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      COVID-19 risk and outcomes in patients with substance use disorders: analyses from electronic health records in the United States

      1 , 2 , , 1 , , 3

      Molecular Psychiatry

      Nature Publishing Group UK

      Addiction, Diseases

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          Abstract

          The global pandemic of COVID-19 is colliding with the epidemic of opioid use disorders (OUD) and other substance use disorders (SUD) in the United States (US). Currently, there is limited data on risks, disparity, and outcomes for COVID-19 in individuals suffering from SUD. This is a retrospective case-control study of electronic health records (EHRs) data of 73,099,850 unique patients, of whom 12,030 had a diagnosis of COVID-19. Patients with a recent diagnosis of SUD (within past year) were at significantly increased risk for COVID-19 (adjusted odds ratio or AOR = 8.699 [8.411–8.997], P < 10 −30), an effect that was strongest for individuals with OUD (AOR = 10.244 [9.107–11.524], P < 10 −30), followed by individuals with tobacco use disorder (TUD) (AOR = 8.222 ([7.925–8.530], P < 10 −30). Compared to patients without SUD, patients with SUD had significantly higher prevalence of chronic kidney, liver, lung diseases, cardiovascular diseases, type 2 diabetes, obesity and cancer. Among patients with recent diagnosis of SUD, African Americans had significantly higher risk of COVID-19 than Caucasians (AOR = 2.173 [2.01–2.349], P < 10 −30), with strongest effect for OUD (AOR = 4.162 [3.13–5.533], P < 10 −25). COVID-19 patients with SUD had significantly worse outcomes (death: 9.6%, hospitalization: 41.0%) than general COVID-19 patients (death: 6.6%, hospitalization: 30.1%) and African Americans with COVID-19 and SUD had worse outcomes (death: 13.0%, hospitalization: 50.7%) than Caucasians (death: 8.6%, hospitalization: 35.2%). These findings identify individuals with SUD, especially individuals with OUD and African Americans, as having increased risk for COVID-19 and its adverse outcomes, highlighting the need to screen and treat individuals with SUD as part of the strategy to control the pandemic while ensuring no disparities in access to healthcare support.

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          Most cited references 15

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          Collision of the COVID-19 and Addiction Epidemics

          People with substance use disorder may be especially susceptible to COVID-19, and compromised lung function from COVID-19 could also put at risk those who have opioid use disorder and methamphetamine use disorder. This commentary describes the risks of the collision of the COVID-19 and addiction epidemics.
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            Tobacco Product Use and Cessation Indicators Among Adults — United States, 2018

