 2004 to 2012: Looking beyond medical cannabis law status.

BACKGROUND: Medical cannabis laws (MCL) have received increased attention as potential drivers of cannabis use (CU), but little work has explored how the broader policy climate, independent of MCL, may impact CU outcomes. We explored the association between state-level policy liberalism and past-year cannabis use (CU) and cannabis use disorder (CUD). METHODS: We obtained state-level prevalence of past-year CU and CUD among past year cannabis users for ages 12-17, 18-25, and 26+ from the 2004-2006 and 2010-2012 National Surveys on Drug Use and Health. States were categorized as liberal, moderate, or conservative based on state-level policy liberalism rankings in 2005 and 2011. Linear models with random state effects examined the association between policy liberalism and past-year CU and CUD, adjusting for state-level social and economic covariates and medical cannabis laws. RESULTS: In adjusted models, liberal states had higher average past-year CU than conservative states for ages 12-17 (+1.58 percentage points; p = 0.03) and 18-25 (+2.96 percentage points; p = 0.01) but not for 26+ (p = 0.19). CUD prevalence among past year users was significantly lower in liberal compared to conservative states for ages 12-17 (-2.87 percentage points; p = 0.045) and marginally lower for ages 26+ (-2.45 percentage points; p = 0.05). CONCLUSION: Liberal states had higher past-year CU, but lower CUD prevalence among users, compared to conservative states. Researchers and policy makers should consider how the broader policy environment, independent of MCL, may contribute to CU outcomes.

Impact of Medical Marijuana Laws on State-Level Marijuana Use by Age and Gender, 2004-2013.

In states that have passed medical marijuana laws (MMLs), marijuana use (MU) increased after MML enactment among people ages 26 and older, but not among ages 12-25. We examined whether the age-specific impact of MMLs on MU varied by gender. Data were obtained from the 2004-2013 restricted-use National Survey on Drug Use and Health, aggregated at the state level. The exposure was a time-varying indicator of state-level MML (0 = No Law, 1 = Before Law, 2 = After Law). Outcomes included past-month MU prevalence, daily MU prevalence among past-year users (i.e., 300+ days/year), and past-year marijuana use disorder (MUD) prevalence. Linear models tested the state-level MML effect on outcomes by age (12-17, 18-25, 26+) and gender. Models included a state-level random intercept and controlled for time- and state-level covariates. Past-month MU did not increase after enactment of MML in men or women ages 12-25. Among people 26+, past-month MU increased for men from 7.0% before to 8.7% after enactment (+ 1.7%, p < 0.001) and for women from 3.1% before to 4.3% after enactment (+ 1.1%, p = 0.013). Among users 26+, daily MU also increased after enactment in both genders (men 16.3 to 19.1%, + 2.8%, p = 0.014; women 9.2 to 12.7%, + 3.4%, p = 0.003). There were no statistically significant increases in past-year MUD prevalence for any age or gender group after MML enactment. Given the statistically significant increase in daily use among past-year users aged 26+ following enactment, education campaigns should focus on informing the public of the risks associated with regular marijuana use.