            Cigarette smoking is the leading cause of preventable disease and death in the United States ( 1 ). The prevalence of adult cigarette smoking has declined in recent years to 14.0% in 2017 ( 2 ). However, an array of new tobacco products, including e-cigarettes, has entered the U.S. market ( 3 ). To assess recent national estimates of tobacco product use among U.S. adults aged ≥18 years, CDC, the Food and Drug Administration (FDA), and the National Cancer Institute analyzed data from the 2018 National Health Interview Survey (NHIS). In 2018, an estimated 49.1 million U.S. adults (19.7%) reported currently using any tobacco product, including cigarettes (13.7%), cigars (3.9%), e-cigarettes (3.2%), smokeless tobacco (2.4%), and pipes* (1.0%). Most tobacco product users (83.8%) reported using combustible products (cigarettes, cigars, or pipes), and 18.8% reported using two or more tobacco products. The prevalence of any current tobacco product use was higher in males; adults aged ≤65 years; non-Hispanic American Indian/Alaska Natives; those with a General Educational Development certificate (GED); those with an annual household income 30% that are not presented. ††† Hispanic persons could be of any race. All other racial/ethnic groups were non-Hispanic. §§§ Northeast: Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, and Vermont; Midwest: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, and Wisconsin; South: Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, and West Virginia; West: Alaska, Arizona, California, Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming. ¶¶¶ Based on income variables from the family file (n = 8,310 missing valid income data). Imputed income files were not used in this analysis. **** Private coverage: includes adults who have any comprehensive private insurance plan (including health maintenance organizations and preferred provider organizations). Medicaid: for adults aged 30%; neither daily use nor nondaily use is presented. The figure is a bar chart showing the prevalence of daily and nondaily use of selected tobacco products among adults aged ≥18 years who currently use each tobacco product, in the United States, during 2018. The prevalence of any current tobacco product use was higher among males (25.8%) than among females (14.1%) and among persons aged 25–44 years (23.8%), 45–64 years (21.3%), and 18–24 years (17.1%) than among those aged ≥65 years (11.9%) (Table). Current tobacco product use was also higher among non-Hispanic American Indian/Alaska Native adults (32.3%), non-Hispanic multiracial adults (25.4%), non-Hispanic whites (21.9%), non-Hispanic blacks (19.3%), and Hispanic adults (13.8%) than among non-Hispanic Asian adults (10.0%), as well as among those who lived in the Midwest (23.6%) or the South U.S. Census regions (21.4%) than among those who lived in the West (15.3%) or the Northeast (17.5%). The prevalence of current tobacco product use was also higher among persons who had a GED (41.4%) than among those with other levels of education and among those who were divorced, separated, or widowed (22.6%) or single, never married, or not living with a partner (21.1%) than among those married or living with a partner (18.4%). Current tobacco product use was higher among persons with an annual household income 1 day during the past 12 months because they were trying to quit smoking and former smokers who quit during the past year. † Percentage of former cigarette smokers who quit smoking for ≥6 months during the past year, among current smokers who smoked for ≥2 years and former smokers who quit during the past year. § Percentage of persons who ever smoked (≥100 cigarettes during lifetime) who have quit smoking. The figure is a line chart showing the prevalence of past-year quit attempts and recent cessation and quit ratio among cigarette smokers aged ≥18 years, in the United States, during 2009–2018. Discussion The approximate two thirds decline in adult cigarette smoking prevalence that has occurred since 1965 represents a major public health success ( 1 ). In 2018, 13.7% of U.S. adults aged ≥18 years currently smoked cigarettes, the lowest prevalence recorded since 1965. However, no significant change in cigarette smoking prevalence occurred during 2017–2018. Most cigarette smokers and smokeless tobacco users reported daily use, whereas most e-cigarette and cigar users reported nondaily use. Even nondaily use of cigarettes has been linked to increased mortality risk ( 6 ). Quitting smoking at any age is beneficial for health ( 1 , 4 ). During 2009–2018, significant linear increases occurred in quit attempts, recent successful cessation, and quit ratio. Population-based tobacco control interventions, including high-impact tobacco education campaigns like CDC’s Tips From Former Smokers (https://www.cdc.gov/tobacco/campaign/tips/index.html) campaign and FDA’s Every Try Counts campaign (https://www.fda.gov/tobacco-products/every-try-counts-campaign), combined with barrier-free access to evidence-based cessation treatments, can both motivate persons who use tobacco products to try to quit and help them succeed in quitting. The prevalence of adult e-cigarette use increased from 2.8% in 2017 to 3.2% in 2018 but was much lower than the 20.8% ( 7 ) of U.S. high school students reporting past 30-day e-cigarette use in 2018. The prevalence of e-cigarette use among persons aged 18–24 years is higher than that among other adult age groups, and e-cigarette use in this age group increased from 5.2% in 2017 ( 2 ) to 7.6% in 2018. During 2014–2017 there had been a downward trajectory of adult e-cigarette use ( 2 , 8 ), but during 2017–2018 a significant increase in adult e-cigarette use was detected for the first time. This increase might be related to the emergence of new types of e-cigarettes, especially “pod-mod” devices, which frequently use nicotine salts as opposed to the free-base nicotine used in other e-cigarettes and tobacco products. Sales of JUUL, a pod-mod device, increased by approximately 600% from 2016 to 2017, making it the dominant e-cigarette product in the United States by the end of 2017 ( 9 ). Further research is needed to monitor patterns of e-cigarette use and the relationship between use of e-cigarettes and other tobacco products (e.g., cigarette smoking). The findings in this report are subject to at least three limitations. First, responses were self-reported and were not validated by biochemical testing. However, self-reported smoking status correlates highly with serum cotinine levels ( 10 ). Second, because NHIS is limited to the noninstitutionalized U.S. civilian population, the results are not generalizable to institutionalized populations and persons in the military. Finally, the NHIS Sample Adult response rate of 53.1% might have resulted in nonresponse bias. Coordinated efforts at the local, state, and national levels are needed to continue progress toward reducing tobacco-related disease and death in the United States. Proven strategies include implementation of tobacco price increases, comprehensive smoke-free policies, high-impact antitobacco media campaigns, barrier-free cessation coverage, and comprehensive state tobacco control programs, combined with regulation of the manufacturing, marketing, and distribution of all tobacco products ( 1 , 4 ). Summary What is already known about this topic? Cigarette smoking is the leading cause of preventable disease and death in the United States. Adult cigarette smoking prevalence has declined; however, new tobacco products, including e-cigarettes, have entered the U.S. market. What is added by this report? In 2018, approximately 20% of U.S. adults currently used any tobacco product; cigarette smoking reached an all-time low (13.7%). During 2009–2018, significant increases in three cigarette cessation indicators occurred. During 2017–2018, e-cigarette and smokeless tobacco product use prevalence increased. What are the implications for public health practice? Continued surveillance is critical to informing tobacco control efforts at the national, state, and local levels. Coordinated efforts and regulation of all tobacco products are needed to reduce tobacco-related disease and death in the United States.
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              COVID-19 and Smoking

              COVID-19 is mainly a disease of the respiratory tract characterized by a severe acute respiratory syndrome; the causative agent is SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2). The virus main entrance way is through mucosal tissues: nose, mouth, upper respiratory tract, and less frequently conjunctival mucosa. Tobacco smoke exposure results in inflammatory processes in the lung, increased mucosal inflammation, expression of inflammatory cytokines and tumor necrosis factor α, increased permeability in epithelial cells, mucus overproduction, and impaired mucociliary clearance. 1 Knowledge about host factors, and in particular avoidable host factors such as smoking, may be of importance in reducing viral contamination and the severity of the disease. The SARS-CoV-2 pandemic started in Wuhan, China toward the end of 2019. To the best of our knowledge and at the time of the writing of this Commentary, six published case series reported the prevalence of smoking among individuals with COVID-19 (Table 1). The study with the highest number of patients compared severe (N = 173) to nonsevere (N = 926) cases. The percent of current and former smokers were higher among the severe cases: 17% and 5%, respectively, than among the nonsevere cases (12% and 1%, respectively). 2 More importantly, among those with the primary composite end point (admission to an intensive care unit, the use of mechanical ventilation, or death), the proportion of smokers was higher with than among those without this end point (26% vs. 12%). 2 Another case series also showed more smokers among the severe (N = 58) than among the nonsevere (N = 82) cases. 3 The single modifiable host factor associated with progression of COVID-19 pneumonia was current smoking in a multivariable logistic analysis (odds ratio = 14.3, 95% confidence interval: 1.6–25.0). 4 Among those who died the number of smokers was also been found to be somewhat higher (9%, 5/54) than among survivors (6%, 9/137). 5 Table 1. Frequency of Smoking and Former Smoking Among COVID-19 Patients. N (%) Guan et al. 2 Nonsevere, N = 926 Severe, N = 173 Primary composite end point (admission to an intensive care unit, the use of mechanical ventilation, or death) Never smoked 793/913 (86.9) 134/172 (77.9) Yes 44/66 (66.7%) No 883/1019 (86.7%) Former smoker 12/913 (1.3) 9/172 (5.2) Yes 5/66 (7.6%) No 16/1019 (1.6%) Current smoker 108/913 (11.8) 29/172 (16.9) Yes 7/66 (25.8%) No 120/1019 (11.8%) Zhang et al. 3 Hospitalized for COVID-19 Nonsevere, N = 82 Severe, N = 58 Current smokers 0/82 2/58 (3.4) Past-smokers 3/82 (3.7) 4/58 (6.9) Cigarettes smoked per day × years of smoking   15 years). 14 The similar upregulation associated with smoking of two different virus receptors observed with two different coronaviruses suggests that smoking contributes to the higher number of viral receptors and may support the findings of the recent case series observations. It is also worth noting that smoking behavior is characterized by inhalation and by repetitive hand-to-mouth movements which are strongly advised against to reduce viral contamination. Public health interventions, such as lockdown, may increase the exposure of family members to secondhand smoke. Lockdown may be an opportune moment to quit to reduce not only the smoker’s health risk but also that of his/her family members. Finally, risk factors of COVID-19 severity (lung and cardiovascular disorders, diabetes, etc.) are more frequent among smokers. Smoking cessation by any means should be a priority among smokers with comorbidities. Future Research Directions The nicotine and tobacco research community should explore the role of tobacco in the current COVID-19 pandemic. We need stronger evidence about the association of smoking with COVID-19. Databases should be identified and analyses focused on the role of this association in virus contamination, severity of the illness, ability to recover, and so on. Smoking status data should be systematically recorded and analyzed among COVID-19 patients. We need data about the immediate and short-term benefit of quitting smoking among symptomatic COVID-19 smokers. Laboratory studies should focus on quantifying the viral contamination of tobacco products with particular attention to shared products such as waterpipes. We also need data about alternative nicotine delivery systems and their risk/benefit ratio in relation to COVID-19. Public Health Challenges/Opportunities We suggest that ongoing public health campaigns should include reference to the importance of smoking cessation during the pandemic. Health care providers should be involved in offering evidence-based pharmacological and behavioral smoking cessation interventions by remote support. Quit lines should promote contacts with smokers with or without COVID-19, symptomatic or asymptomatic. Lockdown may result in social isolation and mental distress both increasing the need for smoking; smoking is more prevalent among economically less-advantaged groups, and they are potentially at higher risk for COVID-19. Large-scale interventions should be targeted at these populations in particular. Supplementary Material A Contributorship Form detailing each author’s specific involvement with this content, as well as any supplementary data, are available online at https://academic.oup.com/ntr. Declaration of Interests None declared.
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                Author and article information

                Contributors
                rxx@case.edu
                nvolkow@nida.nih.gov
                Journal
                Mol Psychiatry
                Mol. Psychiatry
                Molecular Psychiatry
                Nature Publishing Group UK (London )
                1359-4184
                1476-5578
                14 September 2020
                : 1-10
                Affiliations
                [1 ]GRID grid.67105.35, ISNI 0000 0001 2164 3847, Center for Artificial Intelligence in Drug Discovery, School of Medicine, , Case Western Reserve University, ; Cleveland, OH USA
                [2 ]GRID grid.430779.e, ISNI 0000 0000 8614 884X, Departments of Internal Medicine and Pediatrics and the Center for Clinical Informatics Research and Education, , The MetroHealth System, ; Cleveland, OH USA
                [3 ]GRID grid.94365.3d, ISNI 0000 0001 2297 5165, National Institute on Drug Abuse, , National Institutes of Health, ; Bethesda, MD USA
                Article
                880
                10.1038/s41380-020-00880-7
                7488216
                © Springer Nature Limited 2020

                This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.

                Funding
                Funded by: FundRef https://doi.org/10.13039/100000049, U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging);
                Award ID: AG061388
                Award ID: AG062272
                Award Recipient :
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging)
                Funded by: FundRef https://doi.org/10.13039/100000048, American Cancer Society (American Cancer Society, Inc.);
                Award ID: RSG-16-049-01
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100006108, U.S. Department of Health & Human Services | NIH | National Center for Advancing Translational Sciences (NCATS);
                Award ID: 1UL1TR002548-01
                Award Recipient :
                Categories
                Immediate Communication

                Molecular medicine

                addiction, diseases

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